Design of Training Systems, Phase I Final Report 234p. - ERIC

DOCUMENT RESUME

ED 089 779 IR 000 504

AUTHOR Bellamy, Harold J.; And OthersTITLE Design of Training Systems, Phase I Final Report

Appendices, Volume II of II.INSTITUTION Naval Training Equipment Center, Orlando, Fla.

Training Analysis and Evaluation Group.REPORT NO IBM-FSD-ESC-73-535-004;

NAVTRADQUIPCEN-TAEG-12-1-v-2PUB DATE Dec 73NOTE 234p.; For related documents see IR 000 502 and IR

000 503

EDRS PRICE MF-$0.75 HC-$11.40 PLUS POSTAGEDESCRIPTORS Computer Oriented Programs; *Computers; Data Eases;

*Educational Programs; Educational Technology;Management; *Management Systems; *MathematicalModels; *Military Training; Models; ProgramDescriptions

IDENTIFIERS *Design of Training Systems; DOTS; United StatesNavy

ABSTRACTA series of five appendixes presents details related

to Phase I of the three-stage project ',Design of Training Systems"(DOTS) . The first appendix discusses strategic assumptiOns andprocesses, while the second reviews mathematical models and databases operational within the navel education and training command.The third appendix provides a bibliography of materials on threetopics--mathematical modeling techniques, educational technology, andnaval instructions and related pertinent matters. The fourth appendixlists the activities and locations visited in this phase of theproject and the fifth provides a glossary of significant terms.(PB)

TRAININGANALYSISANDEVALUATION

MIR GROUP

TAEG REPORT

NO.12-1DESIGN OF TRAINING SYSTEMSPHASE I REPORT Volume 2

II

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Technical Report: TAEG REPORT NO. 12-1

DESIIN OF TRAINING SYSTEMS

PHASE I REPORT

ABSTRACT

This report presents a functional descriptive model of the currentNaval Education and Training System and idealized concepts orientedtoward a 1980 time frame.. While technological gaps and problem areasare presented, no organizational. elements. are. specified, since theprime areas of interest are the functions performed. In addition,the rationale for selection of candidate mathematical models to bedeveloped in Phase II is given.

Strategic working assumptions for the 19809s are presented in Volume2 of this report.

The study was performed by IBM for the Training Analysis and EvaluationGroup of the Naval Training Equipment Center, Orlando, Florida (Contract No. N61339 -73 -C -0097).

Reproduction of this,in whole or. in part is permittedfor any purpose of the UnitedStates Government

TAEG REPORT NO. 12-1

TABLE OF CONTENTS

VOLUME 2 - APPENDICES

APPENDIX A STRATEGIC ASSUMPTIONS

SECTION PAGE

Abstract

I. THE STRATEGIC PROCESS

A. INTRODUCTION A-I-1

1. Strategic Planning and NETS A-I-12. Pertinence to the DOTS Project A-I-23. Sources A-I-24. Planning Levels A-I-2

B. OBJECTIVES - STRATEGIC PROCESS A-I-3

1. Definition of Objectives A-I-32. Objective Exclusions A-I-3

C. FORMAT/PROCEDURAL DESCRIPTION A-I-4

1. Assumption Form - Description A-I-42, Procedural A-I-53. General Comments A-I-6

II. STRATEGIC ASSUMPTIONS AND STRUCTURE

A. DESCRIPTION A-II-1

1. Index A-II-12. Charts A-II-13. Structure A-II-1

B. STRATEGIC ASSUMPTION INDEX A-II-1

C. STRATEGIC ASSUMPTION CHARTS A-II-6

D. STRATEGIC ASSUMPTION STRUCTURE A-II-87

NOTE: A separate bibliography is not included for Appendix A sincesources are listed on each SA form in Section II. Paragraph C.


APPENDIX B MATHEMATICAL MODELS AND DATA BASES OPERATIONAL WITHINTHE NAVA1 EDUCATION AND TRAINING COMMAND

SECTION PAGE

OPERATIONAL DATA BASES B-I-1

A. FORMAL TRAINING DATA SYSTEM (FTDS) B-I-1

1. Master Course Reference File (MCRF) B-I-1

2. Student Master File (SMF) B-I-1

3. Student Candidate File (SCF) 8-1-2

B. TRAINING ADMINISTRATION SYSTEM (TRAD) B-I-2

C. PER CAPITA COST-TO-TRAIN B-I-3

D. MECHANIZED COURSE COST SYSTEM B-I-4

E. NAVAL AVIATION TRAINING INFORMATION SYSTEM (NATIS) B-I-5

F. MECHANIZED TRAINING EQUIPMENT REQUIREMENTS PLANB-II-1(MECTERP)

G. TRAINING AIDS MATERIAL AUTOMATED REPORTING SYSTEM(TAMARS)

II DATA BASES UNDER DEVELOPMENT B-II-1

A. NAVAL AIR TRAINING COMMAND MANAGEMENT INFORMATIONSUBSYSTEM (NATIS) B-II-2

1. Planning B-II-22. Personnel B-II-23. Training B-II-24. Maintenance B-I1-25. Resources Management B-II-26. Supply B-II-3

B. NAVY INTEGRATED TRAINING AND RESOURCES ADMINISTRA-TION SUBSYSTEM (NITRAS) B-II-3

C. MILITARY PERSONNEL INFORMATION SUBSYSTEM (MILPERSIS) B-II-3

D. CENTRALIZED TRAINING MATERIAL MANAGEMENT SUBSYSTEM(CENTRA) B-II-3

ii


SECTION PAGE

III OPERATIONAL MATHEMATICAL MODELS B-III-1

Status- Time - Attrition - Planning (STAPLAN) B-III-3Recruit Input Optimization Model (RIO) B-III-4Integrated Facilities Requirements System (IFRS) B-III-5U.S. Navy Computer-Assisted Recruit Assignment Model(COMPASS) B-III-6

Computerized Advance Personnel Requirements InformationSystem - Billet and Inventory Subsystem (CAPRI - B&ISubsystem) B-III-7

Computerized Occupational Data Analysis (CODAP) . . . , 8-111-8Cost of Attaining Personnel Requirements Model (CAPER) . . B-III-9Nuclear Power Training Input (9901 Model) B- III -1O

A Network Flow Technique for Optimizing Personnel On-Board by Paygrade B-III-11

iii

TAEG REPORT NO. 12 -I

APPENDIX C BIBLIOGRAPHY

SECTION PAGE

INTRODUCTION C-I-1

II MATHEMATICAL MODELING TECHNIQUES C-II-1

A. LINEAR PROGRAMMING APPLICATIONS C-II-1

B. NETWORK FLOW MODELS C-II-13

C. LINEAR REGRESSION MODELS C-II-15

D. MARKOV MODELS C-II-18

E. MATHEMATICAL ANALYTIC MODELS C-II-21

F. SIMULATION MODELS C-II-28

G. MODEL SURVEYS C-II-33

III EDUCATIONAL TECHNOLOGY C-III-1

A. COUNSELING C-III-1

B. EDUCATIONAL INFORMATION SYSTEMS C-III-4

C. EDUCATiONAL PLANNING C-III-6

D. TRAINING TECHNIQUES/MEDIA C-III-7

E. TRAINING FEEDBACK C-III-16

F. COURSE DESIGN I C-III-18

G. LEARNING PROCESS ANALYSIS C-III-20

H. SYSTEMS APPROACH TO EDUCATION/TRAINING C-III-23

I. TASK ANALYSIS C-III-27

J. TRAINING COST ANALYSIS C-III-30

IV BIBLIOGRAPHY OF PERTINENT NAVAL INSTRUCTIONS ANDREFERENCES C-IV-1

iv


PAGE

APPENDIX D ACTIVITIES/LOCATIONS VISITED

APPENDIX E GLOSSARY E-I-1


DESIGN OF TRAINING SYSTEMS

PHASE I - REPORT APPENDIX A

STRATEGIC ASSUMPTIONS

ABSTRACT

A DOTS, Phase I objective was the development of a descriptive functionalmodel of the Naval Education and Training System (NETS) which would projectan idealized system "in terms of the problems of the 1980's." Design ofthis projected system had to be based on sound Strategic Working Assump-tions (SWA).

A set of Strategic Assumptions (SA), encompassing a broad range of poten-tial impactors, was developed to form one of the supporting data bases re-quired to develop the SWA's. The SWA's provide a vehicle for logicallylinking the numerous, very broad, and sometimes philosophical StrategicAssumptions to the specific tactical assumptions and recommendations ofSection VI of the Phase I Report. The purpose of the appendix is to doc-ument those SA's pertinent to the idealized NETS descriptive model. Sincethis set of SA's should have application beyond the DOTS project, many areincluded that may not impact education, and the approach and format aredesigned to support other efforts.

This appendix also proposes a strategic process and format to become acomponent of the idealized NETS management system

Sources leading to the SA definitions contained in this appendix includethose Naval strategic documents made available to the contractor, a widerange of general long range predictive documents, the Phase I interviewdata, and contributions of the I8M Advisory Group.

Section II - D of this appendix provides charts linking the SA's to eachof the SWA's. The SWA's are repeated in Section VI D-2 of the Phase Ireport which also provides an expansion of. the SWA's through a series ofchange statements.

I.


APPENDIX A

STRATEGIC ASSUMPTIONS

THE STRATEGIC PROCESS

A. INTRODUCTION

1. Strategic Planning and the Naval Education Training System (NET)

Whether military, public or industrial, "training system" planningcan benefit from the application of strategic planning principles.Although development of a strategic plan or a set of strategicassumptions is a highly speculative exercise that seldom producesa "plan," which in its majority, proves correct, the process isessential to the efficient and effective management of any complextraining system having extended life because it is the only way ofproperly orienting management thinking to the future.

NETS planning, as is the case of most industrial or military trainingsystems, tends to be "driven" by strategic considerations developed"outside" the system. Correctly, the NETS planner must support theDepartment of the Navy Program Objectives and, therefore, isprimarily concerned with plans and programs that are fairly clearlyidentified and generally contained within a five to eight yearplanning horizon. Currently, there is only limited direct applica-tion of a strategic process to NETS planning although strategicdocuments such as the Navy Strategic Study (NSS), Navy Mid-RangeGuidance (NMRG), Navy Long-Range Guidance (NLRG), Navy TechnologicalForecast (NTF), etc., do have an indirect influence through theirimpact on development of the Navy Program Objectives.

Although, necessarily, the NETS management system must concentrateplanning efforts on operational and tactical planning levels (tobe defined in paragraph 4), increased emphasis on some elements ofthe strategic process can result in:

a. A systematic review and revision of NETS strategic goals andobjectives.

b. A systematic correlation of system component plans to strategicNETS direction.

c. A forced withdrawal from current operating problems forstrategic reviews.

A-I-1


The value of a "strategic process" to NETS will be in direct propor-tion to the extent it becomes a "working" component of the managementsystem. The NETS strategic process should incorporate existing navalstrategic planning, pertinent to education and training, but shouldalso include strategic "drivers" outside the existhig planning scopewhich impact training.

2. Pertinence to the DOTS Project - An objective of DOTS Phase I was todevelop an fdealfzed descriptive model of the Naval Education Train-ing System (NETS) of the 1980's. Such a model must be based on aclearly defined set of strategic assumptions. At the same time, asubset of the management systems component of this "idealized" systemwould be a viable strategic process enabling systematic developmentof "a clearly defined set of strategic assumptions." This strategicassumptions section provides:

a. The strategic assumption base for developing the 1980's"idealized" descriptive model.

b. A suggested strategic process. As a vehicle for documentingthe strategic assumptions, a format was developed that wouldfacilitate future implementation of a systematic approach toa "working" strategic process. There are many viable approachesto strategic planning and the one suggested is only one possiblealternative.

3. Sources - In developing the strategic assumption and proposed process,111-7Titsrfrom the Phase I data gathering interviews and the IBM Advisory

Group were incorporated to assure inclusion of the most current naval,industrial and educational data.

Specific sources are identified on the individual assumption charts.

4. Planning Levels - The major planning activity pertinent to aneducation or training system tends to occur within operational andtactical planning horizons. Although definitions vary from systemto system, "operational planning" can be defined as that taking placewithin an operational unit of time such as a current fiscal year."Tactical planning" will cover a more extended span and probablyexclude the current period. For example, a Navy Training Plan (NTP)developed at a Naval Training Plan Conference (NTPC) may precedeoperational use of a device or system by approximately three years.Although judgmental assumptions are involved in both operational andtactical planning, these types are based more on defined than assumed(judgmental) parameters.

Indications are that the application of a Strategic Process to thedevelopment of Strategic Assumptions (and the subsequent use ofthese SA's as a driver of the Operational/Tactical planning process)

A-I-2


will result in the greatest benefit to NETS. This is not intendedto preclude a fully developed NETS "Strategic Plan" but to recommenda reference for emphasis. For this reason, the title, STRATEGICASSUMPTIONS, has been applied to this section.

B. OBJECTIVES - STRATEGIC PROCESS

1. Definition of Objectives - The format used in documenting theStrategic Assumptions in this section was designed to support asystematic strategic planning process. In addition to supportingthe major objective of assumption presentation, the format wasdesigned to:

a. Standardize assumption definition format regardless of scope,category or level.

b. Identify sources and estimates of probability.

c. Identify other assumptions either impacting, or being impactedby, any given assumption.

d. Provide an estimate of the impact intensity on a given assumptionby others.

e. Provide a numerical identification of assumptions that would:

1) Facilitate automation of the mechanical assembly of an SAinfluence structure.

2) Facilitate the indexing of specific assumptions by level,category, item or revision.

3) Facilitate the real -time revision of the SA structurethrough exclusion, inclusion, or modification of individualassumptions.

2. Objective Exclusions - As with any strategic process, the intent isnot to:

a. Displace the detailed planning required within the operationalor tactical planning horizon, but to provide an SA base forthese types rf planning.

b. Have the strategic process determine major goals and objectivesbut to assist in their definition, validation against futureprobabilities, and inclusion in lower level planning. The dangerin a strategic process is that an SA will come to pass becauseit was included in a strategic plan, not because it was eithera valid or desirable assumption.

A-I-3

TAEG REPORT NO 12-1

C. FORMAT/PPOCEDURAL DESCRIPTION

1. Assumption Form- Description - The following describes the basicdocument used to define the Strategic Assumptions. Figure 1,Page A-I-7, illustrates the descriptions and is indexed to matchthe alphabetic designations below:

a. Assumption Identification is divided into three levels:

1) Field - major areas of strategic concern such as National,Wail/Cultural, Naval Factors, Education, Technological,etc.

2) Category - a Field is broken into categories. As examples,Research and Development under the Field of Naval Factors;Educational Technology under the Field of Education;Maintenance under Technological.

3) Item - a sub-level under Category, as examples, the "Item"57Task Modularization is under the "Category" of EducationalTechnology; the Indian Ocean under Naval Presence; DiagnosticAids' under Maintenance; etc.

4) Date - if a strategy is to be maintained on a "real time"basis, frequent revisions of Fields, Categories and Itemswill be required. The "Revision" field of the SA numberand SA date identifies the revision level.

5) Number - to precisely identify assumptions, facilitateTReirrig and automation of SA structuring, each SA isassigned a number with the following fields:

XX:XXX:XXX:XXX

FIELD ITEM REVISIONCATEGORY NUMBER

b. Assumption Statement provides a clear statement of the StrategicAssumption. This section should not be used for any significantdetail except as required to assure a clear understanding of thestatement. The "Sources" section should provide the referencesfor the planner seeking supporting detail

c. Periods define the planning horizon covered by a specific Field,Category or Item definition. It is not mandatory that allplanning horizons be equivalent. However, the smallest Periodshould be a discrete fiscal year and a planning horizon incombinations of fiscal years.

A-I-4


1) "Periods" are the subdivisions within a planning horizonand may be of variable length within a horizon. For thatreason, period start and stop spaces are provided. Ifused to indicate a series of years, only the "Start" blankis used. If a given Period represents a decade, then"Start" should indicate the first discrete Fiscal Yearand "End" the final inclusive one.

2) Probability indicates a judgmental assessment, by Period,of the possibility that a given SA will come to pass. Sincesome SA planning horizons project far into the future andare primarily documented for future assessment, an "Indeter-minate" evaluation, in addition to the normal "No" to "Hi"range is provided.

d. Input ID identifies other SA ID numbers impacting a givenassumption. A degree ("O") column is provided for anassessment of impact intensity using the same scale as usedfor SA "Probability" definition.

e. Output ID identifies those SA numbers impacted by a givenassumption.

f. Sources defines the "authority" for a given SA. Authority mayrarsjifrom an individual's judgmental opinion to referencesfrom such documents as the Navy Strategic Study (NSS), JointStrategic Objective Plan (JSOP), Joint Research and DevelopmentObjectives Document (JRDOD), etc. The assumption may not be adirect quote of the source but an interpretive exercise basedon an individual or combination of sources.

This section also constitutes the bibliography for a given SAto direct reviewers to more detailed material than can be pro-vided under the "Assumption Statement" section.

2. Procedural - In developing the Phase I Strategic Assumptions, thefollowing procedure was followed:

a. Preliminary assumptions were defined based on DOTS Phase I inter-view data, a variety of strategic papers, IBM Advisory Groupcontributions, and other pertinent sources of predictive infor-mation.

b. Preliminary assumptions were assessed for pertinence to theNaval Education Training System and those with significantimpact identified.

c. Based on existing or anticipated relationships, a strategic"structure" was developed.

A-I-5


d. Based on the probability projections of the individual SA's, aset of working assumptions was synthesized to form a base fordevelopment of the idealized NETS model of the 1980's.

Although specifically developed to provide a base for synthesizingPhase I working assumptions, this set of Strategic Assumptions hasapplication beyond the DOTS project. Therefore, the workingassumptions are documented in the Phase I report body with the SA'sbeing contained in Section II as a possible "stand-alone" addendum.

3. General Comments - The SA's to follow in Section II represent a"thesis" approach to the strategic process. A group of assumptionshas been formulated and assembled within a short time to form adiscrete document to provide one "driver" in the development of anidealized 1980 NETS model. In short, this is a "snap-shot" approachto defining the NETS environment at some strategic point in thefuture. However, it should be borne in mind that these SA's arebased on a continuously evolving data base.

As has been previously indicated, a viable strategic process mustbe able to consider an ever changing data base and to produce up-dated SA structures that provide practical guidance to the operational,tactical, and strategic planning levels. Therefore, this specific setof Strategic Assumptions should be considered a start and not an endto the strategic process.

A-I-6


NETS NAVAL EDUCATION TRAINING SYSTEM

Strategic Assumptions

FIELD: a-1

ITEM:CATEGOPv: a-2

a-3 . DATE: a_4 NO: a-5

ASSUMPTION STATEMENT:

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- No I - Lo 2 - Med 3 - Hi 4 - IndeterminateFigure 1

A-I-7


I. STRATEGIC ASSUMPTIONS AND STRUCTURE

A. DESCRIPTION

1. SA Index - Every SA Field, Category and Item is assigned a numberwith an SA planning sheet developed for each number. The Fielddesignating revision number is not included in the index. TheIndex is a listing of all SA numbers and associated titles.

2. SA Charts - These charts constitute the data base of the strategicprocess. Each SA Item Chart represents a fundamental assumption.

3. SA Structure - The SA Structure is the result of defining the SA'sand the relationships between SA's. It is a graphic presentationof the Input/Output relationships between individual SA's leadingto the Strategic Working Assumptions (SWA) providing the base forthe Phase I Report, Section VI, on tactical assumptions and recom-mendations. An SA network is provided for each SWA.

B. STRATEGIC ASSUMPTION INDEX

01.XXX.XXX

01.001.XXX

Demography

Education

H. S. Graduates 01.001.001College Graduates 01.001.002

Philosophical 02.XXX.XXX

Religion 02.001.XXX

Moral Values 02.001.001

Institutional 02.002.XXX

Authority 02.002.001

Bio-Medical 03.XXX.XXX

Treatment 03.001.XXX

Injuries 03.001.001

A-II-1


Biological Control 03.002.XXX

Maturity 03.002.001Life Expectancy 03.002.002Behavior Modification 03.002.003

Social/Culture

Attitudes

04.XXX.XXX

04.001.XXX

Work Experience 04.001.001Job Satisfaction 04.001.002Effect of Change 04.001.003

Careers 04.002,XXX

Military 04.002.001

Work Schedule 04.003.XXX

Impact on Training 04.003.001

Human Resources 04.004.XXX

Organization 04.004.001Urbanization 04.004.002

Communications 05.XXX.XXX

Devices 05.001.XXX

Interactive Terminals 05.001.001

Satellites 05.002.XXX

Military 05.002.001

Education 06.XXX.XXX

Student Skills 06.001.XXX

Learning Skills 06.001.001Reading Ability 06.001.002Entering Competency 06.001.003

A-II-2


Technological Change 06.002.XXX

Impact on Content 06.002.001Key Individuals 06.002.002Training Mode 06.002.003

Educational Technology 06.003.XXX

Task Modularization 06.003.001Task Optimization 06.003.002Modular Programs 06.003.003

Post Education/Training 06.004.XXX

Graduate Performance 06.004.001

Simulators 06.005.XXX

Feasibility 06.005.001

Administration 06.006.XXX

Automation 06.006.001Advanced Weapons Potential 06.006.002

Measurement 06.007.XXX

Certification 06.007.001

Motivation 06.008.XXX

Student 06.008.001

International 20.XXX.XXX

Joint Efforts 20.001.XXX

Regional Powers 20.001.001

Military Environment 20.002.XXX

Multipolar 20.002.001Law of the Sea 20.002.002Small Navies 20.002.003

Geopolitical 20.003.XXX

Importance of Sea 20.003.001Technology 20.003.002


Resources 20.004.XXX

Basic Necessities 20.004.001

National 21.XXX.XXX

Domestic Institutions 22.XXX.XXX

EconoMY 22.001.XXX

Worker Skill 22.001.001

Education 22.002.XXX

Value of Degree 22.002.001

Technological 30.XXX.XXX

Education/Training 30.001.XXX

Skill Transferability 30.001.001

Task Reduction 30.002.XXX

Devices 30.002.001Reliability 30.002.002

Personnel 30.003.XXX

Competence 30.003.001

Weapons 30.004.XXX

Interchangeability 30.004.001Satellite Neutralization 30.004.002

Automation 30.005.XXX

Computer Capability 30.005.001Weapons Systems 30.005.002

Military Platforms 30.006.XXX

Air Cushion Vehicles 30.006.001

A-I1-4


Military Doctrine

Mission

40.XXX.XXX

40.001.XXX

Political 40.001.001Tactical Air Projection 40.001.002Amphibious Projection 40.001.003Presence Forces 40.001.004Sea Control 40.001.005

National Policy 40.002.XXX

Defense 40.002.001Nixon Doctrine 40.002.002

Armaments 40.003.XXX

Level 40.003.001Strategic Deterrence 40.003.002Second Strike 40.003.003Submarine Launched Ballistic Missile (SLBM) 40.003.004Capital Presence Ship 40.003.005Satellite Impact 40.003.006

Naval Factors

Organizational

60.XXX.XXX

60.001.XXX

Mission Orientation 60.001.001Training Centralization 60.001.002

Research and Development 60.002.XXX

Educational R&D 60.002.001Student Motivation 60.002.002

Education 60.003.XXX

Civilian Contractors 60.003.001Multi-service Use 60.003.002Variable Loads 60.003.003Graduate Study 60.003.004

Personnel 60.004.XXX

Job Commonalty 60.004.001Enlistee Attitudes 60.004.002Pilot Proficiency 60.004.003Parental Authority 60.004.004Women 60.004.005


Civil/Military Postulates 60.005.XXX

Postulate #1 60.005.001Postulate #2 60.005.002Postulate #3 60.005.003

C. STRATEGIC ASSUMPTION CHARTS

The charts to follow represent the highest level of strategic definitionwithin the report. Generally, the Strategic Assumptions (SA) wereselected for their pertinence to the Naval Education Training System(NETS). However, a number of others were included to illustrate thepotential scope of the recommended Strategic Process.

The SA charts are followed by a series of SA Structure Charts establish-ing a network of SA relationships pertinent to the next lower level ofstrategic definition forming the basis of the Phase I Report, Section VI,tactical assumptions and recommendations. This lower level of assumptionis called a Strategic Working Assumption (SWA).

A-II-6




FIELD: Demography CATEGORY: EducationITEM: High School Graduates DATE: Sep 73 NO: 01.001.001.00

ASSUMPTION STATEMENT:High school graduates as a percent of persons 18 years old are projectelas follows:

1970 (Actual)- 76.5 (Actual)1975 - 83.91980 - 89.5

Historical - High school graduates as a percent of persons 17 yearsold:

1950 - 59.0%1960 - 65.1%1965 - 72.4%1969 - 78.4%

INPUT Id). PERIODS OUTPUT LTAI. 02.002.001 _ 1 la.114c cl o f h i i k 1 mn 0 01.001.002

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SOURCES:1. U.S. Dept. of Commerce, Bureau of the Census, Statistical Abstract

of the U.S., 1971, Washington, D.C., 1971, p. 1747

. Reviewed by IBM Advisory Group; 18 Sept. 1973

- No I - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-7




FIELD: DemographyITEM: College Graduates

CATEGORY: EducationDATE: Sep 73 NO: 01.001.002.00 I

ASSUMPTION STATEMENT:College graduates as a percent of persons 21 years old are projected asifollows:

1960 - 18% (Actual)1980 - 48%1990 - 54%2000 - 54%

The tapering off assumes that an IQ of at least 100 is needed to com-plete college. This point was derived from the high school senior meanI.Q. of 107 and the assumption that a higher IQ is necessary to doacceptable work at a good college.

(Source 1 & 2)

Note: Some of the trends apparent in 1973 tend to indicate that theabove projection is too high. It should remain an assumptionpending trend validation.

(Source 3)

I ' D PER *DS OUTPUT I.Di02.002.001

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SOURCES:1. Hilgard, Ernest R., Introduction to Psychology, Harcourt, Brace and

Company, New York, 1953, p. 399.2. Wehle, Mark and Rockett, Laurie, "Notes on World-Wide School Enroll.

went and Illiteracy and U.S. Graduates of the Year 2000",Workin Pa er A endix to the Next Thirty Years: A Context forSpecu son Institute, Dec. 1966, A 9-31.

. Aas N. an0 Bow C.R. S Strategic Seminar, IBM

0 No I - Hi 4 - Indeterminate

A-II-8




FIELD:PhilosophicalITEM: Moral Values

CATEGORY: Religion

DATE :Sep 73 NO: 02.001.001.00

ASSUMPTION STATEMENT:Although it can be assumed that a number of trends apparent in currentsociety will result in a decline of organized religion, it is doubtfulthat most basic moral and ethical concepts will decline greatly ineffectiveness. However, all social institutions will be forced to dosearching self-examinations pertinent to projected value changes.

Ethics, morals, and religion have been affected by contemporary socialchange. Traditional morality has come under attack on ethical andbiological-psychological grounds. Established Judeo-Christian conceptsof individualism, freedom of choice, and free will are challenged bymodern philosophers and psychologists on the grounds that the need forcooperation, the reality of interdependence, and the truism of en-vironmental conditioning have rendered the former ideals obsolete andinapplicable to current problems.

INPUT I.D. 1 PERIODS OUTPUT LI)03.002.001 a b c d g f h i i I k I nln o. 02.002.001

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_60,002,002 _

60.004.002--60.004-..004

Prot 2,2 4 4

SOURCES:1. Wermuth, Dr. Anthony L., Potential Impact of Cultural Change on the

Navy in the 1970's, Westinghouse, Falls Church, Va., August 1972,V6)-1, ?87,707---

0 - No 1 - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-9

TAEG REPORT NO, 12-1



FIELD: Philosophical CATEGORY: InstitutionsITEM: Authority DATE :Sep 73 NO: 02.002.001.00

ASSUMPTION STATEMENT:It can he assumed that those institutions within our society which are'authority oriented will be adversely affected by the declininglegitimacy of authority in American society and by society's prospec-tive declining interest in socializing its youth into at least someacceptance of the need for authority in a balanced relationship ofrights and obligations.

This will have an especially strong effect on the military since socialf

change will be conceding greater freedom to the individual in someareas, while promising to restrict it further in others.

be, o ER DS OUTPUT I.Dis is b c e u. h i o 01.001.001

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.44c.h-,0)r CO

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_06,001.00360.004.002

33

60.004.004 3 Prot -1 2 4 4 4

SOURCES:1. Wermuth, Dr. Anthony L.,

the Navy in the 1970's,Potential Impacts of Cultural Change on

Westinghouse, Falls Church, Va., August1972, Vol-I, 30.

0 - No 1 - Lo 2 - Med 3 - Hi Indeterminate

A-II-10


NETS NAVAL. EDUCATION TRAINING SYSTEM


FIELD: Bio-MedicalITEM: Injuries

CATEGORY: TreatmentDATE: Sep 73 NO: 03.001.001.00

ASSUMPTION STATEMENT:It can be assumed that major breakthroughs will continue in the fieldof medical engineering especially in the areas of antibiotics, thetransplantation of organs, possibly the regeneration of organs, andthe use of man-made machines to perform the functions of certainorgans.

The treatment of injuries resulting from accidents or battle willbenefit most from these projected advances. Procedures developed insuch fields as artificial organs, organ transplants, and prostheticswill aid in rehabilitation of those who suffer from accident orbattle-related injuries. Any medical techniques that provide swifter,more effective care, resulting in the recovery of higher proportionsof wounded men, particularly those suffering permanent effects, willbe welcomed by the military.

....1.....=

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o PERIODS OUTPUT I.D

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1

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Prot! 3 3,3 31 3

SOURCES:1. Wertnuth, Dr. Anthony L., Potential Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August1972-, Vol-I 45

- No - Med 3 - Hi 4 - Indeterminate

A-II-11




FIELD: Bio-Medical

ITEM: MaturityCATEGORY: Biological Control

DATE :Sep 73 NO: 03.002.001.00

ASSUMPTION STATEMENT:It can be assumed that significant breakthroughs in bio-medicine willdecrease the length of time required for an individual to reachphysical and mental matuHty. This could happen within the nexttwenty years.

If this decrease is significant, it would have radical implications formost social institutions, especially the military. It is anticipatedthat the availability of persons, young in chronological age, butmature in terms of capability could generate a number of status andprocedural changes in military organizations.

14, ' I.11

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41

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01

_g/, :_ IIIII. .004, 0_04_Prot 1 1 . 3.3

SOURCES:1. Wermuth, Or. Anthony L., Potential impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., Wugust1972, Vol -I, 46.

No - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-12


NAVAL EDUCATION TRAINING SYSTEM


FIELD: Bio-Medical

ITEM: Life Expectancy

CATEGORY: Biological ControlDATE: Sep 73 NO: 03.002.002.00

ASSUMPTION STATEMENT:It can be assumed that there will be significant extension of pro-ductive life-spans within the next twenty years resulting from R&Din medical engineering.

This change has many implications for existing institutions. If theburden of extended retirement costs is not to become prohibitive,institutions will have to plan extension of their personnel's activeworking years.

The delays imposed on the generation behind the first generation toachieve substantial life extension will result in significant dis-ruptions to society and its institutions unless remedial programs areimplemented.

l ' o PERIODS OUTPUT I. Do so is

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,Prot 1 1 2. 3 3', ......_.,

SOURCES:1. Wermuth, Dr. Anthony L., Potential Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August197, Vol-I, 47.

-N - Med 3 - Hi 4 - Indeterminate

A-I1-13




Bio-Medical

ITEM: Behavior ModificationCATEGORY: Biological ControlDATE:Sep 73 NO: 03.002.003.00

+NI

ASSUMPTION STATEMENT:It can be assumed that, within the next twenty to thirty years, majorbreakthroughs will occur in modification of, an individual's behaviorand characteristics through bio-medical or psychological means.

Society and its institutions will use behavior-manipulative techniquesor drugs to relieve suffering, to cause desired behavior, or,possibly, to improve such areas as learning characteristics.

Although the breeding and conditioning of a group of people forspecific objectives is not a new practice, the 'breakthroughs'referred to will greatly facilitate the process.

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.Prot 1 1 2 2 3 t- - - --

SOURCES:1. Wermuth, Or. Anthony L., Potential Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August19/2, Vol-I, 47

- No Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-14




FIELD: Social/Cultural CATEGORY: AttitudesITEM: Work Experience

4111111ErDATE: Sep 73 No: 04.001.001.00

ASSUMPTION STATEMENT: It is assumed that many new entries to 1the national work force and wilitary services during the strategic timespan will lack any work experience in organizational settings wheresuch factors as deadlines, schedules, teamwork, sustained productivity,and work standardization may be relatively unknown and perhaps un-appreciated.

This will require not only the learning of work habits, but morefundamental awareness dnd appreciation of work roles and the attitudinaaspects of shared work environments. These attitudes and habits are nolikely to be acquired under coercive conditions. They will constitutean increasingly severe demand on institutional training with an in-creasing proportion of people who have rejected the so-called "Protes-tant work ethic" without having experienced it.

(Source 1)

A counter assumption of the above states that the trend indicated willshortly level out or decline. Also, there is a question of to whatdegree the "Protestant work ethic" has been rejected.

(Source 2)

Ilk 6 PERIODS OUTPUT I.02 _0. li IN

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SOURCES:1. Miller, Robert B., File Memo - Summary of Trends in Navy Trainini,

IBM Advisory Group, 27 March 73, Section 1.3.2. Adams, Dr. E. N., and Bowen, C. R., NETS Strategic Seminar,

IBM Advisory Group Meeting, 18 Sept. 73.3. Reviewed by IBM Advisory Group 18 Sept. 73,

- No 1 - Lo 2 - NI(A 3 - Ui 4 - Indeterminate




FIELD: Social /Cultural CATEGORY: AttitudesITEM: Job Satisfaction DATE :Sep 73 NO: 04.001.002.00

ASSUMPTION STATEMENT:Due to an increasing emphasis on "job satisfaction" in industry and tothe projected changes in many industrial and military job tasks, it canbe assumed that the armed services will be required to structure jobsfor satisfaction to overcome worker's need for interesting, fulfillingwork.

Many companies are experimenting with "uork teams" in which the overallobjective is set for the group but the individual responsibilities aredecided by the group. Concepts of vertical job loading to give theworker increased responsibility have also proven valuable. From atraining standpuint, if the principles of transfer and generalizationare to be taken into account, the training situation must be made toapproximate the performance environment. This will dictate that suchthings as work teams and the like be built into the training environment.

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.400ci,

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_0.003.00460.004.002__ ..

60.004,003_

Pro. 2 3 3______

SOURCES:1. Schwartz, H. A.: File Memo - Volunteers, IBM Advisory Group,

28 June 73, P-1, Sec 2.

. Reviewed by IBM Advisory Group 18 September 73.

- No 1 - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-I1-16


A NETS NAVAL EDUCATION TRAINING SYSTEM


FIELD: Social/Cultural

ITEM: Effect of ChangeCATEGORY: AttitudesDATE: Sep 73No: 04.001.003.00

ASSUMPTION STATEMENT:It can be assumed that the rate of change within our society willcontinue to accelerate and, whether technological or philosophical,will have a profound influence on the thoughts and attitudes of ourpopulation.

Due to its acceleration and pervasiveness, the sense of uncertaintyand intermittent confusion it generates, and the growing suspicion itfosters that there are no permanent answers, changes continue to bedisruptive to men and institutions, unless men develop a sixth senseof continual awareness, or readiness, toward change.

l ' 0 PERIDS -----"OUTPUT I. DI 60 II WM

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Prot DuoSOURCES:1. Wermuth, Dr. Anthony L., Potential Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August1972, Vol-I, 6.


A-II-17




FIELD: Social/CulturalITEM: Mi 1 i tary

CATEGORY: CareersDATE: Sep 73 No: 04.002.001,00

ASSUMPTION STATEMENT:Assuming a peacetime military environment, it can also be assumed thatthe military will offer many individuals a more orderly structure inwhich to cultivate and realize a meaningful life style than they will bable to find in their civilian lives. Formal military training maycombine both technical and non-technical content directed towards thesepersonal realizations resulting in a more effective person in themilitary and civilian environment.

These considerations will affect costs in time and facilities, in-structional style and technique, and will probably result in an in-creased concern by the military for psychologically sensible patternsof career progression, based on achievement of performance criteriarather than simple possession of "credentials," and greater flexibilityin technical assignments.

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SOURCES:1. Miller, Robert B.: File Memo Summary of Trends in Navy Training,

IBM Advisory Group, 27 March 73, Section 1.5

. Reviewed by IBM Advisory Group, 18 September 1973


A-II-18




FIELD: Social/Cultural CATEGORY: Work ScheduleITEM: Impact on Training DATE:Sep 73 NO: 04.003.001.00

ASSUMPTION STATEMENT:It can be assumed that the trend towards the four (or three) day workweek gaining acceptance in the industrial sector will continue, and;ultimately impact the military.

Implications of such shortened work weeks will have to be taken intoaccount in both training and operational aspects of armed forcespersonnel. From the standpoint of economics, the shortened work weekmay require a larger work force which in turn would require greater output from the training function. The training function itself may heforced into experimentation with different schedules in order toincorporate these altered work weeks into its programs.

(Source 1)

A counter-assumption states that, although there will be a shift to aflexible work schedule, there will be no significant reduction inoverall work hours.

(Source 2)

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SOURCES:1. Schwartz, H. A.: File Memo - Volunteers, IBM Advisory Group, 28

June 73, P-1, Sec 1.2. Bowen, C. R., NETS Strategic Seminar, IBM Advisory Group, 18 Sept.

73.

3. Reviewed by IBM Advisory Group, 18 September 1973.

- No - Med 3 - Hi 4 - Indeterminate

A-II-19


N ET S NAVAL EDUCATION TRAINING SYSTEM


FIELD: Social /CulturalITEM: Organization

CATEGORY: Human ResourcesDATE: Sep 73NO: 04.004,001.00 .1.

ASSUMPTION STATEMENT:Based on current trends in the organization of workers in the publicsector such as teachers, police, firemen, etc., it can be assumedthat the organization of armed forces personnel into quasi uniongroupings will probably occur during the next two decades.

This will bring elements of the collective bargaining process to thearmed forces. Training may be based on seniority as will promotions.The rapid changes in job structures and tasks predicted for thefuture may be impacted due to the restrictions of personnelorganization.

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Prot UN inniMinSOURCES:1. Schwartz, Or. H. A., NETS Strategic Seminar, IBM Advisory Group,

18 September 19732. Reviewed by IBM Advisory Group, 18 September 1973

-N -L - Med 3 - Hi 4 - Indeterminate116

A-I1-20


NETS NAVAL EDUCATIONEDUCATION TRAINING SYSTEM

FEELD:Social/Cu, aural

ITEM: Urbanization


CATEGORY: Human ResourcesDATE:Sep 73 NO: 04.004.002.00

ASSUMPTION STATEMENT:By 1995, 90% of all Americans will live in urban areas. The suburbswill absorb most of this increase as the inner-city declines due toracial, economic, and housing problems. Decentralized suburbia may beprototypical for the cities of the future, with communication replacingphysical presence as the dominant mode of idea exchange.

The institutions of society will be impacted by the need to modifytraining and personnel procedures to adjust to the decline of farmbred youth and the predominance of city-bred youth.

h. , o . PERI DS OUTPUT I.D, MX ... I 1 1 0 so 11

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SOURCES:Wermuth, Or. Anthony L., Potential Im acts of Cultural Chan e onthe Nay in the 1970's, Westinghouse, Fal s Church, Va., August19Y2 , Vol - I , 53.

- No 1 Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-21

11ErtTAEG REPORT NO. 12-1



FIELD: Communication CATEGORY: DevicesITEM: Interactive Terminals DATE:Sep 73 No: 05.001.001,00

ASSUMPTION STATEMENT:Indications are that by the year 2000, the U.S. society will besaturated by information devices. These will differ from currentdevices primarily in the increased degree of "interaction" betweenterminals. Children will mature in a society saturated with informa-tion and sophisticated networks for dissemination of information.

For the most part, these will be telecommunications terminals and willinclude graphic capability. There are conservative predictions we willsee ten million computer terminals by 1985. It is safe to assume thatby 2000 A.D., truly interactive audio-visual terminals will be avail-able in every home.

This has profound implications for society and especially for that partof education dealing with information.

(Source 1 & 2)The existence of these devices does not guarantee that most childrenwill be strongly shaped by them. The degree of impact will bedetermined by how they are used, not by how many there are.

(Source 3)

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SOURCES:1. Bowen, t.R., IBM Advisory Group, 18 September 19732. Miller, Robert B.: File Memo - Summar of Trends in Navy Trainin

IBM Advisory Group, 27 March 7 Section '.53. Adams, Dr. E. N.: NETS Strategic Seminar, IBM Advisory Group

Meeting, 18 September 1973. Reviewed by IBM Advisory Group, 18 Sep 73.

No 1 - L - Med 3 - Hi

A-II-22

- Indeterminate




FIELD: Communications

ITEM: Military

CATEGORY: Satellites 1

DATE:Sep 73 NO: 05.002.001.00

ASSUMPTION STATEMENT:It can be assumed that by 1980, military communications will berelayed by a multi-satellite, Department of Defense dedicated system,In the system of the 1980's, the present uses will become much moresophisticated. Those with military implications are weather assess-ment and prediction, navigational aid (very essential to U.S. nucleardeterrent forces), and a broad range of force detection uses.

One major satellite communication advance will be the technological andlogistical advances required for real-time capability. Present problemsof P.F. interference and relay capability will be overcome by the early1930's.

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SOURCES:1. Comoifteo p25, 'Irpact of a Satellite Environment on Naval

°per:firms," Naval Mission Area Paper, the U.S. Navel War College,Newport, P.I. , 19/3, 2, 3, &

- -Ng I - IA) 2 - Med 3 - Ili 4 - Indeterminate

A-I1-23



FIELD: EducationITEM: Learning Skills

CATEGORY: Student SkillsDATE: Sep 73 NO: 06.001.001.00

ASSUMPTION STATEMENT:Based on current educational trends, the product of the public educa-tion system of the 1980's and beyond will be characterized by a lack ofdiscipline and skills in the training-learning process.

It is assumed that this reduced formal background in skill acquisitionmust be compensated for by psychologically sound procedures for engag-ing and holding attention, and for inspiring suitable aspirations forachievement at the level of task learning.

There is some evidence that there will be a reversal of this trend inthe public sector. However, even if this does take place, the changewill be gradual and, as a strategic concern, lack of learning skillswill remain at least through the 1980's.

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SOURCES:1. Miller-, Robert 8.: File Memo - Summary of Trends in Navy Training,




A-I1-24




FIELD: EducationITEM: Reading Abi I i ty

CATEGORY: Stude.nt SkillsDATE: Sep 73N0: 06.001.002.00

ASSUMPTION STATEMENT:It is assumed that there will be a continuing deterioration in the read,ing and communication skills of the public education graduate. Thesedeficiencies are generally attributable to failure of instruction inprimary and secondary school s to overcome home inadequacies.

This factor becomes a strategic concern for projected military andindustrial training systems if it is assumed that future individualizedapproaches will require significant skills in both reading andcommunicating.These deficiencies will have to be remedied with much greater effi-ciency than attained in public schools.

(Source 1)I t can be assumed that there will be an increase in non-verbal trainingaids oriented to performance rather than verbal capability. There willalso be an increase in Job Performance Aids (JPA' s ) al so oriented toperformance which will result in a reduction of formal and verbaltraining requirements.

(Source 2)

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SOURCES:1. Miller, Robert B.: File Memo L- Summary of Trends in Navy Training,


2. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group.0,c,etinp, 18 Sept. 1973


U - No 1 - Lo 2 - Med 3 - Hi 4 - Indeterminate

Ti 25

INd

1AEG REPORT NO. 12-1

N E S NAVAL EDUCATION TRAINING SYSTEM

Strzttegic Assumptions

FIELD: EducationITEM: Entering Competency

CATEGORY: Student SkillsDATE: Sep 73NO: 06.001.003.00

ASSUMPTION STATEMENT:I t can be assumed that, due to the AVF concept, the military will haveto recruit the men they need in the labor market in the same manner asprivate firms and that this exposure to the "free market" may resultin the following change:"For years the military has drafted and recruited young men with fewskills and little experience. It then trained these men to providethe services it required. A possibility that arises with the zerodraft is that the military may decide to hire more experiencedindividuals in order to reduce training costs."

(Source 2)

An argument in opposition to the above is that the military pay scalewill not permit competition with the "free market" for highly skilledpeople.

(Source 3)

1 PERIODS OUTPUT I. D01 . uol.no si

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IIII Prole 2 2 WWII 1111 IIIIIIISOURCES:1. Schwartz, H. A.: File Memo - Volunteers, IBM Advisory Group, 28

June 73, P-22. Moskow, M. M,: "The Zero Draft and the Labor Market" The Con-

ference Board Record, September 19723. AdaTs, Dr. E. N.: NETS Strategic Seminar, IBM Advisory Group

Meeting, 18 September 19734. Reviewed by IBM Advisory Group, 18 September 1973

0 - No I - Lo 2 - Med 3 - Hi 4 - IndeterminateA-1I- 26

111


Ak y. NETS NAVAL EDUCATION TRAINING SYSTEM


FIELD: EducationITEM: Impact on Content

CATEGORY: Technological Change {

DATE: Sep 73N0: 06.002.001.00

ASSUMPTION STATEMENT:It is assumed that rapid and frequent technological changes in bothindustrial and military hardware will have little influence on thespecific task content of most activities. The trend will be towardstraining for "general skills" easily transferred from one device orsystem to another without additional training. The majority of peoplewill receive a broad general base of skills rather than the "in-depth"training of the past. The change will, therefore, be one of breadthand degree rather than specific content.

This assumption is not intended to preclude training of the in-depthspecialist.

AIINamima

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______ _____,Pro IntinfiMIEMER IN

_______ __

SOURCES:1. Miller, Robert B.: File Memo - Summary of Trends in Navy Training,

IBM Advisory Group, 27 March 73,' Section 2.2

. Reviewed by IBM Advisory Group, 18 September 1973

- No 1 - Lo Med 3 - Hi 4 - Indeterminate

A-II-27




FIELD: EducationITEM: Key Individuals

CATEGORY: Technological ChangeDATE: Sep 73 NO: 06.002.002.00

ASSUMPTION STATEMENT:Although in-depth training will decrease, a number of factors inherentin rapid technological change will tend to emphasize the importance ofkey individuals within an organization. This will result from thediversity of level and relevance of the training of many "on-site"personnel, rapid technological changes that will be incompletelydocumented or transmitted; mismatches between tools, procedures,environments, support facilities --, these and other factors will tendto demand at least one or a few individuals with a high degree ofexpertise in taking initiative, working without direct documentation orexperience on the problem and in other ways able to improvise answerswhich will keep the organization running. These key people will havethe capability to diagnose (troubleshoot) under a wide variety ofconditions and to improvise solutions.

i T P o PERIODS s OUTPUT I. I)14 1 11 INIMMIMIUMMIMMISIUMILIno 16.11 /1

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SOURCES:1. Miller, Robert 8.: File Memo - Summary of Trends in Navy Training,


2. Reviewed by IBM Advisory Group, 18 September 1973

0 - No 1 - Lo 2 - Med 3 - Iii 4 - Indeterminate

ii -II-28




FIELD: EducationITEM: Training Mode

CATEGORY: Technological ChangeDATE: Sep 73 NO: 06.002.003.00

ASSUMPTION STATEMENT:Although the number and depth of procedural skills required of theoperator of future industrial and military systems will decrease, theincreasing degrees of interdependence of system functions in moderntechnologies mean that human operators will learn orocedures that mustbe adapted to wider ranges of contingencies. Furthermore, the lia-bilities of various kinds of failure of equipment, and/or personnel,tend to increase the need for the operator to be able to take overwhen things normally planned for automatic or machine performance musthave a manual intervention. Training to cope with a multitude ofcontingencies will be impractical. However, the use of interactive on-

1

site devices will reduce the amount and depth of training required.

(Source 1)

These J.P.A. (Job Performance Aid) devices will also reduce the levelof individual required to maintain and operate equipment.

(Source 2)

A counter-assumption to the above states that the takeover of increas-ingly complex systems by the operator will become difficult if notimpossible. (Source 3)

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Pro iimminom munimmiSOURCES:1. Miller, Robert 8.: File Memo - Summary of Trends in Navy Training,

IBM Advisory Group, 27 March 73, Section 2.42. Fox, Raymond G.: NETS Strategic Seminar, IBM'Advisory Group, 18

September 733. Adams, Dr. E. N.: NETS Strategic Seminar, IBM Advisory Group,

18 September 734. Reviewed by IBM Advisory Group 18 September 1973.

0 - No 1 Lo 2 - Med 3 - Iii 4 - Indeterminate

A-II-29


/../MMINIIr



FIELD: Education CATEGORY: Educational TechnologyDATE:Sep 73 NO: 06.003.001.00ITEM: Task Modularization

ASSUMPTION STATEMENT:Based on recent advances, it can be assumed that by the mid-1980's,fochniques will have been developed that will permit efficient andeffective task/skill definition and subseouent modularization of tasks.There will be generally acceptable criteria for subdividing a total jobinto segments of activity (or task clusters) that hang togetherpsychologically.

A given cluster can be learned as a group, applied to the job as anentity, and used as a basis for estimating the range of variation injob situations to which the trained operator is likely to adapt with "x"amount of time for retraining or adjustment on the job.

An important indirect outcome of suitable task modularities is theability to create data bases with an effective semantic (naming)discipline. These data bases will assist in making efficient changesto a training system. (Source 1)

These task modularities will enable training managers to manage trainingin relationship to specific job tasks and task profiles.

(Source 2)

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SOURCES:1. Miller, Robert 8.: File Memo - Summary of Trends in Navy Training,

13M Advisory Group, 27 March 73, Section 3.1.2. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group

Meeting, 18 September 73.. 122viewed by IBM Advisory Group, 18 September 1973

U - No 1 - Lo 2 - Med 3 - Hi 4 - Indeterminate


N E S NAVAL EDUCATION TRAINING SYSTEM


FIELD: EducationITEM: Task Optimization

CATEGORY: Educational Technology

DATE:SeP 73 NO: 06.003.002.00

ASSUMPTION STATEMENT:It is assumed that a major trend that stresses optimization of trainingthrough a more sophisticated task analysis process will continue togain momentum. In the last twenty years, there has been an evolutionfrom the training policy of "teach them what is nice for them to know"to that of "teach them what they will have to do." In part, this hascome about because better ways of describing the performance require-ments of jobs have been adopted and become widespread. Another develop-ment will be better means of translating performance requirements intopsychological and behavioral models of the learning and performingprocess so that the "natural" capabilities of the student can be bettercapitalized, and his s 1 imi ts and liabilities compensated.

(Source 1)

Task analysis will relate to deferred training modules to facilitate thecorrelation of tasks with instructional delivery and management. Jobneeds/description wi 11 be cross-referenced to task requirements andinstructional module cognitive content.

(Source 2)

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SOURCES:1. Miller, Robert B.: file Memo - Summary of Trends in Navy Train- ng

!7!1 Advisory Group, 27 March i3, Section 3,6.2. Fox, Raymond G.: NETS Strategic Seminar, IBM Adviwry Group

Meeting, 18 September 19733. Reviewed by IBM PAivisory Group, 18 September 1973

- No 1 - Lo 2 - Med 3 - Indeterminate

A-II-31


N E ri: S NAVAL EDUCATION TRAINING SYSTEM

FIELD: Education.

ITEM: Modular Programs DATE: Sep 73NO: 06.003.003.00


CATEGORY: Educational Technology

ASSUMPTION STATEMENT:It is assumed that by the mid-1980's the techniques of developingpsychologically valid "modules of training" will have advanced to adegree that will permit the majority of training programs to be basedstrictly on modules. Discrete "courses," as we knorr them today, willcease to exist.

Each training module will logically and clearly interface with othersof any pertinent sequence. The student's progression, therefore,Capitalizes on what he has learned in previous modules. At the end ofa given module, the trainee may branch to any one of several othermodules; but in each case, the content of the previous module is a

relevant and necessary stepping-stone to the next. Training modulari-ties not only enable the economic benefits of scale, they also fosterthe focus of improvements in the state of the instructional art withinwell-defined sub-objectives in training curricula.

(Source 1)

Since modules will be precisely defined, it will be possible to teststudents and to construct individual performance profiles by module.This profile can be related to specific job requirements. (Sourcg, 2)

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SOURCES:1. Miller, Robert B.: File Memo - Summary of Trends in Nayy Training,

IL)M Advisory Group, 27 March 73, Section 3.72. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group, 18

September 19733. Reviewed by IBM Advisory Group, 18 September 1973

-No 1 -Lo 2 - Med 3 -Hi - Indeterminate

A-II-32

I\TETS NAVAL EDUCATION TRAINING SYSTEM


FIELD: Education CATEGORY: Post Education/TraininITEM: Graduate Performance DATE: Sep 73 NO: 06.004.001.00

ASSUMPTION STATEMENT:It is assumed that by the mid-1980's, the modeling and concepts requiredto predict student post-training performance will have been developed tca level permitting practical inclusion in education management systems.

Recent models under development by the information and behavioral systerrtheorists, and by contemporary investigations into the cognitive opera-tions underlying linguistic processes, are revealing some models havingpromise. When these models are translated into instructional techniqueand into suitable task analytic statements, training may genuinely pro-vide the psychological "fundamentals" for the transfer of training fromvery specific contexts to more general ones such as may underlie a job,family or a career structure.

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Prot 1 2 2 34' 31

SOURCES:1. Miller, Robert B.: File Memo - Summary_ of Trends in Navy Training,

IBM Advisory Group, 27 March 1973, Section 3.22. Reviewed by IBM Advisory Group, 18 September 1973


A-11-33




[-FIELD: Education

ITEM: FeasibilityCATEGORY: Simulators

DATE: Sep 73 NO: 06.005.001.00

ASSUMPTION STATEMENT:It is assumed that by the mid-1980's a significant portion of current"hard" lab training will be administered in both the industrial andmilitary training environments, through second level simulation. In

the past, the high costs of computer hardware, programming and ofterminals made the use of computer systems impractical as a vehicle toadminister simulation exercises except for limited numbers of highlycritical tasks where the cost of using the actual device more than off-set the cost of a computer system. Dramatic reductions in hardwarecosts and large simplifications in application programming will make thuse of computers for simulation practical for even fairly low leveljobs. This is particularly true if educational practice recognizes thaabsolute fidelity in representing the real-world is unnecessary, andthat large variations from the total task environment may, for sometraining objectives, be adequate, and in fact preferable.

(Source 1)

In addition to simulation capability, computer technology will havereached a point where "stand alone" interactive devices will permitthe administration of training modules on-site. The increasedcapability will permit individualization. (Source 2)

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SOURCES:1. Miller, Robert B.: File Memo - Summary of Trends in Navy, Training,

13M Advisory Group, 27 March 73, Section 3.32. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group, 18

Septenter 19733. Reviewed by I3M Advisory Group, 18 September 1973


A-II-34


NETS NAVAL EDUCATION 1'RAINING SYSTEM


FIELD: Education

ITEM: AutomationCATEGORY: AdministrationDATE:Sep 73 NO: 06.006.001.00

ASSUMPTION STATEMENT:It is assumed the present trend of automating the process of educationadministration will continue through the mid-1980's. Administrativeoverhead is very large in proportion to the direct costs of actualstudent instruction. There are substantial movements towards auto-mation, whether acting alone or in consort with a human, to reduce thehuman processing time required in administering to the student:selection, housing, course program preparation, evaluation, accrediting,assigning, transferring, counselling, etc.

The result will be larger channels for student throughput, reducedvariations in administrative competence and motivation, and a corres-ponding greater concentration on the primary mission of the trainingfunction. The creative application of automation to training admi ni s-tration could have larger and faster payoff than adapting the computerto training alone.

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SOURCES:1. Miller, Robert B.: File Memo - Summary of Trends in Navy Training,

Fiti Advisory Group, 27 March 73, Section 4.72. Reviewed by IBM Advisory Group, 18 September 1973.

- Med 3 - Hi 4 - Indeterminate

[AEG REPJRT NO. 12-1



[FIELD: Education CATEGORY: AdministrationITEM: Advanced Weapons Potential DATE: Sep 73 NO: 06.006.002.00

ASSUMPTION STATEMENT:Assuming that current military and national doctrines continue on theirpresent course and that resource restrictions remain, it can be furtherassumed that very complex weapons systems may be designed and developedto "paper" levels with either no or very limited hardware production.In the event of critical need, the "paper" system, already field testedthrough complex simulation, would be rapidly implemented.

The training program for such a "paper" weapon would have to bedeveloped to an "off-the-shelf" stage and held in readiness. Coursedevelopment and administrative predictive tools would be applied tocourse validation.

PERIODS OUTPUT I. D05,nni.nni

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_ _4SOURCES:i. Bowen, C. R.: NETS Strategic Seminar, IBM Advisory Group Meeting,

18 September 1973.2. Reviewed by IBM Advisory Group, 18 September 1973.

- No i Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-36

TAEG REPORT NO. 12 -i

E.



FIELD: Education

ITEM: Student.CATEGORY: Motivation

DATE: Sep /3N0: 06.008.001.00


It can be assumed that one of the primary student motivations of thepast, the need for education/training to provide life's necessities,will decline in value and that public, industrial and military train-ing organizations will be impacted.

Based on MacGregor's thesis that a satisfied need is no longer amotivation of behavior and the fact that in our affluent societymany have no concern for filling their basic needs, trainingmotivations will have to be of a higher level including appealsto social acceptance, social approval, self-acceptance anddignity, esteem, prestige, and self-fulfillment.

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SOURCES:Wermuth, Dr. Anthony L., Potential Impacts of Cultural Change onthe Navy in the 1970's, Westinghouse, Falls Church, Va., August1972, Vol-I, 6.


A-II-37




FIELD: Education

ITEM: Certification

CATEGORY: MeasurementDATE: Sep 73NO: 06.007,001.00


The present movement towards certification of competence, as opposed tocertification by completion of some formal study program, will gainmomentum. This will be especially true in the industrial and militarytraining areas.

This shift is being made possible through improvements in thecapability to define training exit skills, knowledge and attitudes, andequal ly important, to measure criterion achievement.

The traditional motivators (a diploma after four years of college, apassing grade at the end of a semester, earning credits, etc.), willhave to be modified somewhat to reflect the motivational needs of astudent achieving criteria within an unstructured time base.

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SOURCES:1. Adams, Dr. E. N.: NETS Strategic Seminar, IBM Advisory Group


- No - Med 3 - Ui 4 - Indeterminate

A-H-38

1


FIELD: InternationalITEM: Regional Powers

CATEGORY: Joint Efforts

DATE:Sep 73 NO: 20.001.001.00


Since all international powers will be restricted in force size by thehigh cost of weapon's technology, the next two decades will see sig-nificant increases in the sharing of mission responsibilities betweenpowers with mutual concerns. This sharing could lead to specializationof national forces. For example, a small power could provide strictly"presence" naval forces with a cooperating large power providing a hightechnology force which would be supporting a number of small low-technology presence fleets.

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Prod 2 '31 3 3 __-.TIMIINeSOURCES:1. Bowen, C. R.: NETS Strategic Seminar, IBM Advisory Group Meeting,


No - Med 3 - Hi - Indeterminate

A -1I -39


FIELD: International

ITEM: MultipolarCATEGORY: Military Environment

DATE Sep 73 NO: 20.002.001.00

ASSUMPTION STATEMENT:It can be assumed that the bipolar environment shared by the U.S. andthe USSR will continue to evolve through the 1980's into a fairlycomplex multipolar environment consisting of sophisticated and as yetunsettled arrays of real economic, political and military influence.

The U.S., Western Europe and Japan, each having a critical dependenceon resources beyond its shores will find unimpeded ocean trade andtransport critical to its economy and defense posture.

Assuming a continued lack of adequate resources for U.S. sea control inthe projected multipolar environment, it can be assumed that the U.S.will require either resource or force support from other powersbenefiting from such control.

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SOURCES:1. Committee #8, "Sea Control Forces," Naval Mission Area Paper,

The U.S. Naval War College, Newport, R.I., 1973, 14

0 - No I Lo 2 - Med 3 - Hi 4 - IndeterminateA-11-40

-11IMO


NETS NAVAL EDUCATION TRAINLNG SYSTEM


ITEM: Law of the Sea


CATEGORY: Military Envi ronmentDATE:Sep 73 NO: 20.002.002.00

ASSUMPTION STATEMENT:Since many of the states which will be participating in the November1973, Law of the Sea Conference (LOSC) have expressed the belief thatthe breadth of the territorial sea and contiguous zone as proposed inthe 1958 conventions are inadequate, it is reasonable to assume that anexpanded territorial sea will be proposed. Consensus appears tosupport a 12 mile territorial sea with a somewhat larger contiguouszone, probably 24 miles.

If this assumption is correct, 116 straits in the world will revert toterritorial waters and, presumably, require that vessels transitingsuch straits adhere to the provisions of innocent passage. Unless 6critical straits of the 116 are excluded, amphibious projection opera-tions will be seriously hampered, particularly in the Mediterranean,Red Sea, and Persian Gulf Areas,

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Prot: ENIMIN IISOURCES:1. Committee p14, "Amphibious Projection Forces," Naval Mission Area

Paper, The U.S. Naval War College, Newport, R.I., 1973, 31 & 32


A-II-41




ITEM: Small Navies


11.....=1,CATEGORY: Military EnvironmentDATE: Sep 73N0: 20.0O2.003.00

ASSUMPTION STATEMENT:It can be assumed that the navies of "small" powers will have the following characterist.;cs by the mid-1990's:

1. Surface effect ships will have replaced the displacement hull (of1000 tons displacement).

2. Relatively small submarines will satisfy the sub-surface roll.Stress will be on detection rather than endurance.

3. Use of VTOL aircraft will have increasing application in the air

support role.4. Technological innovations such as laser weapons, multi-use plat-

forms, modularity, etc., will significantly increase small navyeffectiveness.

Many nations have had to make do with old WW II ships. The next twodecades will provide an opportunity for small navies to make a majorleap forward when they plan the acquisition of replacements.

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SOURCES:1. Committee #38, "Small Future Navies," Naval Mission Area Paper,

Tne U.S. Naval War College, Newport, R.I., 1973.

- No I - Lo 2 - Med 3 Hi 4 - Indeterminate

A-1I-42




FIELD: InternationalITEM: Importance of Sea

CATEGORY: GeopoliticalDATE: Sep 73 NO: 20.003.001,00

ASSUMPTION STATEMENT:It can be assumed that within the next 10 years, 90 percent of theworld's population will reside within 600 miles of navigable oceansurface.

From a U.S. viewpoint, the geopolitical importance of the sea cannotbe denied. Of 111 sovereign states having coastlines, 42 enjoydefense treaty commitments with the U.S. In this day of rapid culturalindustrial, population, economic and, above all, technological cirowth,it can be assumed that the U.S. can no longer continue to serve as theworld's policeman.

Recognition of this fact is evident in the Nixon Doctrine.

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Prole; 3 3 lingfillill MINIM,SOURCES:1. Committee 017, "Presence," Nava' Mission Area Paper, The U.S.

Naval War College, Newport, R.I. , 197-3,


A-II-43


N lJ 11 S NAVAL EDUCATION TRAINING SYSTEM

...11, Strategic! ASSUniptions

J1111101M1.411.1.1MMI

FIELD; International CATEGORY: GeopoliticalITEM: Technology DATE:Sep 73 NO: 20,003.002.00

ASSUMPTION STATEMENT:There is no question that technological advances can benefit entirepopulations and lead to increased international cooperation. However,it can also be assumed that certain types of change can become theseed cause of conflict.

The impacts of technology, primarily Western, on long-held values maybe highly disturbing. To pro.-.,-)te radical change without being awareof the latent potential disruptions is to invite strains the hostcommunity itself does not understand. Issues about which polarizationmay be expected include the need for population control , thedominance of Western life due to increased industrialization - con-tributing to the resultant revolution of rising expectations, and thecoming competition over exploration of the resources in the oceans andthe seabeds. These issues are potentially explosive.

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P r 0 IRIES11111111 INN MOSOURCES:1. Wermuth, Dr. Anthony L., Potential Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August7)72, Vol-f, 32 1 31-.


A- I I- 4 4


NFTS NAVAL EDUCATION TRAINING SYSTEM


1._FEELD: International

ITEM: Basic NecessitiesCATEGORY: ResourcesDATE:Sep 73 NO: 20.004,001,00


It is assumed that the lack of basic resources required for survivalwill become an increasingly major factor in international relation-ships.

It is predicted that economic and technological gaps will widen, that85% of the world will be struggling to survive, that food productionmay fall further behind population growth, and that resources aredwindling and will be difficult for the heaviest users to import. Theless developed countries are already warning the advanced countriesthat they will not remain indefinitely in states of technological andeconomic inferiority.

It appears essential that the U.S. maintain a substantial Navy fordeterrence of conflict or defense of American interests against re-source predators for years to come.

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SOURCES:

1. Wermuth, Dr. Anthony L., Potential Impacts of Cultural Change onthe Navy in the 19701s, Westing-house, Fills Church, Va., August1972, Vol-I, 31 & 34

0 - No 1 Lo 2 - Mcd 3 - Hi 4 - Indeterminate

A-II-45

TAEG REPORT NO. 12 -1



10FIELD: Domestic Inst)tutions CATEGORY: Economy

DATE:Sep 73 No:22.001,001,00ITEM: Worker S k i l l

ASSUMPTION STATEMENT:It can be assumed that the American economy will be marked by increas-ing efficiency and automation, and that this, in turn, will lead toless demand for unskilled and semi-skilled workers. However, therewill be an increased demand for professional, technical, and para-professional personnel.

Manpower utilization policies will change; shorter work days and weeksmore holidays, longer vacations, more fringe benefits, early retire-ment coupled with vested pension rights, and flexible hours - all willbe part of industry's attempts to cope with automation - induced unem-ployment, greater employee self-assertion and organization, and concepof increasing productivity through positive reinforcement.

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SOURCES:1, Werrnuth, Dr. Anthony L., Potential Impacts of Cultural Change on

the Nav in the 1970's, Westinghouse, Falls Church, Va., August9 , of -I, 5.


A-I1-46




FIELD: Domestic Institutions CATEGORY: EducationDATE:Sep 73 NO: 22.002.001:00ITEM: Value of Degree

ASSUMPTION STATEMENT:It can be assumed that in all sectors of society, the value of acollege degree will decline as a prerequisite to employment. The

degree explosion and consequent cheapening of a university education,coupled with the disillusionment of the "over-qualified" individualis tending to ensure this.

The concept of education, as an integral part of life, will grow andthe current division between work and education will become lessdistinguishable.

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SOURCES:

1. Wermuth, Dr. Anthony L., Potential Impacts of Cultural Chan_.ge onthe Navy in the 1970's, Westinghouse, Falls Church, Va. , August19T2, Vol -I, 86.


A-II-47




FIELD: Technological CATEGORY: Education/TrainingITEM: Skill Transferability DATE: Sep 73NO: 30.001.001.00


It is assumed that future education and training plans will be in-creasingly impacted by two major variables: the psychologicalaspects of growable skill and competence from one "level" of skillfor range of skills) to another; and the administrative aspectswhich determine what is organizationally feasible in terms ofopportunity fur experience and migration of individuals intobroader or more specialized work.

Source # 2 - "7. Navy manpower forecasts will be complicated byincreased specialization, changing demand forindividuals with key skills, and the rapiditywith which certain skill requirements willchange."

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SOURCES:1. Miller, Robert 8.: File Memo - Summary_ of Trends in Navy Training,

;am Advisory Group, 27 March 73, Section 2.12. Wermuth, Dr. Anthony L.: Potential Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August72, /01-1, 40.

3. Reviewed by I8M Advisory Group Meeting, 18 September 1973

- No I - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-I1-48


N E 1 S NAVAL EDUCATIOr TRAINING SYSTEM


111.11141111111.11.

FIELD: TechnologicalITEM: Devices

CATEGORY: Lask ReductionDATE: Sep73 NO: 30.002.001.00

ASSUMPTION STATEMENT:It is assumed that the present trend of reducing or eliminating manual/mental tasks through low cost job aids will accelerate through the nextdecade. Micro-electronics is rapidly paving the way for miniaturizedand low cost job aids in the form of calculators, information retrievalterminals and other devices, stand-alone or attached to computers.These devices will largely replace reference manuals, job instructions,checklists, planning guides and a large number of job aids ranging fromplanning and decision making, through diagnosis, down to clerical andlow level procedural activities. These devices will have radicaleffects on the kinds and amount of formal training required to preparepeople for their tasks, and especially for cross-training and modifica-tions to training. Obviously, these devices will change job proceduresand, therefore, training objectives.

(Source I)The resultant of the above will be a shift from formal training to "on-the-job" acquisition of the skills required to properly utilize theJPA's (Job Performance Aids).

(Source 2)

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Prot mom 3 alnummisainmSOURCES:1. Miller, Robert B.: File Memo Summary, of Trends in Navy Training,

ISM Advisory Group, 27 March 73, Section 3.52. Fox, Raymond G.: NETS StrateLic Seminar, IBM Advisory Group, 18

September 19733. Re% ',awed by IBM Advisory Group, September 1973

0 - No 1 - Lo 2 - Med 3 - Iii 4 - IndeterminateA-11-49

NETS



Strat(4.';ic AssumptIons

FIELD: TechnologicalReliability

CATEGORY: Task ReductionDATFISer., 73 NO: 30.002.002.00

11INMPI

ASSUMPTION STATEMENT:Although difficult to quantify, it can be assumed that there will be asignificant increase in the reliability of Weapons systems and theirsupporting systems. The skill level required of maintenance personnelwill be significantly reduced. Operators will not require as high alevel or quantity of contingency skills.

Since failure rates will become so low as to preclude any meaningfulreinforcement of skills through experience, the armed forces willincreasingly depend on Job Performance lids in lieu of training,artificial reinforcement of required skills through simulation, and/orremote maintenance or maintenance support.

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1,...*=./aiSOURCES:1. Fox, Raymond G. NETS Strategic Semi nar, IBM Advisory Group,

18 September 1973.2. Reviewed by IBM Advisory Group 18 September 1973


TANG REPORT NO. 12 -1


Str:I.legic. Assumptions

FIELD: Technological

ITEM: Competence

CATEGOliV: PersonnelDATE: Sep 73 NO: 30.003.001.00


Assuming that the "arms race" becomes a race for high technologiesinstead of quantitating arms, it can be assumed that the net resultantmay be a requirement for a very considerably smaller number of manpowera relatively small percent of whom constitute a highly trained,technologically sophisticated elite.

Very high technology has certain characteristics almost invariablywherever it appears. To operate high technology where deviance from aroutine is required, generally much higher standards of intelligenceand technical performance are required. Conversely, at a lower levelwhere routine performance is required, a much lower level of competenceis required which normally gives way to automation of the function.

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SOURCES:1. Bowen, C. R.: File Memo - Future of the U.S. Navy Training System,

IBM Advisory Grobp, 15 June 1973

- No 1 Lo 2 - Med 3 - Ili 4 - Indeterminate

A-I1-51



FIELD: Technological

ITEM: I nterchangeabi 1 i tyCATEGORY: WeaponsDAJE:Sep 73 NO: 30.004.001.00

ASSUMPTION STATEMENT:Due to the cost and complexity of future weapon's technologies combinedwith the need to have weapon platforms serve multiple tactical require-ments, it can be assumed that both the modules comprising a givenweapon and the weapons of a given delivery platform will have a highdegree of interchangeability.

It is understood that support systems for weapons will be socomplex as to preclude "interchangeability." However, it is felt thatforce reductions will make versatility an essential characteristic offuture force units.

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SOURCES:1. Bowen, C. R., NETS Strategic Seminar, IBM Advisory Group Meeting,



A-II-52


N L' 'I' L; NAV:11, EDUCATION 'TRAINING SYSTEM

Stralev,ic Assumptions

FIELD: Technological CATEGORY: WeaponsITEM: Satellite Neutralization DATE:SeP 73 NO: 30.004.002.00

ASSUMPTION STATEMENT:If it can be assumed that to successfully accomplish its three missions(Presence, Projection and Control) with restricted force levels, theNavy must have the capability to deny its intentions to an enemy and toisolate the objective area, it becomes obvious that measures must betaken to neutralize projected enemy satellite capability.

Based on this, it can be assumed that R&D will lead to sophisticatedmethods of jamming, deception, denial or destruction of enemysatellites.

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Prot ilimuumummumSOURCES:1. Committee #25, "Impact of a Satelli te Environment on Naval

Operations," Naval Mission Area Paper, The U.S. Naval War College,Newport, R.I., 1973, 11.


A-II-53am*

TAG REPORT NO. 12-1


Strutegic

MELD: TechnologicalITEM: Computer Lapabi 1 i ty

CATEGOR Y: AutomationDATE:Sen 73 NO: 30.005.001.00 ,./.

ASSUMPTION STATEMENT:Assuming a continuation of the current rate of computer development, itcan be assumed that by the mid-1980's computer capability will increaseapproximately ten fold and physical size and environmental requirementswill be reduced by a factor of ten. It is also assumed that the costper interaction will significantly decrease.

The implications to even the smallest and most remote military unit orforce are significant particularly in the area of information trans-fer and its associated area, training. The use of computing power forremote maintenance, on-site Job Performance Aids, computer assistedinstruction, etc., will significantly increase.

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No 1 - Lo 2 - Med 3 - lui 4 - Indeterminate

A-II-54


NEf 1 11S NAVAL, EDUCATION TRAINING SYSTEM

Stratc:!ic Assumptions

FIELD: Technolrgical

ITEM: Weapons Systems

CATEGORY: AutomationDATE:Sep 73 NO: 30.005.002.00

ASSUMPTION STATEMENT:It can be assumed that the current trend to automated support andweapons systems will continue to accelerate. Although it is too earlyto assess the impact on personnel skill requirements, some sub-assumptions can be projected as follows:

. Only a very limited number of people will be required to maintainand operate very large and complex systems relative to today'srequirement for a similar system.

. Although the normal tasks required of personnel will demand lowerskills than required by current systems, the operator may requiresome very high level capabilities to permit his intervention inthe automated process if the tactical situation demands it.

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SOURCES:1. Bowen, C. R.: NETS Strategic Seminar, IBM Advisory Group, 18

September 19732. Reviewed by IBM Advisory Group, 18 September 1973

- No 1 - Lo Z Med 3 - Hi 4 - Indeterminate

A- I I - 65


_A_ NETS NAVAL EDUCATION TRAINING SYSTEM


FIELD: Technological CATEGORY: Military PlatformsITEM: Air Cushion Vehicles DATE: Sep 73 NO: 30.006.001.00

ASSUMPTION STATEMENT:It can be assumed that by the mid-1980's ACV hulls of 4000 to 5000tons will be possible with sufficient size for any form of propulsionincluding nuclear.

The ACV has the following advantages:

1, The ACV raft-like shape gives a stable weapon platform.2, It can be built to be amphibious.3, It can have a light structure despite its large size.4. It can be designed to have a large "flat top" almost as big as

the craft allowing the operation of VTOL aircraft and helicoptersor the positioning of weapon systems, radars, and payloads anywhereat will.

5. It can have a low acoustic, pressure and magnetic signature.

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SOURCES:i. Committee 038, "Small Future Navies," Naval Mission Area Paper,

The U.S. Naval War College, Newport, R.I., 1973, 9 & 10

0 - No 1 - Lo 2 - Med 3 - Iii 4 - Indeterminate

A-II-66




FIELD:Military DoctrineITEM: Political

CATEGORY: MissionDATE: Sep 73 NO: 40.001.001.00

ASSUMPTION STATEMENT:The present shift fron a doctrine of "mutual exclusion," a reasonablyclear separation of civilian and military functions, to a doctrineusing the military as a bargaining instrument for acceptablepolitical solutions will continue through the mid-1980's.

Prior to this shift, the mission was the destruction of the enemy armedforce in the shortest period of time with the fewest possible friendlycasualties. During the negotiating phase of the Korean war, thecombat function lost its last vestige of autonomy from politics. Theworld situation will require the orchestration of the militaryinstrument with the other elements of statecraft - political, economic,psychological, and social. The mutual exclusion of civilian andmilitary roles has given way to what has been called "fusionism."Civilian participation in what had been the exclusive province of themilitary has proceeded rapidly.

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.1PINNI.1SOURCES:1. Gard, Brigadier General Robert G., Jr., U.S. Army, "The Military

Profession", Naval War College Review, Naval War College, Vol. 26No. 1/244, July/August 1973, 8

-No 1 -Lo - Med 3 - H i - Indeterminate

A-11-57




FIELD: Military Doctrine CATEGORY: MissionITEM: Tactical Air Projection DATE:SeP 73 NO: 40.001.002.00


Excluding strategic nuclear war, the worst case threat to the U.S. isgeneral non-nuclear or tactical nuclear war with the USSR. The follow-ing assumptions pertinent to use of naval tactical air under non-nuclear case conditions are:

1. Since in the early worst case situation, the sea control missionwould predominate, Naval air projection forces should be tailoredto use in later stages of worst case when at least local seacontrol and air superiority have been established.

2. For low threat environments, the Sea Control Ship with VSTOLaircraft would produce the desired results.

3. Although attack carrier levels will decline, the internationalsituation will demand sufficient numbers to cover mid-intensityand greater exposures.

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SOURCES:

1. Committee #12, "Naval Tactical Air Projection Forces,"Naval Mission Area Paper, The U.S. Naval War College, Newport,R.I., 1973, 1-, 3& 13

0 - No 1 - Lo 2 - Med 3 - Hi 4 - IndeterminateA-I1-58


alallMy

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FIELD: Military DoctrineITEM: Amphibious Projection

CATEGORY: MissionDATE :Sep 73 NO: 40.001.003.00

ASSUMPTION STATEMENT:Assuming no major shift in the Nixon Doctrine, the following can be

assumed pertinent to the use of Amphibious Projection Forces (APF).

1. APF 's will continue to provide the U.S. with a vi tal capability forprosecution of a maritime strategy as amplified by the NixonDoctrine. The APF allows the President to choose the time, placeand degree of involvement without concern for shore-basing or overfl ight rights.

2. Current APF sealift and manpower levels will be adequa,te to meetany contingencies within the 1975-1985 time-frame.

3. Current tactics and weapons systems will require continuous R&Dand procurement in order to maintain a credible balanced force.

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SOURCES:

1. Committee xl4, "Amphibious Projection Forces," Naval Mission AreaPaper, The U.S, Naval War College, Newport, R.I., 1973, 28 & 30.

- No 1 Lo 2 - Med Hi 4 - Indeterminate

A-II-5 9

1




FIELD: Military Doctrine CATEGORY: MissionITEM: Presence Forces DATE:Sep 73 NO: 40.001.004.00


Due to the range and degree of forces required to support the Navalpresence mission, it can be assumed that some significant changes maybe made in the tactics of maintaining presence if the mission is tobe accomplished within available limited resources.

Assuming that U.S. Naval Forces diminish and task forces can no longerbe sustained indefinitely in distant areas, individual ships or forcesconsisting of a few ships will have to be relied upon to convey atleast occasional evidence of U.S, goodwill and concern in those areaswhere once the U.S. Navy was able to sustain formidable presenceforces.

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SOURCES:1. Committee #17, "Presence," Naval Mission Area Paper, The U.S.

Naval War College, Newport, R.I., 1973, 12


A-II-60



FIELD:MI 1 i tary Doctrine

ITEM: Sea Control

ASSUMPTION STATEMENT:It can be assumed that up to 1980, Sea Control among the NavalGeneral Forces will receive resource priority.

Despite the encouraging aspects of detente with the Soviet Union, thefact remains that the Soviets are capable of challenging us now andother countries will probably be able to do so in the forseeablefuture. More importantly, our decreasing ability to survive in theopen ocean environment without incurring significant, if notprohibitive, losses, is probably the Achilles heel of the U.S. Navy'sposture today.


CATEGORY: Mission

DATE:Sep 73 NO: 40.001.005.00

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Naval Forces From a Projection Mission to a Sea Control Mission,"Naval Mission Area The U.S. Naval War College, Newport,

R.I., 1973, 11.


A-II-61



Stratvgi Assumptions

..mirmorrral

FIELD: Military DoctrineITEM: Defense

CATEGORY: National PolicyDATE:Sep 73 NO: 40,002.001.00

ASSUMPTION STATEMENT:The concept of "national security" as opposed to "national defense"will remain a primary base through the mid-1980's.

The national defense approach was based on security maintenancethrough reliance on a tiny, physically isolated army and a relativelylarge but still small Navy, both of which could be expanded bymobilization in time of emergency. In case of threat, destruction ofthe offending force was considered the clearest way to end the threatto freedom, Little attention was paid to using limited force todefeat the enemy.

The national security policy is applicable in both peace and war,The world situation will continue to require not only the maintenanceof substantial ready forces, but also the orchestration of the military

instrument with the other elements of statecraft-political, economic,psychological and social. Deterrence of general war will have thehighest national priority.

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SOURCES:1. Gard, Brigadier General Robert G. , Jr., U.S. Army, "The Military

Profession," Naval War College Review, Naval War College, Vol. 26,No. 1/244, July/August 1973, 10-


A-II-62



Stritt*i0 Assumptions

FIELD: Military Doctrine CATEGORY: National PolicyITEM: Nixon Doctrine DATE:Sep 73 NO: 40,002.002.00

ASSUMPTION STATEMENT:It is assumed that the key elements of the Nixon Doctrine will continueto form the basis for U.S. military doctrine into the mid-1980's.Although the doctrine stresses diplomatic efforts for peace and theavoidance of confrontation, it does state that the U.S. will:

1. Keep all treaty commitments.2. Provide a nuclear shield for its allies.3. Provide military and economic assistance when requested.4. Rely on the nation directly threatened to provide manpower and the

major effort in its own defense.5. Provide help wherever it will make a difference and contribute to

the interests of the United States.

In support of the above, the Navy defines four mission areas.1. Strategic nuclear deterrence; 2, Power Projection; 3. SeaControl; 4. Overseas Presence.

A'' IP PERIODS OUTPUT I, D0 01 01

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SOURCES:1. Committee 417, "Presence," Naval Mission Area Paper, The U.S.

Naval War College, Newport, R.I., 1973, 1-2



FIELD: Mil itary Doctrine CATEGORY: ArmamentsDATE: Sep 73 NO: 40.003.001.00ITEM: Level

ASSUMPTION STATEMENT:Due to a leveling in the quantity of naval armaments, just as was thecase with strategic missiles, it can be assumed that the race will betechnological rather than quantitative. The diversion of expendituresotherwise slated for additional fleet units (beyond replacement) willgo into increased research and development. This should lead to muchmore complex, sophisticated equipment to insure a continued qualitativesuperiority in weapons over any other nation.

o PERIODS OUTPUT I. I)e se el niaravurainfirannneur.in o 1 li ii

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SOURCES:1. Bowen, C. Ph.: File Memo - Future of System,

IBM Advisory Group, 15 June 1973.

No Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-64


NETS NAVAL, EDUCATION TRAINING SYSTEM


FIELD: Military Doctrine CATEGORY: ArmamentsITEM: Strategic Deterrence DATE:Sep 73 No: 40.003.002.00

ASSUMPTION STATEMENT:The following can be assumed to be a general U.S. nuclear deterrencestrategy that will support stated national policy:

"A comprehensive direction of power (military, diplomatic,and economic power) to persuade our adversaries that it isin their interest to desist from a nuclear attack on theUnited States and to pursue, with us, serious negotiationstoward limiting, then reducing, and eventually banningnuclear weapons."

Although national policy is hard to define, President Nixon's state-ments that we are seeking a decade or generation of peace; that we aremoving from an era of confrontation to one of negotiation; that we areseeking to curb and reverse the arms race; and that our ultimate goalis complete nuclear disarmament; tend to support the above strategy.

ismoirwassoIfigXlarbIll11BWITOMIIIIMPI

Imi imiivitawairinmninesaerPERIODS OUTPUT I. D

0 30 00,.002

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SOURCES:1. Committee #3, "Strategic Deterrence Forces," Naval Mission Area

Paper,, The U.S. Naval War College, Newport, R.I., 197, 3 & 4

- No 1 Lo 2 - Mcd 3 - Hi 4 - Indeterminate

A-I1-65




FIELD: Military Doctrine CATEGORY: ArmamentsITEM: Second Strike DATE: Sep 73NO: 40.003.003.00

ASSUMPTION STATEMENT:It is assumed that the U.S. currently has the level of nuclear secondstrike capability required to support its present strategy.

Since "deterrence" is the key philosophy guiding this strategy, it canbe assumed that the limited funds projected for national defense willnot be diverted to development of a first strike capability. It can beassumed that the destructive capability of the U.S. arsenal, evengranting the unlikely event that two-thirds of it were destroyed, isstill sufficient to wreck such devastation as any rational adversarywould consider unacceptable. To the extent that any adversary can bedeterred, therefore, our present nuclear capability is sufficient forsuch deterrence.

1/4 ..10(011011111fiffillialfillIIINIMIIII1140.002.001

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SOURCES:

1. Committee #3, "Strategic Deterrence Forces," Naval Mission Areapaper, The U.S. Naval War College, Newport, R.I., 1973, 5 & 7


A-II-66




FIELD: Military Doctrine

ITEM: SLBMCATEGORY: ArmamentsDATE: Sep 73 No: 40.003.004.00

ASSUMPTION STATEMENT:It is assumed that, in a five to ten year range, nuclear deterrencestrategy will continue to depend upon the triad of strategic bomber,ICBM and SLBM. However, it can also be assumed that after that periodhas elapsed, the SLBM will predominate.

Current vulnerability of the strategic bomber and ICBM missile silos.will result in the SLBM leading based on its survivability of a firststrike. Even if the enemy suddenly made a gargantuan technical break-through in ASW sensors, his forces would still have to search overthree million square miles of ocean to locate and destroy FBM sub-marines.

This assumption is predicated upon development and implementation on atotally reliable and effective command, control, and communicationssystem.

/1ilk ' o 1112 PERIODS OUTPUT I. D6 et et IIIINFIlritarillIfilifilifir111113RINEll

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Prot. 1 ©E©©1 IIIIIIM NMSOURCES:1. Committee #3, "Strategic Oetermence Forces," Naval Mission Area

Paper, The U.S. Naval War College, Newport, R.I., 19/3, "6 & 17.

0 - No 1 Lo 2 - Med 3 - 1-li 4 - Indeterminate

A-11-67




FIELD: Military Doctrine CATEGORY: ArmamentsITEM:Capital Presence Ship


DATE:Sep 73 NO: 40.003.005.00

Based on the assumption that aircraft carriers, perhaps the ultimatein presence forces, have become inordinately expensive to constructand operate, it can be assumed there will be an evolution to asmaller, less costly, and more plentiful type of ship with some air-projection potential. Therefore, the Sea Control Ship may very wellbecome the capital presence ship of the future.

Although the SCS will never replace the aircraft carrier, it can servein a power projection role in those areas where the presence of acarrier may be prpvocative or unwarranted.

INPUT I.D. ° PERIODS OUTPUT I. D.001 3

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SOURCES:

1. Committee #17, "Presence," Naval Mission Area Paper, The U.S.Naval War College, Newport, R.I., 1973, 12-13

0 - No I - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-68

TAEG REPORT NO. 124



...6.11,FIELD: Military Doctrine CATEGORY: ArmamentsITEM: Satellite Impact DATE: Sep 73N0 :40.003.006..00

ASSUMPTION STATEMENT:It can be assumed that most of the power structures will have developedand implemented sophisticated military satellite communication andtactical systems by the mid-1980's. The major effect will be on U.S.Sea Control, Presence, and Projection missions.

In both cases, reduced Naval forces increase the need for surprise.Satellite detection will greatly increase the probability of detection.A submerged FBM or SSN submarine is not presently susceptible tosatellite detection. However, the possibility of a technologicalbreakthrough enabling such detection should be considered within aplanning horizon of two decades.

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SOURCES:I. Cor74,ittPe .25, "Impact of a SatIlite Envirt,liv:nt on Naval

OpPra',itoc," Naval Mission Area Paper, The .S. Naval War College,Nmort, P.I., 1173, 5 Fi 6.

0 1 - Lo 2 - 111(,d 3 - Hi 4 IndrAvrminate

A-II-69




FIELD: Naval FactorsITEM: Mission Orientation

CATEGORY:Organi zationalDATE: Sep 73 NO: 60.001.001.00

ASSUMPTION STATEMENT:It is assumed that the armed forces will become increasingly missionas opposed to service oriented.

This assumption is predicated on the increasingly higher costs of newtechnology and the continued trend in Armed Force size reduction.With some of the high technology systems approaching $50 or $100billion in cost, we probably will see multiple uses for the U.S.Armed Forces such as outer space and underocean exploration; also, thcuse of these high technology forces for commercial purposes such asfarming and mining to give the armed forces a return on theirincredibly huge investment.

lk I o P R ID OUTPUT I.D$ ifs is i1 17rarn ! Ii111111111111311111311 o I 41 01

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SOURCES:

1. Bowen, C. R.: File Memo - Future of the U.S. Navy TrainingSystem, IBM Advisory Group, 15 June 1973

0 - No 13- Lo 2 - Med 3 - Hi 4 - Indeterminatei 1 I '''

A-II-70


NE:TS NAVAL EDUCATION TRAINING SYSTEM


FIELD: Naval FactorsITEM: Training Centralization

CATEGORY: OrganizationalDATE: Sep 73N0: 60.001.002.00

ASSUMPTION STATEMENT:Assuming that the Navy continues its thrust towards high technologiesand that this thrust results in the need for a "technological elite",it can be further assumed that increased centralization of train-ing will be essential.

Since the success of the naval forces will essentially depend upon thecompetence of this "technological elite," they will be the major focusof naval training. In order to insure the success of this trainingand to focus top resources on it, it is believed the U.S. Navy willcentralize, as a minimum this training and as a maximum all, theirtraining.

11, PERPIDS OUTPUT I.D1 e t r i

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SOURCES:1. Bowen, C. R., File Memo - Future of the U.S. Navy, IBM Advisory

Group, 15 June 1973


A-II-71


FIELD: Naval Factors

ITEM: Educational R&D

CATEGORY:Research and DevelopmentDATE: Se 73NO: 60.002.001.00


Assuming that a combination of factors will result in centralizationof naval training, it can be assumed a greater amount of R&D will beaccomplished by naval training.

Given the possibility of a necessary "critical mass" of research, realprogress can more readily be achieved in the following areas:

A. The basic disciplines such as psychology, learning theory,statistical prediction of behavior, etc.

. Behavior Modification. In particular, the Navy, due to itsextremely complex weapon systems, will be interested inintelligence enhancement through chemicals and prosthetic devices.

. Instructional devices and systems utilizing rapidly advancingcomputer and communication technology.

t PERIIDS OUTPUT I.D____0a,001.001

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SOURCES:

1. Bowen, C. R.: File Memo - Future of the U.S. Navy, IBM AdvisoryGroup, 15 June 1973

- No 1 - Lo 2 - Med 3 - Hi 4 - Indeterminate a

A-1I-72




FIELD: Naval FactorsITEM: Student Motivation

01111.

CATEGORY: Research and DevelopmentDATE: Sep 73 NC: 60.002.002.00


Based on the combined trends in nava, training, it is anticipated thatan increasingly large share of the resources available for trainingR&D will be directed towards developing techniques for student"motivation."

Student motivation has greater impact on training efficiency andeffectiveness than any other one factor. The combined trends ofindividualized instruction and emphasis on certification based on skillproficiency will result in a need for improved techniques for studentmotivation.

.----,h ' ' 1 p o PERIIDS OUTPUT LDIltiYARsonpum vrammnraravuotararaniuniuri n o 1 a.002.nnl

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SOURCES:

1. Adams, Dr. E. N.: NETS Strategic Seminar, IBM Advisory Group,18 September 1973

2. Reviewed by' IBM Advisory Group 18 September 1973

0 - No - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-I1-73




FIELD: Naval Factors CATEGORY: EducationITEM: Civilian Contractors DATE: Sep 73NO: 60.003.001.00

ASSUMPTION STATEMENT:Assuming a continuing emphasis on resource reduction, there will be anincreasing need for the armed forces to assign their personnel todirect support functions. As a resultant, there will be an increase inthe use of,civilian contractors to fulfill training responsibilitiesnow being accomplished with military people.

There are other assumptions, pertinent to improved job assessment andassociated task analysis combined with improved post-training measure-ments, which will greatly facilitate development of training contractsand in measuring contractor performance.

q r a PE IDS 0 TPUT I.DI Wet III . . 0.1111F111.111111111111 60.001.00230.003.00

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SOURCES:1. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group



A-II-74

gIner'



Strategic A ss u nip t ion s

FIELD:Naval FactorsITEM: Multi-service Use

CATEGORY: EducationDATE :Sep 73 NO: 60.003.002.00


It can be assumed that there will be a significant trend towards thesharing of training facilities and courses by the armed services.

The projected trends in weapons systems and the skills required tooperate and maintain them will make the sharing of the training burdenboth feasible and cost-effective. Continuing budget restrictions maymake this essential.

0 Wil PERIODS OUTPUT I. I)0. Is animewarantammilrini9111111,1 n o 04.002'00130.001.001 1111

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Prole_ 1 2 21313..1SOURCES:1. Fox, Raymond G,: NETS Strategic Seminar, IBM Advisory Group,

18 September 1973.2. Reviewed by IBM Advisory Group, 18 September 1973


A-II-75




FEELD:Naval FactorsITEM: Variable Loads

CATEGORY: EducationDATE:Sep 73 NO: 60.003.003.00

fr

ASSUMPTION STATEMENT:It is assumed that future naval doctrine will attempt to anticipate acomplex and significant range of requirements with a resultingpotential for wide variations in training loads. Therefore, the Navywill increasingly stress application of those educational technologiesaccommodating wide variations in loads. This assumption amplifiesthe current trend towards self study and "individualized" instructionplatforms.

This is supported by the assumption that some future weapons systemswill be designed and developed only to the "paper" stage and then helduntil the military situation dictates production. Self study packageswill be required to form an "at ready" training program for thesepaper systems.

I ' PER DS OUTPUT I. a' I. ,11 IWAIIIIIII

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SOURCES:1, Bowen, C. R.: NETS Strategic Seminar, IBM Advisory Group Meeting,


4.1.11111.0. - No 1 - Lo 2 - Med 3 - Hi 4 - Indeterminate

A-II-76




40 IMENIME.WM.6-

FIELD: Naval Factors CATEGORY: EducationITEM: Graduate Study DATE: Sep 73 NO: 60.003.004.00


Due to the complexity of the technological and social environment ofthe 1980's and beyond, it is assumed that the Navy will significantlyincrease the number of graduate level programs pertinent to itsofficers and certain enlisted ratings.

It is anticipated that the "college without walls" concept willcontinue to spread in the community at large and will greatlyfacilitate both graduate and undergraduate level work in theArmed Forces.

*kr

k. PER DS OUTPUT I. Ds s tja ME , s s - - 111111111311111Zio s onl.onl_.4.00 is Wil 1

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______ _

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_ _ _ _ _ _ _ _ . _ _ _

SOURCES:

1. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group, 18September 1973



A-II-77


FIELD: Naval FactorsITEM: Job Commonalty

CATEGORY: PersonnelDATE:Sep 73 NO: 60,004.001.00


Due to the trend towards mission (as opposed to service) orientation ofthe armed services, and to the trend projected for skills required tosupport future weapons systems, it is assumed that the armed serviceswill move towards a uniform system for defining occupational tasks andskills.

This is compatible with the assumption that the armed forces willincreasingly share training facilities and courses.

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SOURCES:

1. Fox, Raymond G.: NETS Strategic Seminar, IBM Advisory Group,18 September 1973


3, Coomittee #38, "Small Future Navies", Naval Mission Area Paper,The U.S. Naval War College, Newport R.I., )913, if- No 1 - Lo 2 - Med 3 - Hi. - Indeterminate

A-11:78





ITEM: Enlistee AttitudesCATEGORY: PersonnelDATE: Sep 73 NO: 60.004.002.00

ASSUMPTION STATEMENT:It can be assumed that the general attitude of today's youth, thatmilitary service is an interruption of their lives rather than alearning experience and career enhancement step, will continue to somedegree through the next two decades.

¶he captive force permitted by the draft since World War I I, wi th the..ixception of one year,permitted development of some approaches withinthe military which tended to foster emphasis on institutionalobjectives, even unimportant ones, with minimum regard for the impacton personnel. The military, as is true of industrial and civilinstitutions, will have to develop a deeper understanding of humanattitudes, motivations, and behavior. An objective of military train-

ing will be to change the attitude of military service as an"Literruption" to that of an "opportunity" for continued development.

t OW PERIaDS OUTPUT 1.DIV is gallEIMI

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- - - -04,__0_04,002 _____

. .06 007 001-06. oU. In Pro ringummlum =gm ________

SOURCES:1. Gard, Brigadier General Robert G. , Jr., U.S. Army, The Military

:'rofession," Naval War Colle e Review, Naval War College, Vol. 26,No. 1/244, Ju y ugust 197 1 & 15.


A-11.79




FIELD: Naval FactorsITEM: Pilot Proficiency

1111111111,

CATEGORY: PersonnelDATE : Sep 73 NO: 60.004.003.00

4

ASSUMPTION STATEMENT:Based on the assumption the AVF concept will continue as will acontinued reduction in Navy size, it can be further assumed conditionsand steps taken will result in increased proficiency_of Naval pilots.

As the number of tactical VA/VF pilots/NFO's is reduced, the Navy willhave an opportunity to make these reductions qualitatively as well asquantitatively. The pilot selection, training, and assessment programscould be geared to assure that the best qualified aviators wouldfollow a career pattern emphasizing flying culminating in a highpercentage receiving squadron command by their 15th year. A sidebenefit would be the reduction of the average age of tactical pilotswithout sacrificing experience since they would be flying a greaterpercentage of the time.

l 111

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OUTPUT I. D1 41

40,0017002

,

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Pr ot UMILUMMIMMIIIIII IN 4

SOURCES:

1. Committee #12, "Naval Tactical Air Projection Forces"Naval Mission Area Paper, The U.S. Naval War College, Newport, R.I.

fc

-No -L - Med 3 - Hi 4 - IndeterminateA-II-80




FIELD: Naval FactorsITEM: Women

4.01CATEGORY: PersonnelDATE :Sep 73 NO: 60.004.005.00

ASSUMPTION STATEMENT:It can be assumed that ultimately there will be no activities in whichmen engage that will not admit women on an equal basis, not excludingselected combat roles.

It can be further assumed that the military will have a special interesin research into sex roles, leadership situations involving women incommand roles over men, and the firmness of sexual stereotyping. Theremay be conflict in close-knit institutions between members fromethnic groups with restrictive views of women and the expansion ofwomen's roles in the Navy.

A major increase in the role of women will necessitate a thorough re-view of all institutional policies to eliminate all forms of sexdiscrimination.

h84 is et

laInlMIMI 1101111C111111114

PERIDS1 I 0

OUTPUT L D1, II II

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,--

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SOURCES:1. Wermuth, Or, Anthony L., Potential Impacts of Cultural Change o.

the Nav in the 1970's, Westinghouse, Fans ChurCh, Va., August9 o -I, 4.

- No 1 - Lo 2 - Med 3 Hi 4 - Indeterminate

A-11-82


NET S NAVAL EDUCATION TRAINING SYSTEM


FIELD: Naval FactorsITEM: Postulate #1

CATEGORY: Civil/Military PostulatesDATE: Se. 73 NO: 60.005.001.00

ASSUMPTION STATEMENT:The first postulate envisions a civilianized armed force whose valuessteadily converge with those of civil society. Technology, the riseof "individuation," adaption by the military to youth values inattempts to obtain volunteers, and the improvisational tendency ofmodern, low-intensity conflict - all may well cause democratization ofthe military and a decline of the military mystique, subsantialdecline in authoritarian leadership, and even the emergence of

unionization, as in Sweden or West Germany. Factors militatingagainst this trend are the sustained stress and rigor of actual orpotential combat, once entered; the disaffection of career personnelwith the "New Sensibility," and the marginal impact that changes toappease the "New Sensibility" might have on truly committed anti-establishment dissidents.

PERIODS OUTPUT I. D/ e s I t s 1110111111111111MMINIMID

II

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"r-_ - _ _ _

IIII_ - ___ _____

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_____.

.._.

SOURCES:1. 'e.:.-rmuth, Dr. Anthony L., Potential Impacts of Cultural Change on

the Nav in the 1970's, Westinghouse, Falls Church, Va., August10)2, o -I, 0 .

-No - Med 3 - Hi 4 - Indeterminate

A-II-83


AM11111110MI

AI_ NETS NAVAL EDUCATION TRAINING SYSTEM


FIELD. Naval Factors

ITEM: Postulate #2

.11111. ......11111001111,

CATEGORY: Civil/Military Postulates,DATE: Sep 73 NO: 60.005.002.00

ASSUMPTION STATEMENT:The second postulate stresses a divergence of the civil and militaryand is the reverse of the first. It assumes that an all-volunteerforce will be unleavened by a constant influx of disgruntledcivilian soldiers and upper class officers from liberal backgrounds,and would be recruited instead from traditionally conservativeregions and universities. An increase in hereditary service recruit-ment and a decline in the importance of the civilian reserve wouldprovide further impetus.

This postulate has a low probability since divergence implies conflictwith the general culture and trends within it, a course which is notlikely to attract enough quality personnel in the future.

gra PERIODS r UI.2_1_)i _11,.._'I.If If 1140.002,0 +1

111111111111F11111MVINIFIn_igi

4...

1,4

.5(/)

.10Z

44

r--.al

CilN.a),--

IX)ONr...

.ZI^COCn-

och01roCD0(N.1

111111111111111Wol

-1

1111 CY)al0'1,---

I

i- --

,

Prot 1 1 NMSOURCES:1. Wernitn, Or. Anthony L., Potent'al Impacts of Cultural Change on

the Navy in the 1970's, Westinghouse, Falls Church, Va., August1972, Vo1--I, 108.


A-II-84




VIONEMIMIMI=1.111101111111.11=11111111.11111.011110111110111110.111111..,-.... .01.111Mr


ITEM: Postulate #3

-+CATEGORY:Civil /Mi 1 i tary PostulatesDATE:Sep 73 NO: 60.005.003.00


Postulate #3 envisions a mix of combat and support elements segmentedinto traditionally military and civil ianized support groups. There-fore, the system will be partially divergent, and partially convergent.However, all elements of the military will be affected by drasticsocial change, will interact more with civilian society, and will becalled upon to perform non-military functions. New administrativetools will combine with value and attitude change to keep the wholearea of personnel administration influx for the next decade. Newnorms of interpersonal relations will undergo persistent readjustment.

li, ng PER ODS OUTPUT I. Di s o .011 ADZ.SE:IL

IK11WIre

MCn

111111111MIMICIMM1ll11111111

44

.N

CI.tiCT%

,

C>

ONr-f-- -

C)

(7)r---,

00CV I

--

0rzl

1",Ch

CO01

Cr$01

- -_

. -----4Prot, 2 3 Ella 3 MINIIIIIII1111111111111

SOURCES:1. Wermuth, Dr. Anthony L., Potential Impacts of Cultural Chanatort

the Navy of the 1970's, Westinghouse, Falls Church, Va., August1972, 108

- No Lo 2 - Med 3 - Hi 4 - IndeterminateA-II-85


D. STRATEGIC ASSUMPTION STRUCTURE

The tactical assumptions and recommendations, projecting the idealizedNETS of the 1980's in Section VI of the DOTS Phase I Report, were basedon a set of five key Strategic Working Assumptions (VI D-2). The chartsto follow provide a reference network to enable correlation of theStrategic Working Assumptions to the Strategic Assumptions.

Since the relationships between SA's are numerous and complox, only thosejudged most significant were included. The Strategic Process, at best,is a judgmental one and it is understood that the configuration of anygiven net could take an almost infinite number of patterns.

It is hoped that the forced discipline of the hierarchical approach willincrease the validity of the process. The SA, SWA, change statement,tactical assumption and tactical recommendation flow does provide a de-fined and documented flow permitting analysis and critique of the logicof any given tactical assumption or recommendation.

A-II-87


20.007.001T :,ter,42,064$

C Military baelroormota

70.00/.00220.603.04110.003.00220.004.00140.000.00140.002.007 a

F0.001%40!36.004.00240.036,03440.001.00440 poy. 001444444r4443.003.002

40 003,00340.003.004

0131:1013131300113111CCI11:10100111111111111111111

.......wootbbi

F Noitery Doctrieec Matlooal Polityi Defense ...

LAM I. D.0

o 00:p01 1.1:1,

20.003,03120.003.03220.004.03140.007.002

t 20.002.0012 40.041.0011 40.001.0023 40.001.00)

40.031.00440.001.03340.00.00 .040.041.00360.003.00160.603.00260.063.001

CINICIJOICIIM 11C0©11110111111111111111111111111111

I 40.032.002F aillItery Doctrinec #410441 Pal lty

41044 0_ _:act,___114

ou60,46.0.20.303.001 2 20.001.001

20.002.00120.002.00340.601.00140.001.00040.001.00340.031.0%40.001.00360.002.00140.003.00140.003.002

, 10.003.001F 1,..4 At:00g , IIC rforttnnof

1 (6156106c#

111=1111111101143131/11all

VI. Of, ok'.4u, 001,144

0,001,00110.001.00

0 04 .004 .0C11 06.002,001 66,00..062I 40.0f.1.603

60.341.00100.643.04160.'104.013

0.004.003

001100151:10 OcCiaentaillisiiiiimilisi

# 40.003.037

F MIllt,ry Doetrima

C 4mempnts

I Stratejlc teterferLe

Input 1.0. 0ChApAt I. D.

20.002.00140.002.002

1 30,004.0023 40.003.001

40.003.00340.003.004

04c621D000111,120k1CIE IIIIIIIIIIII POO

I 40.033.00111' 4111140y 00c tri heC Arobaxott

1 Live

,...'-cprrtir-rwr-T.,,S. 20.042.001

20.002.00.130.006.03130,000.002

.43,002,001N. 40.002.0024.40.003.002

40.603.006

b-.7

2 20.001.001..7 30.00:.0013 30.002.042..

3 .10.003.001+41 30.004,00 ? .....41 40.0C..0012 46.601.003

1 10.001.00440. 001.00'060.001.001..060. ro03 . DO3

0131311110111110111311C010011101111111111MIOU

20.001.021F tour,Atio041c J6I6t Efforts

I 0,91041 Pow*. US' ' '

.0.0(1.001t%).1.6...00e79.003.41zo.x3.7otn.on4.%143.667.002

46.003 00143 003.N6

3 01,40.00l1 20,004.6032 411.001,064I1

3

2

I

0013139001011111:11MCICPECIEIE1111111111111111111

10.502.001F forhnolevoli .

C fe,i ;wet co

I Offy!ce4

Inpurrir714fpr0.001.00115.003.001

11.705.0074,..40.tnf.001

f '06.001,0023 04.504.0017 04 00'2,001

1 116 ,17.00206.'x01 .003

04-403.00f06.001.00206.003.00106.005 001

06.006.002 mob

OaccaraonaortFISH'EIM11111111011011

f )0.004.001F Technologicalc WeigorA

i InterchangoabIllty

Input r. D. i. &I put I D

20.0Q2.0.140.)01.0eA

0.003.04:1

OceactibLunilearnrn l

1

i1

111111111111111111

06.002.00106.003.01406.001,06.00530.00i .00140.001.00140.001.00560,001.06160.001.00260.003.00260.003.003

Al001

4'00;%0C'

F 14c44oloocd4

C rim Recuction

1 Pcofb,lity

Input 3 1) o 00404 I.D.

1..43 003.001 I 04 001.00204.004.00106.002.00106.042.00206.042.00106,003.00106 00).00206.003,00106.000.00106.006.002.4

0130131:1131011011JECI111111/111/1111111111111111111

' 60 001.001

f Marsl $40 ',tor5

C nr,4tkitt,A41

I .o,,,,lor, 0,1.mtatIn6

input 1. D. u Output 1. D.

.03. -)01 nO 'am.oi,i,im

I 10.003.0012 60.001.000

60.001.002

0111:11121/1310111111:113CCI1111013611111111111111 Ill

,41011,

A-11-88

TAEG REPORT NO, 12-)

2 40.001.004P Military 0o.trinec IttssIon1 0n-sect Forces

-6-rals.--r-m7rinr

05.002,01-.20.001.001

20.002.00120.002.00220.002.00320,003.001.4.506.10141.00: ool60401.00240.003.00140 003.006

1 10.204.0011 30.004.0022 40.001.0051t2

I

3

21

unciounammucoinsomilimmonse

0 36302301P (4.C.it10I1C A IPInIttr.it No1 00,11%*4 611110+1 Pptert t:

&put 1. D. o Ospot [ D...

1 ,,,,Cc 1.001 *I 06.000.0012 06.004.001I1

1

1

04.002.00106.003.00306,005.00130.001,001

p.30 307.001p.30.102.002

30. 005. 011

1

copouvuotiogicanrnomompommom

0 60,003,302? IWO FICIOrtC Education1 Mani SerriSa Ulf

119 1 r. culanummill3 04.002.0013 60.001 0025

1

2

b6.003 30330.001.00110.004.00160.001.00160.04401

pop d monconoucrowen summi

° 04.003.001P Soc./ I !Culli.raiC Uort ScheduleI (ms act uo rri int ri

Input I.03 . Output I, D ,

04.004.60106.001.00521.00.00160 C04.002

opooparoanoucacornommosionnums

I 02.002.0011 04 .o01 ,00;! 04.00.0051 04 .002.001

05,301.00106.00..00160.003.003

' nk 001.001

F :J,,,,,catioo,C DevItesI Inleract04. 0ortnInd1

Input I D. 0 f Output I D.

.....04.001.00,06.001.1'4106, 00; .00:

....06,006.230.005,0016n.001.00360.003.0'1

I 01.031.001I 01.001.002I 05.002.001I 06.005.001i ,6.006.0013 y0,002,0011 t..3 00 ) 00;.

60.00?.00160.002,002

=b000OM

00000000OSOMOMOO

' 111,103.oeF teopolooicat

C automatic,/ 1000o,, E,:,,,t,iity

140 I. D. 0 cxtput I.11.

115.0)1.01,;36.004,00106.005.90;06.006.01,106.306.00.,20,003.0ce10.102.01130, 0,15.040260.c11.00160.001,00:60.1102.001

OOMOMO R O0110000OEMOMOM OOMMIMMO

I 06.002.002

P Education

C Admmisoltion1 Autormtion

input E.D. o j Output i 0.

...02.002.001

..02,001.00240.002.001

OOOCOOM800000OUDOOMMOMMOM

1 (0.001.0023

3

Strategic Working Assumption #1 Resource Control

A confluence of factors will result in a significant reductionin the resources available to accomplish the NETS trainingmission. Although a current concern, the degree and scopeof resource restriction will become increasingly severethrough the mid-1980's and will result in major changes tothe NETS resource control approach and structure.

1111ra

A-1I-89


cm.....-il 40.001.001V 0111 tsry 04,ctrIneC *me/Gantt3 01,11

1404 1. D. o Output 1.D.

20,000,01120.002.003W. OC S. )0100,0105.10240.002,10163.002. 0243, C01. XI40.003.106

2 20.001,001t 30. WI 0013 XL 032. 0023 10 001.0013 30.004.0311 40.001.0022 40,001.001I 40.001.004

43.301.01660.03140!60.001.001-

a 0c00 0000000 ft*MOMOOMOMSOO

..--..-..0 )0 , 004 . 301F trenno1ovca1C 1/440,30,

t,t4r06.,;e4e.Itty

input I. D. o Output L D.

'0.000.00360.301.00440,003.001

1 06,002 0071 06.003,001I 06.003.001

04,006,00130.001.00140.301.00241,001 . 03560,001.0010-um60.001.00260. 003.00160.003.033 --.

EICUOUCCOMINICOnranimmeau30.005.00

F 9eC5nu10q1C41C 11Jtegat

I *loons I stenInput D. n Output 1.D.

05.002.00130.005.001 3

04.004,00106.002,00206.002.00306.004.00110,502. 50130.003.51140,001.04240.001.00543.063.00!60.001.001

' 1V.047.002F ,,P,Ao',d1r.d,

C ',..1, Rtd,,t cl^I , ,,!..'llty

I

0,,,,,,,t 1, P. 14 Output 1. D.

1...40.,n;1 :01

opacencomMicaIIIIIIIIIIIIIIIIIIIIIIIIIIII

1 1

1

40,001,00204.704,001ococtoci

6.002.00e.0G.',0,1

01.0;-1.6. Cf: I .00';!...01 1.001.0 0,5.00104.005.002

,'=0

1 r.i) ,01.6,11F 104,41 r,,,!: '',1,,,1,,.r.,.I %, 11C.n j1.,1W77y----,Output 1. t)

F..r,i. 4 ,.,0' I

0.543.00)I X.0( 3.001 -.2 60 .001 . D02

60 '601 00? --G

b, 4 ef011901111111111111811

aelleante

6D orooIkuroc

0 36 ...02 001F t.vcettonC '.4:N-31,cqlsa1 Change

I het:: on Cunt* tIIMMIQUENCI 0040 1. D.

54. 301.-(304.007. 0,106.10 Xi30.00,,00130.002. 0G I3i . 002 07730.001,30'60. 004,001

,Dt . 1k 2. Xi, '.03 . IV.o. .003.002

1 06,003.5013 06.306.0021 10 003.003

1

1

CI b d e oucaaGIBEE101111011111nenno111111111

4...+50.001.003

F ,oval Fa rtor ,

C id.A..st. :nI 4 arl 4104 toads

''S'put 1.0. t., Ouiput 10.

011.003.001.m06,002.001

06 003 00?30.003.001

....30 .334 . 001

.A0.005,0026. 40.003.001

2 "5.00 L .0013 na . 5:1.002 ......2 06.001.3012 Go. 005.0011

COCICILICIEMOCUE .1 §0111111111111M11111

' 30 002.041V rec.nr.olev c..1

C l'asn Peloction1 trvice

MN 1 D. Output 1.1,

05.001,0'.1133.005.00140,005 032

40.003.00

, LI 001.0623 04 304 0032 ,..6 , .,; .0011 06.302.302

04. O02. 00306.003.J0106.001,00:'03. WI. 0t.+136.006,00106.006.007

DOCIOME1011130C1114100161011111111 NNW

1.,.003.001r rf:5110304 ctillC Prrso00611 C.)0(4t,er,,6e

Input 1. D . o Output I. D.

4.305.002il ., 3C 1.00110.001.0C/

60 7,ni. 5 ,

2 0.4 . 004 , 0001 06.002.0021 06 003.002

41 .001,O0...60. 001,00160,003,00460.004.00160.004.005

a 0 11113I 2 1 11111110110000

1711111111111

0.0.,J1J1 DO?

F 51 raztoetC 1J6cucl.1i 4,I0i-Serr1c I; e

Input 1- D. u Output 1.0.

06.0u3.00330.001.00130 004 001

1..60 op! V'60.304 001

3 04.002.0013 60.001.00231

2

INOCODEICIDDOCCIDFICEO111111111111111Mil

11

------,,of . t 33. DO?

F uuc ,,,,,C wyc.1,,,,I !.,,,,,),,,,,,,I No. GrAimi.ution

Input I. D. o Output I.D..

06.307.00136.03.003L.

..30.002.00'30.303.05160.002.001

*.c 3.

b

0'2.0,',1

#71 G01

13131:11113130000CD

I2

1

21

72

06,002301te , 002.00266.501.01. +,. 004,00130,001,00160.001,002 ,r60.003.03

ICU 011111111111111111

A -Il -gO

=1:

TAEG REPORT NO. 12-1.

1 to.cal.mi

F Nara! 16cloriC 1 IvtitonI Or/ 1166 Co tr4cI 4/

Input 1.1) r. 1.)futp...1 1.11

66 006.00!.00.0'31.007

1 '4.001.002r.

GM d 0,.1

0 60 1104.00'

F 'ayes 44...c-o Iser,e6re,1 Job (orrcne f t,

lAput 1 D. 7 ,.

i

wf,fpuf 1. 1,

,,

... ,.....

an 00

OtICII34I

i g!:,

t.41.`121`: °2 2 1 1_ I 1 / 1

. tO, 00' . :-

r .1, ., .. I I, Pc,rs

C ;I'j,If it rat1 Ira ,,.., ../,!rj itAT.I.,

Input : ft ., 0./.1ru/ 1, D.

,. il i,,

'6 ''', 1, .11.''5 ,',.;.'.. , 0 '.

06.6..4 ,o' 1

06. 1-0.Or ,o ,,,

4,, (,.(1,. N..,,, rA.,1.,3 I

...a.,f f401 -,6!., J.,/ .1 ..,2161. 6/, ',.001

+4,01.2,001 -..2 4 . n1.00!...II b: ., 002 Aci ...,

-/

CIMIMINIOnerIr .111e1111CI

F /.1., 1 r

C , /nr,111c/I ,,,..,

I ;NJ)! t t ^ r n1.S.1 .

Input 1.11--,'_. /4...tpui I. D.

53 ' 'I I,%Ili .".. 0

/ 'jr il ,,

Or ,J,'1, 01,10i.',41 '10.16 1.4)2 00:'0.+,04 Or.. 1. 1

5, nN.003I.. 2n1.001' .', 3,002,, le. 003. .4 002

.. ,,6^ 9,13

NI, t ,. , k DCIallMINI

.......o 6c ..102.00F S./.1' I v.torsC ,/-.eira. and De elepeeet

1 (.40:41166e1 AEI

Input 1. D.

06.001.00106.0.1.Un'06.001.00206.302.00231...006.001

.m60,001.00'

6 0616..0 1. D.

2 04,022,0411

1 1:4.003.0d1

1 06.003 047 .

1 06.003 0032 06, 004.0011 06.006.001

10.001,00

b rj d , ono k i nnoOreille

II 10. f001,oeF 7e41 Wtiicd)C ..140e1 .Dr,ree/n F,1

I 01111 Tra',11,Cr9 Oit,

pot 1,0, Out; at .1")_..... _..__..1 C2., 11..

......:,4.00216.1-.0:1.0r.'

1 ,,E. 001, ,' l',47 4. Mt . 0'1

1., r13 .:,,-

..k. -.,-,.002..A f Q1.1101cc. :,0. OW30,004,00!0.001.002'' ,02.0014 , fi,...4. 001

MedHi '011eilli.. ,.., or.,t

. ,,,, j'..11.,11..1r,r,w' ',LA'',

/PDX 1. D...-- Oulpo 1,11_.

43.002.001 . o" .. f 4 I'0 .,10.007 ,...... 0.1 ,.:.,,

A ,.,0.1. 001,t 1'!11.003I ,i01. ',01

.., ,, ,,-; 1

..A.,1

,.3.f1.01.12

rall11111XIMINCEINsuitimollin

Strategic Working Assumption #2 Resource Distribution

The projected combination of restricted resources , tech-nOlogical change, national doctrine, and military strategywill result in a major change in the traditional distributionof resources across the military services and, also, acrossthe various commands and functions of any given service.The impact on NETS will be substantial since its missionis driven by most of the other functions within the Navy.

A-II-91


1.01.0(.1F 00114,4tfc InstitvtloelC 0440043 banter 2(111

Input I, D. o Output 1. 0.

Uan1)013COUOUCCIOUElleilliellle

01.001.03104,003.00104.004.001

1 04.00 .001F Ezuce ,o,C S1u4e t 811 11

I tern rig 201114Input 1.0. o Output I.6.

01.001.00103.007.00106.002,50106 ,006.00122.002.00160.004.002

01.001.00204.001.00300.001.00106.001.001....60.002.00160.002.002

aciatagoonouut ^ °itaieveumposes.r 06.001.002F felucetio,C StOent StithI tter414 Ability

t. D. 0 Out. I I.D.

01.00.00123.002.00306,002.00106,1013.00122,002.00160.0(4.002

3 01.001.0021 04.001.0031 ^1,001.001, 04 . 001.00

1 60.0/4.0011 60.002.002

00000UDOOODUCCCICOICHINIMMIONIIIMI

IP 17 2.001.001

F Ph 11csopl. tc4IC Re'1910n

I 410rel !elves

In I I. D. Q Output I D.173.002.00103.002.00304.014.00260 001.004

3 02.002.00104.001,00

0 04 001.0033 06.002.001

D6 006.0(112.002.00160.002.00260.004.00260.004.004

00 COUODUCOUCOCIU 2' '02111111111111111111111

1 0/.004 D01F 1,o4,41,/r.ulture1C Pultde, Wec,,,ct.,

: 0,46rilit,O,

1.4p,,1 I.D.,...... . _.........

,)t,,,,0 :,i0).22,,01.001

30. 00. . 41130 062 00110.001 MI10 .005.002

o 01.131u1 I.D._________,1 02.002.001,..1 03.003,0011 011 cm .061.6.

1 01 1101 001...2 C4.001.001...i 60.014,102..

Cle00100011110100C0MISE111111111111111111111111

1. 06.001. 03F f4ula1IOn

C b'udenl, Wit,

1 lnitrirn r2e0e) r ),

Input J. D Output 1 D

ul.01,001.11.,

,6.0,.,1

101,

T2.002.001

CCIOCCUOCUIMUCCIOUn101111111111111.111111111

00/ , aC1

307

.001

3 02.:02.001I 0.001.1011 04.002,001I 04.001.001I 04,004,1101

60.003.00100.004.002

F60, 114.664

2471,0

C 022,,nnel

Peitntii Autocrit

Input 1 1).

21.002 001(4 01!1 ,1,0204.061.004

Output I D.

1,1..3.001 .002

.)0,11.0C04.001.410171 001.00106.001.00106.000 0131

a 04.001 102F 104161,10,,Itur41C trlItu.0.I .3-4 040,s,..1,.1

Input 1

r.4.01.1,001rJ3.00. V I.1 004. 11.1A ,(01. DI')04,000.00110.001.30110.001.02,:60 0C4 CA

(put I. e.

3 02.001,00)2 03.002.0032 04.002.0011 00.002. 16.001 0012 60.002.0022 60.003.0043 60,001,002

60.0(4.001

DOCOCIUCCUMUUCOO111001,101111111111111111111111

C

a 04.001.001

F Social/0u Itur41C AtIftwdeiI 140r3 1.1,00r,once

361041 Li). C)utpA I D.

2,001.00I

06.011.00140.004,006

DemoEN,

.004.001

acconaoroaJIIIIIIIISSIIIIIII

2 '2.60I 04 001.602

60.003 60.004

60.0204.005

,.001

..1,32

002

04.001.00121c141/Cu t ,A1

Murh 3,orlulo

inVe.t en 1

Input 1 IT Output 1 D

004,7010M1.0(4.001

10.141.001

07.002.001 104 001,00?04.001.003'14.001.03100.001.00106.0,6 XI

,.21.601

mo popponaucomCC 1611101

. u2 . t,J .1101

F Pm,lc orbic.i,

C Ir%tt utorl,

1 Aut4.; ,ty

Input I. D. 0 Output I.D.22.001.00103.002.00101.002.0034 001.00104.001.002 '

04.001.0(104.003.00104.004.00166.001.00360.004.0060.001.004

2 01.001.001I D1.001.0021 60 002.00222

3

23

3

3

3

CCOCCUCCOCOUGOCIIN3000.1111.111111

0 60.001 002F .1,11,61 rectorsC 04,,surireli Witter Att tides

IICIZI121.011=11EMI02.001.001111.012.001171 ..0.1.1.004 17..04004.001. "1010.002.00104.104,00104,044.00:06 031,00306.007.0014.0013 OM

00046ut

1 02.002.0013 01.003.0013 06.001 0013 06.,101.0022 .

1

2

2

t

z

onnoticsimrmnrnommossomns

A-II-92


ONINNOMe

f 40.002.0(0

F Sire tutor.C liestirch end DoWcome4

I 1666...1,141 163

1146'..'77-..--:1r7"..,-------05.00,00I06.001.06,06.00,002Co. 1C2,01236,001,0060.001,00:

-......

2 r4.3.12.031 0.6.001 011 Of 001.01,,...1 4 00x.'0): cf 034 c.,J 06.066 V"

JU.06!Al...

COCIOLIGIDC111011C011 1 nteniaiiiiit 34.001 .00V SocsolitvIturs)

C it.titudes

I ((tea of Choice

IAN' 1 D..

u Oute.1 I D.

02.001.00103 002.0C1

64403.002.0036.04.003.001' 04.004.002

CA, Of 1.001001.001.00200 004.005

I

oggoopoononce0603MOOMMOME

2 02,081.9011 CnI 06.1)(2I 4

60.904.4161

1

I

06'2.41.:,02....

021 .001

OA .044

O 0~.,c3.00:

I to40A,-0,

( i J.. At ,nto I 'If ,)110S,,',,.;t11A)li11 ,t

input 1.0. a IMMO.'11.112.51116 03.00330 . oPe .6.)130 002,601..,) .'.), 1.;)1,0.0,1 u.r.n.st,:3 0o..;

INIIIIEJOgran_ffieranlilleillossesuillUll

1 06.002.0017 16 . SO. )121 lc. ot^ , 0,7;2 66 ON 001

1r..*1.. 014. .'1II ,,,).11' 21: On:

60.012.002F 44,41 rsoto %C Rated rch in Deer Potren t) Student Motivation

11 ot 10, O a 1p,Ii I. D.

'142.0()!.")0102.06'2.001

03.00? 00113.002.00234.101.00104.001.00205.001.0026,001.00106 001,0024.002.002Of . 0,02.00106.006.001

L1' ,..52..743

u11.102.0013 06. 213.0013

3

3

2

I

2

2

ocaoppggii,amnimnaimmossons

4. ,002 ,112Fk.3..re.,c,

C 'ennnn1111.41 Cr trge.I ..... , note,t4411

Input 1.- ._,...C4.0,2, 1,01'2,..P4 0')I t"1.1

06.0 ;.001el .!e,.., ,...02

r 1.11..,11i.'%,. 012.

3' ao0.1..10..

190011131M110fillaMO

D...-

X.1

001n^

NOSSMOOMUMN

o 0010ut 1 D.--2 Ot , Cot 0013 .10.1M,00)/ 60.002.0011 O.0C).0021

1

1

, 1

I, .3.002.663F 410-SedcalC 8,6.091..1 Cunt 63I iirPldvior 16121 ft .4 tion

Input 1.6. o Output 1 D.

04.001.20200.00.(.3100.010`2. 002

1 .11 001 ,.'1112 111 .6211.0623 02.001.001

02.002.00103.002.00104.001.003+406,001.0014.001.00206.006 001

cgocuocusgurs,soloopommillosom

f 11.001.001

F !c6,c1094ce

C; LAKEtior/Troln no

i 61111 Tfinoeratoht

put 1.0._-_-

!put I. .

------ -' -

t 4.002.0.12 06 0152.DG2

2 20.x2.06)t (A :41.r.o12 0,.. f 1.(...

1 t3.(43.1/02

16 002.002

06.001.011.001 0A2

3e.0 4.0411

o 021 ,002.00,'.Ccl

60.044.001

DelaaaanINIMORLISRESIIMO11111111111111111

0 60.004.001

F ,4,41 1,,c.tvs

c Pente,nnelI Joe r tortn, 3 i t.,

Input I.D. 1 o Output 1.D

03131111/01EXIMICIUICO111011101011011111111111111

,b eq/, 1,1I 6 .,;17,` .'.1)0.6 00.04306. 001.0613.; no,1 2,01 ...i60.' 01 110260 v)3.,.7

, 06.1 OF.001F i ItiCII ,c,C m..t1 vat! OM1 Stolent

Input Cr). n Outptt 1.10

0/.001.00103.002,001

3.002.00314.001.00340.004.004

2 J1.001.0013 01.001,0021 04.001.0011 04,001 .0022 06.043,001

06.001,10202.017.60:22.00, .0016o 002 .co,eto 11..80?

cciagoringgangsmoMrflEMMOMOOMMOSO

Strategic Working Assumption #3 Human Resource Managementand Accounting

The average recruit entering the military service in the mid-1980'swill have been influenced by the changes in national culture, attitudes,and the total pre-service education process. The changes resultingfrom these influences combined with the changing requirements ofthe services will necessitate changes in the management of humanresources, especially in those areas leading to a trained and moti-vated person capable of fulfilling their designated mission.

11111.10

A-11-93

111,..1MG

t6-II-y

pagilemis gm cuominuaraillitlicta .

200 ' t 00, '09

0 00' )0' t i011'110,, I

t 100'(00"1,0

'0'1 1^0100 Q .01'1 0nd li . 1,,,o1,9 1

,, 114,161,6c11 3 1,1t1p,r1.1 1

100'90,0 91; a

111111111 . 1113313M D3001)11X1

tw. 000.0( 1001000'99

1..... IOW ON . 000 '000'

400't00'90 100'040'90 100 400 '

90 90

to

s i 110013

t 200 00 09 4 ion'SrAi 0( 4 1 200700 90 I Z00'100'90 1 001'.1010'90 4 100 ' ' 00 50-0

(1.1 V'dWJ _

0.1 01 v.5411

Opt 1e0v114v,P3 I

1.4cdoo 0,1 put, 41,,,,se4 3 1,0221j 1100* 4

100201'09 0

11111111011111I11111110fileili

c, C3CICINECODOCEICII0

200 '400'09 200' 990 10

000`(00'01 (00'00090

t 00'200' 9V 00'100'0C

0 , 09 ' /00 0I9

I .:0620,Y09 t tt!'1' 10'09 i Hy., :-?yer 7. ,.:04'(43'9(. 2 100'000'90, I 00C '40,' it.

' )11d1 1 ' Woci

hill NiiS1+1.1, l O.% I 6.4 .111,JJ/JOI l4'.,,,r II 3

opla,0p,400, 4 100"130 01 0

1111111810 aalai na4"4P615004.t

SOU' WI '', I No 000'04

CJOA'Ai CS 1C0100'0.1

5011' 100.01 ZOOtrA '9.1

+00700'90 03' KO '10

I I( no'c 1 1,,,m'Coc'Cit I ,^0't00 ' a r ;;0 ".00 .41

'I 10d$00 101 .a 1 owur

,4,,i1,44,,,, t

I.Juvs,.4 L3

11710410.,4,al j 1,o'CLK.^C. a

MOM 1 AM/m=01.

ggessuguas osocoomannaco

, 24('

0i 00 ZOO

100 II... 100

100'003'90 100'.100.50 200'1110'17

WO'

'200'09 '200'09 100'u9

200' 00 "900 '90

1 OG' 10

I POO ' ZOO ' 09 c E0y10014..... r J30'9:0'0(.0 I e0:090*90 1 .00'000'90 1 t 0^ ' 100.7e: i .00 (CC 00

'al Indimo 0 '( 'I Int-tI '

lout,01 ,41,:edo0u1 1

Sa70,4: 3 ,w00.)1.01..00 4

; DO ' 10V5U ,

imilisomplianou

,t00' tDcCE t 00 ' 07,0 ' 90

00 'EGO'9C1

430 00c. 10

,,10,,.2)0,0 tOt,'Itr'Ut

000.000 00 iC0',0st Ci

700 94'90 7..Rr C JO '10

1111..:.,t '9"0.* I 't 0' 100 '10

'01 10O1rv0 m 1 ii,,,dui

le,,ileilavy..ig '.) i (yolomy'ai Ow01:,,,NI 3

))0111144J 4

100'0'0.90

0 SI u

1 iv. IC i ' Ill it

1 a , 1 y ;ILA

ip .,1911

VO 11, ',4 i Oq' "C 0, ...... o , ..: 1

rt 1 ,'?")

7 I'd' ,,,. 1 IX t,u,

---- ... r, '41 I 04441

.,,,41.4.4..0104,., 641.0',1.4,/, .1

$J,n...) tiny .1

',00 IA 91 .

20^'1':,'09 00'000 'Cy

Z00'000'02

L0O'COO'C: Zlq' 9"...{00' 9)0'40

1/0.030.4,

al rano 3 ir.416 ti

Al.tmaPI

V:t1r,r1r11

010:40,04 .4

130'03( '0;

1111111111111111111111111111301113

0 w 3111:10 I I' 131101X1130

( kayo( or 1 zoiviococ 1 109 ' 000 ' V.

100'900'90 0 tcotoo.ot t 00 COO 99 0' 200 ' [ 'X Pt

200100,4 ( OC TX '0.) 2 .0^ 00 '10', WO' 10' SI

, ' a 't 11d 1n9 c '(0. 1

10+Fg

s 101 aiaqpi,4 i Yeti11r03 3

J0013 114111, 4 COO 400'01 a

111111111111111111110 Otil 031113110131JOGI

00 (00 09 NT 430'90

t00t30' 90 Z00'400'90 1.0000'000'902,

NO' ZOO ' 90

1 loo i 100 0 NO t 0:10'Z i 100'100 Z ZOO

0 COO 1 000'100

P OD

px. D9

10G' 00

'ZOO 'OE

000( ' r1 coo 90

200'90 ' PO

' a I 104700 0 a 1414414

lualucr) uo inrle! I

09143 ir,15cou,7at 3 woo, ...o.i '4

ICK, 230*90 I

11111111311111101110NUE 003013oncionotootio

COO C00'09 200'000'09

ZOO 106 09 :70'100 C4

00'100'01 000'000'00 100.100'10 100'900'90 (00'00'90 100'00'90 100'200'90

I 100'000 01 1 110'I00'01 I ("O*2.10 It

. 10th 10C411

1$001a6ueulaiu1 1

svoe'.)! 3 11)1501,v4,*; A

00.1,`J CV A

L-V. 'ON Ind321


0 36.003.002

V lOuctionC iduratiunol .es.eoelagyI tosk Opt161i tier)Icizimala

I it I. a .

06.002.001461103,003$0.09r.00t)(1.002.0020.103,011

60. 002.00160.003,003

06.002,001e4.13em()206.03,00)

,u,)10.00,0)160. 0/' 1 .C1'i1.0.001.003

I3 llga greougge111a )i1O MEIN men

/...........0 00 OA./ 003

V Education

C Iouct,onal tie nu1agyI Modular Poo/ 'nit

1rias.",Trir1mlars--'DK 00.. Jo!06,001.10

...30.001.00123.002.03130.002.00211.000,001e0. 302.00i60.003 00360.004 001

7 (6.00.002I 06.004.0011 i..t. 004 .00?1 6 ...iv, .,42 .....4I 40.003.002

1

cououncoricoac,,Nairn' MHO

I 06. XI, 001r idur 0 tl G.C Poll ClAcatVnniirornnu

1 Grouts/. I', f,, man, ,

WWI 1 D. n Output 1 D.

06, DO ? . (1. riGf., 003. 3006.001,00306.006.00230.006.001

.... 60 . 002.CA1

6J.10 I .G'.'60.1/0).t.0).+

I

2

2

0130§011130DMLOCC1111 11111Es1111

4 11=1..........=,bi.11.44,,.1 I

F Sa, I, to.turs1. Fel si n/el

,:,..., Eva/An) 1 lt

.r Du..,,TrrririN.11I. br 0

1,, UQ,

1.f .,..CWX}

O. At 1 003

i ,6n1V1'1',1i ,e. .007........

'LS: Ow 00?

ti BMWA it =FM;OILER 01111=11111

' 0.0. UO3. 00,

V 611,a1 fa .tors

C EducationI CIti-Serrite Use

Input I. O. p Osalput 1. U.

OE . C33.0033u. 001.1010 0 .0T4 . owC... U)1 .W11a') 004,01

3 04.100. 0013 60.001.0023

I

2

aineagng001713E1213Rent' s'us's'' to.L.1.00

F 24111 )4(trr1

C 1+,,c a t .oet 12.,11an Conrad tors

trput I. 1). ii Output I. li.

004 . 0O1 1 611.1'11. COO,6.0.03.1)01 i

CCI cdMUMACJOGINIIMEMIMMInigainle

....

0 60.001.002P Naval NettlesC Orient tationo I1 Training tenet...Notion

11.put 1. D. o Output 1. D.

'26.001,001

Cl.g0°3.°01C323

6.004.00106.006.00130. 004.00130 . 065 .00160.001.001

t .t , 0.101, COIN._60.003,001

ClellfitlfielgODOCCIsirsnessonsese

3 ..4,002. 001

43 1600.°417.041

31

3

3

I

11

2

Strategic Working Assumption #4 Organization

Inter-service cooperation and consolidation of the training function,increased need for precise control of training resources, a need forhuman resource accounting, the thrust towards instructional modesrequir ..ng highly systematized and disciplined development, and ashift to more on-board training will result in a NETS exercisingstrong centralized control over all Naval education and training bythe mid-1980's. This increased control will be mandatory if the edu-cation-training mission is to be accomplished as currently planned.

A-11-95

96-II-V

1111111111111111111111110 ' 301013000001:113

( 000. 100'00

1 009'SO4.04

1 twroo.nr 1r..-000'000'90 (00100'90

2 100'000'0O"

0 100'101:90.9 000100'90 1 119'100'90 100'100'90 Z 000110'99

4

,

'13'1 00100 ci .1 10dvi o 50101 a91141A 1

uotykarkpl.:: 0.0999j krAlry A

400'000'09 0

1111111111111111131351113 31101110111120000CICI

' 009'900'90

'

"11'100'000'90 4..t00100'90 000'[00'90 110100'90 000'000'90

P..100'100'90 100'100'90 100400.90 0x'100'10

I 100100 09 t 1:0'110'Ut

( 100'50 00 t 110'101'10

' g 1 1119r010 --" u '13 '1 10d111

..- 1011100 1

011),Wd ksti :-,

19,10otatoay 3 00'/QC'rt

.,-

IIIIIIIII06tlti 0200UUCIE1111000 q

000'000'01 100'900'90 t.,......(0010000

00'C00'90 10014090 '111'100'000'40

t too tooll 1 '00'100'01

0 100 001'01.

t owzover t 61W0',00( o ZL,C COO 90..0 Z t'.93.100'99..1

1 100 '100 ' 91

'a' 10d111 1 9101 10 tpoJtitt 1

oty, ) tr,,b0ou4,o1 3

...,11000 3 100'100'91 0

(

0

1111111111.11,1101' IMEICIMOINICIII q

L 2(X1.200.09 00401100 /D0'100'01

t 100'21:1911 100'109'0( e tc,,-0)0.90 100'900'00 ' 6c0'rocto

m.(J0.9011 r

ixrcuoll 4 109':00,10 400'1.0'21

.....112...00oo 4.......42.1:Lq_.101 -- --4

411,,,A,00mN 1094 1

00100499j 1,9041,1mp7 3

. 0.199001 4

1001W0 , .

II 11112

5440001 VP

1,0'00'19 150'00'09 0001100'0 700100190

Zr'n 160'900'10

Sall- 110111103103 000001011111000(10

'900'09

'It1r; 90

I 00'700'09 L 100100'01 k 100'100'01

0 200'G70 CA.

1.1 1 IntLINO C al 10dv1

nal400, 1

! OUVOSJaj 11315010v4/0; 3 tOO'S00'0C 4

0111111111111111121111111 .cranoosnonoaccia

Z00'190'09 100'100'09 200100'09 .._100.00.m 00.900'90 1°0'900'90 100.100.90 I010''100.10

I00'10010

1 90010'09 f "." t 100590'01. 1 zn0'900.40 1 /0(,.1.)090 1 t(0' 100'90

t 000'200 9.)

'a 1 ink:W10 't1 9 11,d71

1t194,1: 9.11,900,1 I

,,,,on j SJ011911wWw0) 4 190'0010

,- 111111111111111111111OU1111111 1331100d01311130/11:1

... )00 ' NC' '9L,

I 100'90'09 Z 30100 1 200Z00

1 Loczw'or I too' C 200'000'90

tG0'0C

Ot.' Vt.."

1

'a'1 1001,13 0 al ma01

styk 1L119k9J1 1

aburtn 1 1 1,040,,00. a ultlIwp) A

% k290 90

stemminasazio 102110111D1111211000

, ok, , :r,.G1 .r :, '1.4

10:1' trie'Ct

100'90'90 L11f11L191 90

roc :),. .00 ilik i:,:l ..*

L10'.910 2 t00'10e 7 100' C ,./)

/ ',)(`',.'t",t'lk.

I kOf 'Ltrt t00.r.t,t,

1 070'10.'s!

44:4 'D9

' tq

'01

9.,

11111111=1111112 .t.1 I 100,4

'0,1' ',Pit% 1e 1

F501N14) 10,0111'0 I 3 ., I' '''l 1 . '110 '1 00 t' 1

aissrulani 03tICIUU0001217

100'000'09 LOo'r00'0) sivi00'Cir zoolcc'cl 100(00%

.

100100'oc 400'900'00 (00.200''90

000'000 9) 100'190'10

t 100'000'% t 100200'SC

f3 I 1001,93 p CI 1 VW 01

.1.0013's 1.11)1901 I .011,11019 3 0)16o,t4v1.1. 4 000'070'0( I

J

SINN 11 1;4 fill E191113811 0 I a P J q

100100' r 9 ZOO' 10009

100100 et 200'000'00

100'200101 ?COI cD0?

200'900'90 100 900'90

100000'90 100' ex 'V, ...IV' tt)O'Vt:

' 7 l. r70171

, CT

1..... ,)

.

al roal -,

4100:,ie-,4 ,ay.1..03 1

U011,01^* 3

1r,12.10,u.aj 4 oo'sx'or ...

S111111111131:1111 00311311300£111113DEICIO

2

200'(00.09 100'900'90

00100'90 000'0010 00'20010

100'100'09 100'000'09 400'100'09 100'900'fl

009'1J0.90 101'000'90 000'Itti'92

..3.2)042Ao 0 'a 'I Inct

Alit; J a9uPa1 0111. I

twoiedult0471JAP) 3 111.101ma;

100 1090'00

000'900'90 100100'90 900'0090 e00100'40, 030'000'n

100

ZWZO0'00

tacr,01,1 101100' PO

odino

I 100'1'50'01

c' '11 I

'ON 110d3ti 9301

/111,9,119,1 te1910094 151, a

L910010'4,04, 4 ;Ott

,

TAEG REPORT NO 12-1

21.06 .. 003F 16.cot tor.C 1.10 ot,onal oc nologyI Modular Pow tr,1

Pul_'.....1.._

2 6 , 0 0 2 : : 1 C 1

'6.00300130.001.001

0.002.00730.032.00230.0:0.0.31bn t-'?.00160,03!.0,360.004.00.

tput........____..

? 06.001.00?3 06.0(4,0011 06.006 002I F (1, 00 .00?1 30.001 0121

3

?

011300140000011119C00ventinolosanseso 03. 302.002D CoucotiouC I !Oro [Niko CP4 Mae

I (to lediklu I

Input I. D. Output L D.

06.002.00330.001,00160.0102,00160.002,002

C4,001.002(4.001.003

.002.00106.003.00210.001.00130.007.00133 002.0C 230 003.00130.006.00?

011313000012011= , ,NE10180111111111111111111111111

06.004.201F i.U....a...,,C S,u1ot,.rs3 FralloOlty

Input I.O. I n Out put I 13

O. L.01,0011.,::02.:3111

30.42.00230.00630.003.00710.0(6.00200. X6.3.003,00360.004.001

CCOCCUI3111111:11113111C0IMEILIIIIIIIIIIIIIIIIIIII

.001

2.0o1.1)

1

I

3

1

1

I

.1

1

3

1

I

, 6 .,.,1t .'. '4.

n.1111......60 001.002

F 4011 idmiCti

C Cri,1:411J,Ii

1 Tru.,1,41 lentil nr:tor,Ln put I. D. 0 Output I. D.

14.1.01 0C i6 Ct.:, 1,'32

r;, ,..33,,, .106.001,0010640.16.001Ou. 1.'4,,k 'l3...,..''',.C,Ilnr AH.11 . JObt, . Ck.' 1. 02260.031.1010e.,"31 NI

j 04. 0..72, V,17 30 001 .1(.13 60'X 6013

i3

3

1

I

NEM 111111

I.,). '02' 1,07r N,..ii s,t,r,C k, ,a N. h .1/0 Dolt LC ATOP t3 33,,4pro 4311.411,,3

Input 1 D. 1 Output I. D.

312 1J,) i . ,',1i .02.002.k.1A .002.001 3

03.1V.2 . 0024.003 . 001 3

CA . 0C1.007 1

04.001.00, 2

06 .031.0,;1Ok . 001 0(006 . c,:,7.002

r05 . 0c 1 . 0010t. LY:11.07 I

.2; X.1.0(11',4.002. Of )f.... , tit). 0(..1

rminali r,

(5..)06.002F 101 ,41.,03

C Alpur.,,,,,t1-,..3 Adya,....ci Me non% P,-, lential

Sn put 1.2.3,_

06.001'.,,01,ro,.. 50 3. 003.46.005.001

30,001 ,,X):30,062 0013.1.402 ...11:'3+3 ..(.4',.. M,1

iO rOul put 1, D-.41 "4.',1,000I L.t .001,6(1

2 06.004 00

,1

IlleMilalliing no' 14111111161=1.1111

4

I 60.0,2.001F halal talon,C Pr, ri r(111 £'6 C-0 e 1op000t

1 Nutt It on a1 IP

p''771o1 . D.

03,001.00130.001.1.00106.001.(0?

....(16.0.002X/ , EAS. 001

C0,061.0)J3

o Output I. D

2 C.4.10.2.0011 06.001.001I 36,003.002I Ct .CO 3,0032 06.304,0013 06.004.007

30.301.003

EIGNIMOUOINICCIIMM11111011111.411111

' 01.002,003F 1310-11edico1

C 01010gIcoi Coot c1

1 8t6otoor ONO 1 O tett ion

nil pu I 1.0. o Output I.D.

04.001.00201.004.001

-60.002.002

i 01,001.0012 01.001.0023 02.001.001

02.012.00103.002.00..4.001.001102.001.00106 001.00206.106 001

111311113111:11011013111CCI1131313 1111111111

06.004.001

F Iducar,onC' PoSI 4.Len3lr.n,;ranity

L Graduate r'erf.mon.

bput 1 0, n Output 1. 12.

06 .001.110106,003,002

0.06.003.02.11076 006.002

30 000.00160.002.001

I 60. 001.00 i'1 60.003.031

1

2 .

i2

I

011110=11111111111111111111

13 0100000110111 r"

Strategic Working Assumption #5 Process

The present trend towards increasing the efficiency and effectivenessof the NETS training process will continue and will be complementedby major improvements in the areas of job and task analysis. Improve-ments in these technologies will significantly increase the integrationof the training process into the actual job stream, especially in themaintenance and complex task environments.

A-11-97


APPENDIX B

MATHEMATICAL. MODELS AND DATA BASESOPERATIONAL WITHIN THE NAVAL EDUCATION

AND TRAINING COMMAND

I. OPERATIONAL DATA BASES

The following data bases represent the major operational data baseswithin the Naval Education and Training Command. Additional majordata bases, which are maintained by organizations other than CNET,such as the Enlisted Master File in BUPERS, the Navy Cost InformationSystem (NCIS), and the Resource Management System (RMS) are utilizedextensively within CNET, but are not included in this discussion.Also, special purpose data bases may exist at lower organizationallevels within CNET but because of their limited application are notdiscussed in this section. Included in this section are generaldescriptions of the following systems:

Formal Training Data System (FTDS)Training Administration System (TRAD)Per Capita Cost-to-TrainMechanized Course Cost SystemNaval Aviation Training Information System (NATIS)Mechanized Training Equipment Requirements Plan (MECTERP)Training Aids Material Automated Reporting System (TAMARS).

A. FORMAL TRAINING DATA SYSTEM (FTDS)

The FTDS consists of three files or data banks which provide toolsto manage and monitor the total Navy training effort.

1. The Master Course Reference File (MCRF) compiles Navy trainingclass and course information. Primarily it:

a. Collects and standardizes, at one central source,informatio. necessary to publish the indices andconvening date schedvles for the Navy formal schoolscatalog.

b. Provides class quotas and convening dates for theRecruit Allocation Control System (RAGS).

2. The Student Master File (SMF) is an exception reporting systemdesigned to provide timely information on Navy personnel under-going training. It also provides an automated method for

assigning the training history codes and school generatedNEC's to the Enlisted Master File.

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3. The Student Candidate File (SCF) compiles data on prospectivestudents detailed by BUPERS, to formal training schools.

B. TRAINING ADMINISTRATION SYSTEM (TRAD)

TRAD is a student and support personnel accounting system which isadministered by the Chief of Naval Technical Training (CNTECHTRA).

Personnel data is compiled at the lowest level (course, school, oractivity) to which support and trainee data is identifiable.

The TRAD input vehicle is the CNTECHTRA School/Course Report,CNTECHTRA-GEN 1500/6. The CNTECHTRA School/Course Report containsthe following data:

Identifying Data

Unit Identification CodeSchool C ')st Code

Course IdentificationDate M/Y

Student Data (By Service

Planned InputActual InputBlock InputGraduatedAcademic DropsNon-Academic DropsAcademic SetbacksNon-Academic SetbacksAverage Under InstructionAverage Awaiting InstructionAverage Awaiting Transfer

SJAP2rtfAtkAIYCitg29171

Instructor RequirementInstructor AllowanceInstructor On-BoardAdministrative AllowanceAdministrative On-Board

Average Awaiting Instruction Data (By Service Group)

Mess CooksCompartment CleanersBackloggedAll Others

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TAEG REPORT NO. 12.1

AgrAgeOn:BoarW013

Total of average under instruction, average awaiting instruction,and average awaiting transfer.

C. PER CAPITA COST-TO-TRAIN

The Chief of Naval Education and Training (CNET) has the responsi-bility for developing and maintaining cost-to-train data for Navyformal education and training. Training cost data is frequentlyrequired by inter-service committees conducting studies in personnelretention and replacement, common core training, and related efforts.Also, per capita cost serves as the basis in determining foreigntraining costs for foreign military assistance programs. In con-junction with CNO, CNET has developed a reporting system to provideinformation as to the actual cost of training.

The following cost-to-train data is reported on CNT Form 7310/1(Financial/Student Data) for each school and course:

1. Heading Entries

a. Activityb. School/Coursec. Report Year

2, Cost Factors/Student Data

a. Direct Training

1 Instructional equipment and supplies2 Aircraft3 Instructor personnel4) Other

b. Direct Support

1) Training support2) Aircraft intermediate maintenance3) Facilities major repair projects

c. Command and Staff

d. Indirect Support

31

Hospital2 Family housing

Carrier operations

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e. Staff and Instructor PCS Travel

f. Equipment

1 Capital equipment depreciation2 Aircraft depreciation3 Capital equipment maintenance4 Progressive aircraft rework5 Totals by appropriation

g. Student Compensation

1) Pay and allowances2) Travel

h. Student Data

1

2

3

4

5

6

Average on-boardTotal student weeks availableTotal student completionsAverage weeks to completeTotal attritionTotal attrition weeks.

D. MECHANIZED COURSE COST SYSTEM

The objective of the Mechanized Course Cost System is to provideuniform cost collection and reporting which can be utilized to:

1. Answer Congressional inquiries

2. Aid managers in making decisions concerning training

3. Support training budgets

4. Provide basic cost data which can be used to develop cost-of-training chargeable for military grant-in-aid and charges toDOD contractors for training.

The system utilizes costs collected under the present ResourcesManagement Accounting System (RMS) and utilizes cost codes whichfit into existing cost coding procedures. Training cost codesidentify departments, divisions, or school groups in addition todirect course cost. Cost data is grouped for certain special Fleetand short duration courses, and those where the training methodsor organizations require students from different courses to trainon the same equipment and/or in the same classes with studentsfor other courses.

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The following data is collected through the Course Cost System:

1. Work units in man-months of training

2. Military man-hours chargeable to a specific course or workfunction

3. Civilian man-hours chargeable to a specific course or workfunction

4/5. Military and civilian labor costs charged at the organiza-tional level where the services are performed

6. Materials and supplies charged to a direct course or workfunction

7. Work costs which have been contracted

8. Miscellaneous costs such as travel, printing, utilities,rents, etc., charged at the applicable level

9. Cumulative costs which constitute the activity OperatingBudget (08) expense, broken down by cost level

10. Cumulative New Obligatory Authority (NOA) expense, plusprior year charges, broken down by cost level.

The Mechanized Course Cost System is administered by CNTECHTRA.The data collected through this system forms the basic input tothe Per Capita Cost-to-Train Report which is compiled by CNET.

E. NAVAL AVIATION TRAINING INFORMATION SYSTEM (NATIS)

NATIS consists of the following six modules:

1. In-Flight Training Information Subsystem (IFTIS) provides dataon individual student flow, student performance, instructorperformance, and pipeline flow and control. These data areutilized to manage large groups of Student Naval Aviator's(SNA's) and Instructors Under Training (IUT's) to achieve moreuniform grading, and to provide the Naval Air Medical Institutewith source data for their research program supporting thetraining of student aviators.

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2. Student/Instructor Control and Reporting Subsystem ( SICARS),which has been renamed Personnel Data Base Application(POBA), is used to control the personnel factors relativeto naval air training. Entries and modifications to theIFTIS master file are accomplished through the SICARS system.

3. Individual Flight Activity Reporting System (IFARS) is anoperational system used by the Navy to report on flightactivity.

4. 3M-Aviation Statistical Data (3M-ASD) represent thecomposite information taken from the IFARS data.

S. The Bunker-Ramo-700 (BR-700) is an off-the-shelf applicationof equipment to speed the flow of information relative tomaintenance requirements and assets within the squadron, whileat the same time allowing random access of information relativeto maintenance problems.

6. UDAPS/MIZDO are supply applications to provide information onparts inventory and to control such inventory.

With the exception of IFTIS and SICARS, each of the modules representindependent data subsystems and are not combined at the system level.

F. MECHANIZED TRAINING EQUIPMENT REQUIREMENTS PLAN (MECTERP)

MECTERP is an automated system established in 1970 to enable CNATRAtraining activities to report their technical training equipment(including general purpose electronics test equipment) and trainingaids material requirements information. The system supports trainingmaterial support requirements for aviation training activities underCNTECHTRA.

G. TRAINING AIDS MATERIAL AUTOMATED REPORTING SYSTEM (TAMARS)

TAMARS was established in 1966 to enable education and trainingactivities to report training aids material requirements information.The system is operated by CHNAVTRASUPP.

II. DATA BASES UNDER DEVELOPMENT

Effort is currently underway to consolidate, centralize, and improve manyof the existing information systems within CNET. The plan for the develop-ment of a common Navy education and training data base is detailed in theAutomated Data System Development Plan for the Naval Training InformationSystem (NAVTIS). Brief summaries of several of the NAVTIS modules which

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represent potential data sources for the mathematical model develop-ment phase of the Design of Training Systems project ure included inthis section.

A. NAVAL AIR TRAINING COMMAND MANAGEMENT INFORMATION SUBSYSTEM (NATIS)

NATIS, using the Data Base Management System concept, will providea common data base to support the following Naval Air TrainingCommand (NATRACOM) areas:

1. Planning

An interactive simulation model, similar to the existingIntegrated Facilities Requirements System (IFRS), will bedeveloped to support three basic planning functions: (1)determine asset requirements; (2) predict short-rangesystem performance; and (3) determine mission impact ofunprogrammed changes.

2. Personnel

Existing applications are being revised anti files expandedto provide a data base which can be utilized to account forand control personnel resources, as well as interface withthe BOERS personnel system.

3. Training

Existing applications are being redesigned and data filesexpanded to develop a system which will

a. Provide feasibility for computerized scheduling ofstudent training

b. Provide detailed information on student status

c. Provide detailed data relative to instructor grading.

4. Maintenance

The system will aid in scheduling a dynamic maintenanceworkload.

5. Resources Management

The system must be designed to interface with the CNET standardfinancial and accounting system.

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6. Supply

Applications should be developed to supplement the standardNavy UADPS-SP.

The preceding system description represents a long range NATRACOMgoal. Only the personnel and training objectives are currentlybeing pursued.

B. NAVY INTEGRATED TRAINING AND RESOURCES ADMINISTRATION SUBSYSTEM(NITRAS)

NITRAS is designed to consolidate two existing training systems,FTOS and TRAD, and to establish interfaces with the followingexisting systems of other major commands:

1. Manpower and Personnel Management Information System (MAPMIS)

2. Recruit Allocation Control System (RACS)

3. CNTECHTRA RMS Cost Accounting System

4. Computer Managed Instruction System (CMI).

C. MILITARY PERSONNEL INFORMATION SUBSYSTEM (MILPERSIS)

MILPERSIS will be implemented to provide the required militarypersonnel accounting information for pipeline management.Accurate student population data which will be responsive tothe requirements imposed by higher commands will be maintainedon a daily cyclic basis.

D. CENTRALIZED TRAINING MATERIAL MANAGEMENT SUBSYSTEM (CENTRA)

CENTRA will consist of the following primary data bases:

1. Activity

Identifies all training activities by title and location andcontains data related to budget support.

2. Course

Identifies each course by title, catalog number, and locationand contains data necessary for budgeting and planning.

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3. Material

Contains approved training material allowances and inventories;maintains projection of requirements for seven out-years.

4. Trainer Material Support

Consists of information to identify material shortages on NavalAir Maintenance Trainees (NAMT) and to provide inventory andbudget information.

III. OPERATIONAL MATHEMATICAL MODELS

A comprehensive survey of computerized mathematical models related tomanpower and personnel management, with emphasis on Navy operationalmodels, was receQtly compiled by the Naval Personnel Research and Develop-ment Laboratory.' All models were classified into one of two generalcategories: Manpower Management which involves determining, forecasting,planning, and programming manpower requirements necessary to accomplishthe mission of the Navy; and Personnel Management which embraces budgetingfor acquiring, training, controlling, and forecasting the personnelinventory in filling authorized programmed billets. All training relatedmodels are therefore included in the Personnel Management classification.Of the total 101 Navy models reviewed by Hutchins, 50 were classified asPersonnel Management models. Two subdivisions within the PersonnelManaciement category are specifically related to the training function.Included in the category Active Inventory Maintenance are those modelswhich deal with career pipelines, including the estaMishment and opera-tion of special training schools. Training requirements is one of severalfunctions included in the Policy Alternative Generator category. Atotal of seven training related models were identified within the abovetwo categories. These models address such topics as training require-ments, occupational data analyses, selection criterion impact on train-ing costs, and school assignments. In addition to these seven models,two additional models, which were classified as Manpower Managementmodels by Hutchins, deal with training related activities. STAPLAN(Status-Time-Attrition Planning) is used within BUPERS to develop Class"A" school requirements, and IFRS (Integrated Facilities RequirementSystem) is being developed by CNATRA to assess the impact of changesin pilot training rate requirements. Of the above nine training models(six reported to be operational, three are being developed) only one,IFRS, falls under the domain of CNET. The remaining eight are utilizedeither within BUPERS or at the Naval Personnel Research and DevelopmentCenter. The net conclusion is that there are no operational mathematical

1Hutchins, E.

Management:

S. Jr., et al., Computer Models for Manpower and Personnel

State of Current Technology, as ing on, D. .: Navai Personnel

Research and opment Laboratory, April 1973, (TR 73-25).

'AEG REPORT NO. 12-1

models within CNET. This conclusion was verified by an independentsurvey conducted by the IBM Study Team in conjunction with Phase I ofthis project, Appendix D notes the activities/locations which weresurveyed.

Although not directly related to any of the candidate modeling areasidentified in Section VII, brief descriptions, including input andoutput variables, of the nine models identified in the Hutchinsreport as models related to Navy training, are included in this Appendix.Output data generated by these models represent an additional source ofinput data for models selected to be developed during Phase II of thisproject.

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MODEL NAME

Status-Time-Attrition-Planning (STAPLAN)

COMPUTER

IBM 360/65

COMPUTER LANGUAGE

FORTRAN III

MODEL DESCRIPTION

STAPLAN examines the projected inventory of the U.S. Navy enlisted force(by rating) for a period of seven years in the future and compares theinventory status with the future requirements for petty officers (E4through E9). Based on this comparison, flow requirements are calculatedto provide, on the most efficient basis, necessary candidates for eachrating for advancement to E4. STAPLAN optimizes on this single criterion,producing candidates for E4, and optimizes in the sense that it selectsa preferred alternative of a fixed set of three alternative methods ofproviding input to a rating. The flow requirements produced by the modelare balanced with expected recruit training output. Based on physicaland policy constraints, the flow to each rating is further subdividedinto school and on-the-job pipelines.

MODEL INPUTS

Forecasts of fixed gains, losses, and reenlistments; accessions, advance-ments, and losses necessary to maintain each of the nine paygrades atrequired levels on a monthly basis.

MODEL OUTPUTS

Lists imbalance between projected inventory and projected strengthneeded. Input and training are then adjusted to compensate variance(i.e., flow rates for each rating to OJT or "A" school training pipe-lines are determined by the model).

STATUS

Operational (to be replaced by RIO, a model being developed within theAOSTAP system).

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MODEL NAME

Recruit Input Optimization Model (RIO)

COMPUTER

IBM 360/65

COMPUTER LANGUAGE

FORTRAN

MODEL DESCRIPTION

The RIO model optimizes the number of recruits input to a rating duringa time period by minimizing a function of the number of recruits. Themodel expresses the costs of various recruit allocations. The RIO modelis being developed to replace the STAPLAN model currently performingthese functions in the ADSTAP system. In the development of the RIOmodel, attention has been given to a continuous optimization functionwhich employs five criteria for selection, with provisions for weightingand discounting weights over time. This will permit better analysis ofnew accession resources.

MODEL INPUTS

Petty officer "requirements" /rating distribution over length of serviceof those advanced to paygrade E4.

MODEL OUTPUTS

Forecast of optimal recruit inputs by rating, for future time periods.

STATUS

Under development within ADSTAP system.

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MODEL NAME

Integrated Facilities Requirements System (IFRS)

COMPUTER

GE-635 (time-sharing)

COMPUTER LANGUAGE

FORTRAN IV

MODEL DESCRIPTION

This model simulates management decisions by computing logistic support,facility requirements, and costs needed to achieve the desired annualpilot training rate.

The long-term objective of IFRS is to develop an operational system thatcan be used by the Navy to determine the optimum economic utilization ofits facilities for specific pilot training rates (PTR's), trainingsyllabus (MODE), and percentage (MIX) of pilots trained for jet, prop,and helo aircraft. More specifically, IFRS is designed to provide anoperating system to allow the Chief of Naval Air Training to determinemore quickly and precisely the changes in both the total Navy militaryconstruction budget and total Naval Air Training Command system cost whichmay result from changes in PTR, MODE, and MIX of pilots trained.

MODEL INPUTS

MODE - training sequence (prop, jet, or helo), specific content and dura-tion of each training phase (primary, basic, and advanced)

PTR - the annual pilot training rate (assumed constant throughout theyear)MIX - the proportion of pilots trained for jet, prop, and helo aircraft.

MODEL OUTPUTS

Logistic support requirements by phase of training; logistic supportrequirements by base; runway and OLF requirements; facility requirements/assets/deficiencies/excesses; aircraft and facility investment costs;O&M costs by station.

STATUS

Under development.


MODEL NAME

U.S. Navy Computer-Assisted Recruit Assignment Model (COMPASS)

COMPUTER

CDC 3600

COMPUTER LANGUAGE

FORTRAN

MODEL DESCRIPTION

Given the properties of up to 2500 recruits from each of the three NavalTraining Centers and school quotas for up to 91 different school types,this model assigns all recruits to formal schools or general duty suchthat the following assignment objectives are successively optimizedsubject to given enlistment guarantees and constraints imposed by pre-vious optimizations: (1) maximize quota accommodations, (2) minimizetransportation costs, (3) maximize accommodation of interviewerrecommendations, (4) maximize the selection - relevant area aptitudescore, and (5) maximize adherence to BUPERS distribution specificationsregarding the assignment of lower mental standard personnel to variousGENDET apprenticeships.

MODEL INPUTS

School quotas; priority level; share distribution values, test scores;interviewer's recommendations with associated level of importance;transportation costs.

MODEL OUTPUTS

Recommended disposition of each recruit; management reports.

STATUS

Operational.

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MODEL NAME

Computerized Advance Personnel Requirements Information System - Billetand Inventory Subsystem (CAPRI - B&I Subsystem)

COMPUTER

IBM 7080

COMPUTER LANGUAGE

COBOL

MODEL DESCRIPTION

This model has six subsystems: Planned Requirements, Approved Requirements,Selected Requirements, Inventory of Personnel Training, On-Board Inventory,Training Plan Computations and Output Reports. Together these modules mapthe management of personnel subsystem development and production. TheBillet and Inventory subsystem continues to function during both the develop-ment and production phases of a personnel subsystem life cycle. During thedevelopment phase, it is used to produce projected time-phased personneland training requirements. In the production phase, it produces currentand projected on-board personnel status reports for use in evaluation ofweapon system operational readiness and for any reprogramming required.

MODEL INPUTS

Planned requirements; loss factor development input parameters; TrainingProgram Plan - processing options and "C" school data; Training PlanProgram - input data parameters; Training Plan Output Options.

MODEL OUTPUTS

Complete Training Plan detail; required training input; projected on-boardstatus; billet requirements; output parameters.

STATUS

Reported operational.


MODEL NAME

Computerized Occupational Data Analysis Program (CODAP)

COMPUTER

IBM 360/65, IBM 370/155

COMPUTER LANGUAGE

FORTRAN, ALC

MODEL DESCRIPTION

CODAP is a series of about 23 programs used to manipulate and display taskdata and other related items garnered from questionnaires administered topersonnel in selected occupational fields.' CODAP is executed under thedirection of an occupational analyst for the purpose of describing,evaluating, and structuring jobs in a hierarchy. The heart of the CODAPsystem is a technique for clustering individuals beginning with those per-forming the most similar jobs and progressing toward larger groups atlevels of decreasing homogeneity. An assortment of data processing toolsis provided for sorting, ranking, and statistically analyzing certain dataon user selected groups of individuals. Use of CODAP leads to improvedmanpower utilization in the areas of classification, assignment, andtraining.

MODEL INPUTS

Background data on person completing questionnaires; time spent on.varioustasks; how various tasks were learned; equipment.

MODEL OuTPUTS

Successive groupings of people based on similarity of jobs performed;various rankings of and statistic: on, responses of selected groupsof personnel, e.g., time spent on various tasks, personal history data,method of acquiring skills, and measures of job satisfaction (NAVY),job descriptions; regression analysis for one dependent and up to 34independent variables.

STATUS

Operationai within USAF and USMC; to be implemented within Navy,

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MODEL NAME

Cost of Attaining Personnel Requirements Model (CAPER)

COMPUTER

CDC 3800, RCA 301

COMPUTER LANGUAGE

FORTRAN

MODEL DESCRIPTION

Using cost and empirical frequency data provided by the user, the CAPERmodel determines the following 11 estimated values for the ordinary orexisting strategy, and for an experimental recruiting/selecting strategyat each possible cutting score on the selection test: Number recruited;number accepted; number of erroneous acceptances; number of erroneousrejections; costs of recruiting; cost of selection; cost of induction;cost of training; cost of erroneous selection decisions; total cost;and total cost per graduate. Therefore, the CAPER model determines anoptimal recruiting-selection strategy for minimizing the estimated totalcost of recruiting, selecting, inducing, and training a sufficient numberof persons to meet a specified quota of satisfactory personnel.

MODEL INPUTS

Quota for graduates; base rate; proportion of graduates plus failuresqualified at cutting score; personnel costs.

MODEL OUTPUTS

Cost consequences of alternative recruiting-selection strategies.

STATUS

Being developed at NPRDC.

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MODEL NAME.

Nuclear Power Training Input (9901 Model)

COMPUTER

IBM 360/65

COMPUTER LANGUAGE

FORTRAN IV

MODEL DESCRIPTION

This model encompasses the computational procedures involved in planningthe recruit input and flow patterns necessary to establish quotas forstudents for the Basic Nuclear Power Class, Class "C", that will befilled in the future. The model provides a five-year projection run whengiven the necessary NPS class convening dates and planned class sizes.The model considers quota requirements of the "C" school in each quarterand determines the number of men needed in each of eight preparatorylevels of the normal inventory flow to meet these quotas. Appropriateattrition rates are applied to each of these levels as the inventory isaged over 22 quarter-length time periods. The levels considered by the

model include: Class "C" school in, "C" school ordered, Fleet pool (4-6 months), Fleet pool (0-3 months), "A" school graduates, "A" school in,recruit out, and recruit in.

MODEL INPUTS

Baseline inventory - specified by current level attained with the training

route. Attrition rates determined from statistical analysis of historicaldata. Descriptive material.

MODEL OUTPUTS

The following information is provided for each of the training levelsdescribed for each of the 22 quarters projected by the model: "C"

school required; "Cu school quota fill rate; ASO personnel; PSIpersonnel, ASE personnel, RI personnel; Fleet pool; attrition expected;recalculations of required recruit input.

STATUS


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MODEL NAME

A Network Flow Technique for Optimizing Personnel On-Board by Paygrade

COMPUTER

IBM 360/50

COMPUTER LANGUAGE

FORTRAN

MODEL DESCRIPTION

The model considers the present number of personnel on-board at each pay-grade of a rating and will attrite and advance them realistically infuture time periods. The future allocation of personnel among paygradesis optimized for a five-year period relative to the paygrade requirementswithin the constraints of predicted personnel attrition, advancements,reductions in grade (demotions), and the non-petty officer base. Thus,under the assumption that it is equally important to meet requirementsas closely as possible at each paygrade, the model will select the bestadvancement policy. Such an ability to optimize is a major feature ofthis model, which enhances the capability and flexibility planners wouldhave in their effort to match inventory to requirements.

MODEL INPUTS

Baseline Personnel Inventory for a given rating; billet requirements forthat rating; attrition rates by paygrades; test taker rates for advance-ment exams by paygrades; test passer rates.

MODEL OUTPUTS

Initial status of manpower variables - and predicted inventory flowrates (e.g., attrition rates); Requirements-Inventory comparisons foreach of the out-years by paygrade; Percent of requirements met for eachof the out-years by paygrades.

STATUS


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APPENDIX C

BIBLIOGRAPHY

I. INTRODUCTION

This bibliography represents a very tentative and subjective judgmentof the literature most relevant to the Design of Training SystemsProject. It covers an immense area, including mathematical modelingtechniques and applications related to training, a variety of topicsunder the broad heading of educational technology, and a listing ofNavy instructions related to education and training.

Annotations are provided for all items included in the bibliography.Most of the annotations represent objective reviews of the literature;many are simply abstracts composed by the author or publisher. Several

of the annotations are critical, pointing out virtues and faults ofthe document at hand.

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II. MATHEMATICAL MODELING TECHNIQUES

This section consists of a representative sampling of mathematicaltechnique descriptions and of technique applications in the areasof education and training as well as manpower and personnel manage-ment. The literature has been classified by modeling technique.Major classifications include:

o Linear Programming Applications

o Network Flow Models

o Linear Regression Models

o Markov Models

o Mathematical Analytic Models

o Simulation Models

o Model Surveys

A. LINEAR PROGRAMMING APPLICATIONS

By far, the largest contingent of papers representing modelingtechnique applications falls in the area of linear programming.Linear programming is an optimization technique in which theexpression of system performance (the objective function) to beoptimized is expressed as a linear relationship of the systemvariables. In addition to descriptions of applications of thesimplex linear programming technique, this section also includesarticles describing applications of modeling techniques closelyrelated to linear programming such as goal programming, integerprogramming, transportation algorithm, assignment problems,dynamic programming, and scheduling problems.

Harden and Tcheng [1] discuss the application of linear program-ming to the classroom utilization/scheduling problem. Theresources available for scheduling are the classrooms andlaboratories; the constraints considered are the course loaddemands and classroom capacities. The objective is to deter-mine the minimum number of course sections which satisfy all

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constraints. The model assumes that faculty preferences andavailability provide no effective constraints. A schedulingalgorithm developed by Shoeman and Bhaumik [2] considersstudent and faculty day and time preferences, faculty locationpreferences, and previous preferential treatment of faculty inaddition to the above variables. The objective of this formu-lation is to schedule all classes within specified constraintswhile maximizing either student or faculty preference achieve-ment. Lawrie [31 describes constraints to the scheduling prob-lem in terms of departments, groups of pupils (i.e., all thepupils in the first or other year of the school), and layouts,which are statements of the curriculum and its organization fora group of pupils. A variation of Gomory's Method of IntegerForms is then applied to a rather complex arrangement of manylayouts to arrive at a schedule permutation which meets allspecified requirements. Of the three scheduling algorithmsexamined, Lawrie's integer programming approach was by farthe most complex and, by his own admission, difficult toimplement. A generalized scheduling algorithm incorporatingthe best points from the many existing techniques, and appli-cable to most Navy training schoolhouses, should be investi-gated for feasibility and potential benefit to the trainingorganization.

Another variation of the linear programming technique docu-mented in this section is goal programming [4,5,6]. Allthree articles utilize goal programming to study problems inthe manpower planning arena. Charnes [6] examines the impli-cations of utilizing training as an alternative to recruitment(in the civilian job market) and job transfers in order tomeet specified goals. Patz's [4] stated goal is to managehuman resources based upon a sound understanding of the struc-tural, policy, and behavioral variables of the organizationbeing considered. His goal programming formulation of theproblem solves for the procurement rate, the retention rate,and the overages or underages by level necessary to maintaina steady state flow of people through a specific structuregiven a set of promotion policies, a set of continuationpolicies and a set of attrition rates. The technique issufficiently general that with slight modification it couldbe utilized at an aggregated level within the Navy trainingcomplex.

Dynamic programming is an optimization technique which testsa series of interrelated decisions. The objective is todetermine an optimal policy for the entire sequence of deci-sions. Although Alper, Armitage, and Smith [7] propose adynamic programming formulation to optimize alternate deci-sion sequences which must be evaluated in the course of plan-

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ning an educational system at the national level, the varia-bles and relationships presented are too vague and ill-definedto be of practical use. Bellman (the father of dynamic prog-ramming) [8] presents a dynamic programming solution to amultistage decision process in which the constraints consti-tute classes of alternatives whose boundaries are not sharplydefined. Bellman's treatise is mathematically oriented andrepresents a first attempt at constructing a conceptual frame-work for the theory of decision-making in a "fuzzy" environment.Two Navy personnel system models utilizing dynamic Programmingare described in 9 and 10. Both models, the former con-cerned with the establishment of advancement policies forpetty officers and the latter addressing the personnel dis-tribution function, were developed at the Naval PersonnelResearch and Development Center at San Diego.

Fox, McCamley, and Plessner [11] use a transportation model toallocate college faculty among courses and between courses,research, and administrative activities, while Lt. CommanderAndrilla [12], when faced with a similar situation in theassignment of Naval officers, stops short of recommendingthe adaption of an optimization process. Andrilla presentsa case for the automation of the massive data handling taskassociated with officer-billet matching. In item 13,researchers have formalized the decision criteria on which theenlisted personnel assignment process is based. An optimiza-tion process is utilized in CADA (Computer Assisted Distribu-tion and Assignment) and assignments are made based on optimalvalues for specified decision criteria. Three variables areoptimized in CADA -- utility (value of man to billet), desir-ability (value of billet to man), and cost. As in CADA, King[14] also attempts to predict the result of the assignment andthen include this prediction in the actual optimization proc-ess. All that is required for the application of King'sStochastic Assignment model using maximization of the jointprobability of success as the criterion, is a set of teststhat can be used to predict performance along with pastexperience on which to base parameter estimates.

Eastman and Kortanek [15] apply a combination of the Markov processand the linear programming technique to the problem of generatingrequirements for community schools. Variables considered are themix of housing designs and their sequence of construction. A

description of how linear programming can be used to analyze theeffects of different personnel policies on organizational manpowerflows is contained in 16. A less sophisticated technique is usedin the Policy Planning Program (POLIP) of the ADSTAP System toaccomplish nearly identical objectives related to Navy force structureplanning.


Sengupta, in his discussion of stochastic linear Programmingoffers a theoretical discussion of the stability in terms ofvariance) of optimal solutions when the parameter space (coeffi-cients of the objective function and constraints), defined in termsof probability functions, is allowed to generate a sequence ofoptimal solutions. The article points out the difficulties encoun-tered in application of this technique as a result of approxima-tions involved in estimating the distribution of the objectivefunction.

The total modeling process, from problem description to modeldevelopment, analysis, and implementation, is discussed in 18.The example used to illustrate the modeling process develops alinear programming model to design a teacher salary structure.

Willingham [19] formulates the problem of determining school capa-cities as a linear programming problem based on facilities, instruc-tors, course content, and specified throughput. An annual schedulefor the optimal number of convenings of each course is then devel-oped and its feasibility verified. A variation of this approachwill be investigated to determine its applicability to the schoolcapacity and resource allocation areas identified in Section VII.

A macro-level approach to manpower planning is discussed by Maki[20). The model, which is mathematically similar to a recursiveprogramming model, is designed to serve as a framework for coor-dinating several aspects of labor-market analysis.

Thelwell [213 and Henderson and Schlaifer [22] both present brieftutorials on the technique of linear programming. Thelwell'sobjective is to evaluate linear programming and multiple regressionas alternate techniques for determining manpower requirements. Heconcludes that the analysts' objectives and the application itself,rather than the technique, should determine which technique to usein a given situation since neither is universally superior to theother. Item 22 concentrates on a series of hypothetical exampleswhich exhibit a range of application areas for the linear program-ming technique. McNamara [23] presents a synthesis of literatureon the application of mathematical programming in educational plan-ning. His major conclusions are that most applications have beenat the macro-economic level and that the lack of communicationbetween educator and O.R. specialists has impaired the utility ofmathematical models in the educational arena.

I HARDEN, W.R. and TCHENG, M.T., Classroom Utilization Planning by.Linear Prograrving. Normal, Illinois: Illinois State University,Office of Academic Planning Educational Sciences Section andAssociation for Institutional Research, Atlantic City, New Jersey,November 8-10, 1972.

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This paper presents a linear programming formulation of the class-room utilization problem at Illinois State University. The objec-tive of the study was to determine the feasibility of accomodatingthe projected course load with existing classrooms under presentscheduling time frames. No change in time frames was required.Similar to other LP applications on same type of problem. theresults, in this case, were actually applied to a real situation.

2. SCHOEMAN, M. and BHAUMIK, G.,'A Class Scheduling Model and Algor-ithm. Austin, Texas: Project GUM, Phase III, Graduate School ofSUFTness, University of Texas, December 1968, WP 70-30.

This paper describes the use of the transportation algorithm toschedule university classes. The routine integrates the informa-tion provided by an analyses of student flow and faculty andfaculty availability into a workable plan of course offeringsinvolving day, room, and time assignments.

3. LAWRIE, N.L., An Integer Linear Programming Model of a School Time -tabling Problem. United Kingdom: University of Strathclyde,Department of Operational Research, March 1969.

Earlier papers have defined the input requirements of a program fortimetabling in terms of a list of lists of items, each item being ateacher, a class or set, a classroom, or a piece of equipment. Thispaper describes an approach based on larger items of departments,groups of pupils (generally year groups), and layouts. The problemis given an integer linear progranlning formulation, and computa-tional methods used in obtaining solutions are discussed.

4. PATZ, A.L., Manpower Flow Problems and Goal Programming_Solutions.Cambridge, Mass.: Alfred P. Sloan School of Management, MassachusettsInstitute of Technology, January 1969, Report No. 366-69.

A goal programming version of the standard linear programming model,

is a mathematical technique which provides a method for simultaneouslyconsidering a large number of management goals and some of the struc-tural, policy and behavioral variables related to these goals. Themodel focuses attention on promotion, continuation, retention, andattrition problems and forces some explicit formulations necessaryfor the resolution of these problems. The goal programming modelsolves for the conditions necessary to attain and maintain a steadystate personnel flow through an organization.

5. CHARNES, A., COOPER, W.W and NIEHAUS, R.J., A Goal ProgrammingModel for Manpower Planning. Pittsburgh, Pa.: Graduate Schoolof Industrial Administration, Carnegie-Mellon University, December1967, Management Science Research Report No. 115.

A goal programming model is formulated for guiding and controllingmanpower planning at the level of the Office of Civilian ManpowerManagement of U.S. Navy. Markov elements are used to trace throughthe effects of initial and subsequent personal commitments and


budgeting constraints, personnel ceilings, etc., and form partsof the total multi-dimensional goal considered. Further exten-sions will include training, environmental factors, etc., afterclarification is secured concerning the pertinence of such a lineof development.

6. CHARNES, A., COOPER W.W., and NIEHAUS, R.J., A Generalized Net-work Model for Training and Recruiting Decisions in ManpowerPlanning. Pittsburgh, Pa.: Graduate School of Industrial Admin-istration, Carnegie-Mellon University, May 1970, ManagementScience Research Report No. 206.

This paper represents an extension of a set of models for man-power planning which utilize goal programming mathematics withembedded Markov processes. The author develops an analyticalmodel which examines internal training possibilities as alter-natives to recruitment and job transfers in order to meetspecified goals. This allows coordination of "career management"and "manpower planning" by allowing for possible variations inmanpower mixes and trade-off possibilities in recruitment, trans-fer, and training. This is accomplished in a context that con-siders constraints such as financial budgets, supply and recruit-ment limitations imposed by policy or the environment, andvarious limitations on training facilities.

7. ALPER, P., ARMITAGE, P.h., and SMITH, C.S.,"Educational Models,Manpower, Planning and Control." Operational Research Quarterl1,Volume 18, No. 2.

This paper describes the setting up of models of the educationalsystem and their use in decision making. The methodologicalproblems of planning and controlling a large socioeconomicsystem, such as education, are discussed.

8. BELLMAN, R.E., and ZADCH, L.A., "Decision-Making in a Fuzzy Environ-ment," Management Science, WO), December 1970.

By decision-making in a fuzzy environment, is meant a decision proc-ess in which the goals and/or the constraints, but not necessarilythe system under control, are fuzzy in nature. This means that thegoals and/or the constraints constitute classes of alternativeswhose boundaries are not sharply defined.

An example of a fuzzy constraint is; "The cost of A shouldnot be substantially higher than a," where a is a specifiedconstant. Similarly, an example of a fuzzy goal is; "xshould be in the vicinity of xo," where xo is a constant.The italicized words are the sources of fuzziness in theseexamples.

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Fuzzy goals and fuzzy constraints can be defined precisely asfuzzy sets in the space of alternatives. A fuzzy derision, then,may be viewed as an intersection of the given goals and constraints.A maximizing decision is defined as a point in the space of alternatives at which the membership function of a fuzzy decisionattains its maximum value.

The use of these concepts is illustrated by examples involvingmultistage decision processes in which the system under controlis either deterministic or stochastic. By using dynamic prog-ramming, the determination of a maximizing decision is reducedto the solution of a system of functional equations. A reverseflow technique is described for the solution of a functionalequation arising in connection with a decision process in whichthe termination time is defined implicitly by the condition thatthe process stops when the system under control enters a speci-fied set of states in its state space.

9. MOONAN, W.J., and COVHER, M.H., A Com puter Program for the Deter-mination of an Optimal Advancement Policy for Petty Officers: ADynamic Programming_Approach. San Diego, Calif.: U.S. NavalPersonnel PesearCh-Aetivity, May 1966, SRM 66-31.

An important function of personnel planners in BUPERS is concernedwith the establishment of advancement policies of petty officers.This report describes the details of a digital computer programwhich will permit the determination of the optimum advancementpolicy for a rating for one time period. This program will assistthese planners in performing their tasks more effectively. Thebackground material, flow charts, operating procedures, and illus-trative examples are provided. The method of optimization used isknown as dynamic programming.

10. THORPE, R.1)., and CONNER, R.D., A Computerized Model of the FleetPersonnel Distribution System. San Diego, Calif.: U.S. NavalPersonnel Research Activity, February 1966, SRR 66-13.

This report describes the development and operational test of a

computerized personnel distribution model designed to simulatethe distribution functions of the Enlisted Personnel DistributionOffice (Pacific) (EPDOPAC). The model consists of the Sort-Matchmodel, which is designed to screen personnel made available toEPDO by HUPERS, and the Quota-Determination model which allocatesto the type commands those personnel who are not assigned by theSort-Match model.

The report also describes other current research concerned withpersonnel assignment, prediction and policy-testing techniques,and personnel rotation.

FOX, K.A., MCCAMLEY, F.P., and PLESSNER, Y., Formulation of Manage-,ment Science Models for Selected Problems of College Administration.Ames, IoWa: Iowa State University for the U.S. Dept. of Health,Education and Welfare, November 1967, Final Report, Contract No.OEC-3-6-068058.

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lnis paper deals with optimum allocation of teachers in a two-level system. By the authors' definition, a tao-levei systemone in which the teacher's duties consist of classroom instructionand research. Three models are presented, none of which is an"applications" model.

12. ANDRILLA, J.J., LCUR., "A Computer Assisted Officer AssignmentSystem," Naval War College Review.

In a recent issue of the Naval War College Review, Capt. G.H.Lewis advocated the need for automating the niTiT officer selec-tion and promotion system. As a sequel to that work, the authorevaluates the existing officer assignment system and argues thecase for automation. Decisionmakers in the present system aresimply overloaded with raw personnel and billet data, and pres-sure is building that will, of necessity, lead to a better way- a computer assisted assignment system.

13. WHITEHEAD, R.F., SUITER, R.N., and THORPE, R.P., The Developmentof a Computer Assisted Assignment (CADA S

for Navy Enlisted Personnel. San Diego, Calif.: Nava Personneland Training Research Laboratory, August 1969, SRM 70-1.

This report describes the development of a computerized system toassist Navy personnel managers in carrying out the functions assoc-iated with the distribution and assignment of enlisted personnel.The Computer Assisted Distribution and Assignment System (CADA) willbroaden the range of assignment alternatives for each man and billet,expand the number of decision criteria considered, and be more res-ponsive to changes in the personnel and operational situation.Although designed for use in a decentralized distribution officeenvironment, the system can be easily modified to operate effi-ciently in a centralized distribution function.

14. KING, W.R., "A Stochastic Personnel-Assignment Model," OperationsResearch, 13(1), January-February 1965. This paper was presentedat the 1964 CAS/ORSA Joint Conference in Montreal, Canada inMay 1964.

Personnel assignment decisions involve performance prediction ofjob success using test results, etc., and the determination ofoptimal allocations of individuals to jobs. A model is developedthat integrates these two phases and obviates the theoreticaldifficulties introduced by their independent application. Oneform of the model requires value measurements that are beyondthe scope of current techniques, mak:ng it necessary to present"information conditions" that may reduce the level of therequired value measurements.

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15. EASTMAN, C.M., and KORTANEK, K.O., "Modeling Scnool FacilityRequirements in New Communities," Management Science, Vol. 16,No. 12, August 1970.

This is an exploratory paper developing new formulations for model-ing selected social and economic phenomena in a new or existingcommunity. The demand for educational facilities is shown to bedependent on the mix of housing designs and their sequence of con-struction. A Markov model, in a linear programming format, isdeveloped that explores the relation between alterative growthcurves of the student population and the housing mix and construc-tion sequence. Objective functions and constraints are formulatedthat allow for a wide variety of school planning objectives to berelated to the housing mix and schedule as defined by market, social,economic, or administrative constraints. The use of linear program-ming models to facilitate the analysis of complex social phenomenais detailed.

16. PAR, A.L., "Linear Programming Applied to Manpower Management,"Symposium - Management of Human Resources, IMR, Winter 1970.

This paper describes the basic features of a linear programmingmodel that can be used to analyze personnel policy combinations,in terms of their appropriateness, for maintaining a steady stateflow of people into, through, and out of an organization. Person-nel policies, however, cover so many aspects of human resourcemanagement that it is not feasible to include all of them in anyone model, given the current limitations of applied mathematicsand computer technology. The kinds of policies under considera-tion in this paper are shown in Figure 1. This figure presentsa macroscopic view of a typical organization's personnel proce-dures. It shows the interrelationships among recruitment, dis-tribution, training, and sustainment policies, and the effectsof these policies on an organization's training programs andoperating inventory of people. In the operating inventory ofpeople, those who perform other than "in training" roles arereferred to as the "organizational inventory." This inventoryis the focus of almost all modeling efforts since the attain-ment and maintenance of a desired organization inventory isusually the crux of manpower management problems. The inventorygreatly affects and is greatly affected by procurement, distri-bution, training, and sustainment policies, as indicated by the"closed loop" form of Figure 1.

17. SENGUPTA, J.K., "The Stability of Truncated Solutions of StochasticLinear Programming," ECONOMETRICA, Vol. 34, No. 1, January 1966.

In an ordinary linear programming problem it is assumed that allthe parameters (i.e., the coefficients of the objective function),the inequalities, and the resource availabilities are exactly known

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without errors. This assumption is relaxed in stochastic linearprogramming where some or all of the parameters are known only bytheir probability distributions. A distinction is generally drawnbetween the two approaches to stochastic linear programming; thepassive (also termed "wait and see" approach) and the active (alsotermed "here and now" approach). In the passive approach, theprobability distribution of the objective function is derivedexplicitly or by numerical approximations, and decision rules arebased on some features of this distribution. In the active approach,additional decision variables are introduced indicating the amountsof various resources to be allocated to different activities. Thispaper analyzes a method of characterizing the distribution of theobjective function values corresponding to the set 3f extreme pointsin the solution space for both these approaches of stochastic linearprogramming. Truncation refers to the selection of extreme pointsthat are neighbors, so to say, to the optimal extreme point. Thesensitivity of objective function values corresponding to truncatedsolutions is analyzed here in terms of stability properties, stab-ility being measured in terms of variance. An application to anempirical economic problem where there are parametric variationsin the coefficient matrix only, is presented to illustrate thenumerical problems and approximations involved in estimating thestatistical distribution of the objective function. From an eco-nomic point of view, the approach outlined here offers a theoryof the second best, since it specifies the set of conditions underwhich a value of the objective function that corresponds to theoptimum solution on the average may have higher instability thananother value of the objective function that corresponds to a trun-cated solution, under the assumed conditions of stochastic linearprogramming.

18. BRUNO, J.E., "The Function of Operations Research Specialists inLarge Urban School Districts," IEEE Transactions on Systemt Science& Cybernetics, October 1970.

The high cost of public education has stimulated interest in apply-ing the techniques of operations research and systems analysis tothe management of schools. These applications are generallyintended to promote greater efficiency in school operations andinsure more effective use of educational resources. Due to thesocio-political nature of public elementary and secondary educa-tional institutions, the role of the Operations Research (OR)specialist-systems analyst in the education sector might be con-sidered different from his counterpart in the military and indus-trial sectors. The function of the OR specialist in a largeurban school district is particularly affected or influenced bypolitical action groups, both in the school itself, e.g., teacherorganizations, and by the community. Yet it is in these largeurban districts where problems are most serious and the skillsof the OR specialist-systems analyst are in greatest need.

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TAEG RI PORT NO. 12-1

An attempt is made to demonstrate the role of the OR specialist inlarge urban school districts by using a problem situation which con-cerned itself with the politically sensitive question of developingan alternative to the fixed step salary schedule. A model is devel-oped and analyzed, showing in a scenario fashion the functions ofthe OR specialist. The highly political nature of certain schooldistrict planning problems, such as salary evaluation, stronglysuggests that the OR specialist in school districts be highlyskilled in working with political action groups and possess communi-cations skills to articulate various aspects of the planning effort,in addition to possessing the usual mathematical competencies.Graduate programs in OR at colleges and universities should reflectthese special needs in training OR specialists for public institu-tions.

19. WILLINGHAM, D.G., Determining the Optimal Flow of Student Sectionsat the Naval Guided Missile School. Monterey, Calif.: Naval Post-graduate School, Wasters Thesis, September 1971.

The problem of determining the capacity of a facility, such as theFleet Ballistic Missile School, to train sections of studentsattending numerous distinct courses was considered as an optimiz-ing problem, approachable in two phases. In the first phase, alinear programming model was developed for determining the maximumnumber of courses and the optimal mix of these courses which theschool can convene in one year. This model incorporates resourceconstraints, course content requirements, and the requirement tograduate a specified number of trainees over a period of time. Inthe secoid phase, criteria were developed to sequence the Phase Ioptimal number of convenings of each course into an annual schedule.A heuristic approach was presented to test such a schedule forfeasibility.

20. MAKI, D., "A Programming Approach to Manpower Planning," Industrial& Labor Relations Review.

A manpower planning model utilizing soon-to-be available data onjob vacancies is proposed by the author. The program is a fixed-horizon type planning model for the nation as a whole, but permitsregional disaggregation. The proposal model is based on a recur-sive programming technique.

21. THELWELL, R.R., "An Evaluation of Linear Programming and MultipleRegression for Estimating Manpower Requirements," The Journal ofIndustrial Engineering, XVIII(3), March 1967.

This article describes an analy ;s of linear programming and multi-ple regression as alternative estimating techniques for manpowerrequirements. The applicability of the usual regression model'sassumption concerning a constant variance when applied to a work


measurement situation is discussed. An alternative LP formulation,which makes better use of the observations, and one which providesa better fit to models with a constant term, is presented. The useof additional managerial information to supplement the traditionalinformation on resources used and units completed is suggested forLP. Included is a discussion of the applicability of dummy varia-bles to both techniques permitting the analysis of variables whichcan only be classified and not measured on a continuous scale.

22. HENDERSON, A., and SCHLAIFER, R., "Mathematical Programming: BetterInformation for Better Decision Making," Harvard Business Review.

This is a two-part article devoted primarily to optimization ofdelivery schedules and facilities usage via linear programming.Part I is an executive level survey, Part II deals with specificexamples.

23. MCNAMARA, J.F., Applications of Mathematical Programming Models inEducational Planning: An Overview and Selected Bibliography.University of Oregon, Council of Planning Librarians - ExchangeBibliography #271.

This paper contains a summarization of major conclusions based onthe synthesis literature on the application of mathematicalprogramming models in educational planning. It also contains alist of criteria in the form of questions to evaluate operationsresearch models.

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TAG REPORT NO. 12-1

B. NETWORK FLOW MODELS

Network flow models are employed in the solution of a variety ofproblems concerned with the actual or conceptual movement ofcommodities, information, or personnel. The mathematical tech-nique for solving network flow problems is somewhat related tothe Simplex algorithm for solving linear programming problems.Specifically, all three of the documents noted in this section[24,25,26] refer to the out-of-kilter method for minimal-costflow problems developed by Fulkerson in 1961. The approachconsists of an iterative procedure progressing from one feasiblesolution to another (improved solution) until an optimal solutionis reached. The report by Decisions Systems Associates [24]states as its objective, the development of an optimal networkflow algorithm which is more efficient than the current state-of-the-art. In addition to a review of related algorithms anda survey of application areas, a comprehensive description ofthe flow algorithm, a modification of the Fulkerson approach,is contained in the report. Hayter and Conner [26] describea Navy application of the network flow model to personnel plan-ning problems. This application considers five major control-lable personnel variables; requirements, on-board, attrition,advancement, and non-petty officer base. Gorham [25] presentsa slightly different approach to the same problem. His goalis to determine a set of training and retraining flows whichwill maximize the achievement of manpower requirements. Thenetwork flow technique should be further investigated for appli-cation to the aggregate training process flow model identifiedin Section VII.

24. HATCH, R.S., NAUTA, F., and PIERCE, M.B., Development of General-ized Network Flow Algorithms for Solvin_the Personnel AS§ignmentProblem. Decision Systems Associates, Inc. for Office of NavalResearch, April 1972, (Final Report - Contract IdentificationNumber NR 151-328).

This report describes research designed to develop efficient solu-tion approaches applicable to the personnel assignment problem.The research resulted in methodological enhancements to Ford andFulkerson's primal-dual network flow algorithms -- enhancementswhich provide a manyfold increase in efficiency. The enhancedsolution methodology is described in detail. Benchmarks areincluded to demonstrate the increased efficiency of the enhancedalgorithms over original versions of the Ford-Fulkerson algorithms.In addition, the superiority of the enhanced algorithms over assign-ment algorithms employed by the U.S. Air Force, the U.S. Army, andthe U.S. Navy is demonstrated via computer benchmarks.

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TACO REPORT NO. 12-1

Application of the algorithms to the personnel assignment prob-lem is discussed, including a comparative benchmark of the USMCComputer-Based Recruit Assignment (COBRA) model with the old andthe new algorithms, using operational recruit assignment data.

Although the enhanced algorithms are hardware independent, theirefficiency is still somewhat dependent on the basic computationalspeed and instructional repertoire of the hardware used. Bench-marks are provided to compare the relative efficiency of theenhanced algorithms on large, scientific computers manufacturedby IBM, CDC, and UNIVAC.

25. GORHAM, W., An Application of a Network Flow Model to PersonnelPlanning." IEEE Transactions, EM 10, 1963.

In this paper, a network flow model is applied to the prcblem ofchoosing the best pattern of training and retraining activitiesundertaken to insure that properly trained personnel are avail-able when and where needed at minimum cost. Although developedand discussed in the context of programming training in the U.S.Air Force, where the "employer" trains most "employees" for speci-fic military skills, the model is appropiate for other applica-tions where employers must engage in large scale training andretraining activities. First the problem is defined, and thegeneral model formulated. Then the details of tailoring themodel to the characteristics of the particular type of problemare discussed. An example using hypothetical data is presented.

26. HAYTER, D.F. and CONNER, R.D., A Network Flow Technique forOptimizing Personnel On-Board OfPay-Trade, San Diego, Callf.:U.S. Naval 'Personnel Research Activity, February 1966, SRR 66-12.

This modeling technique is based upon a network flow model uniquelydesigned for allocating present and future enlisted manpowerresources within the limits of constraining factors, in a mannerthat will meet manpower requirements as closely as possible. In

short, it is a planning technique for optimally allocating person-nel on-board at all pay grades of a rating for the next five years.

The model considers the present number of personnel on-board ateach pay grade of a rating and will attrite and advance them real-istically in future time periods. The future allocation of per-sonnel among pay grades is optimized for a five-year period relativeto the pay grade requirements with the constraints of predicted(exponential smoothing) attrition, advancements, reductions, andnon-petty officer base.

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C. LINEAR REGRESSION MODELS

The Linear Regression model is concerned with the estimationof the coefficients b = (b1 bn) of a linear relation-ship between a dependent variable y and a set of independentvariables x = (xl xn) having the form:

y b1x1 + b2x2 + + bnxn

The estimation is performed on the basis of a set of multivariateobservations on the variables y and x. Both Bottenberg [27] andWegner [28] provide a shortened textbook description of the linearregression proCess. Bottenberg's dissertation addresses the appli-cation of regression analysis to the prediction of personnelrelated criteria such as training success, job performance, etc.He also presents an iterative computational technique for solvinglarge scale regression problems. Wegner discusses the overlapbetween the two disciplines, multivariate statistics and mathe-matical programming. Both linear regression and linear prograw-ming are described in detail as techniques requiring conceptsfrom both disciplines.

A conceptual model of a generalizable educational system whichhierarchically and categorically organizes specific system inputsis described by Copa [29]. Multiple linear regression is proposedas a means of implemdriting the conceptual model by separatingrelevant and non-relevant inputs. The Marlowe, Escobar, Rowlandreport [30] describes the application of regression analysis tothe prediction of naval flight student training success. Phillipa[3] investigates a similar problem - the assignment of personnelto training schools in a manner that will result in optimum useof human resources. Phillips proposes use of a multiple discrim-inant model to solve the problem. Discriminant analysis differs.from regression analysis in the nature of the dependent variable.Regression analysis uses a quantitative dependent variable;whereas discriminant analysis uses a qualitative dependentvariable.

27. BOTTENBERG, R. A., The Exploitation of Personnel Data by Means ofa Multiple Linear Regression Model. Lackland Air Force Base,Texas: Wright Air Development Center, December 1960, WADD-TN-60-266.

One broad class of personnel problems involves predicting acriterion (training success, job performance, job knowledge,reenlistment decision) from available predictor information.Effectiveness of personnel utilization depends to a large extentupon effective prediction systems for such criteria. This reportdescribes an iterative procedure for determining weights in a

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multiple regren.;sion problem, programmed for an electroniccomputer. Large-scale regression problems can be economic-ally computed while avoiding, altogether, the question ofsingularity. The procedure also permits precise tests ofhypotheses, enabling the investigator to express his hunchesin full detail in formulating the regression model.

28. WEGNER, P., "Relations Between Multivariate Statistics andMathematical Programming," Applied Statistics.

Both types are subfields of multivariate analyses which isconcerned with linear, quadratic, and non-linear relations.Multivariate statistics i; concerned with the estimation ofparameters and the determination of the structure of relationsbetween variables. Mathematical programming assumes a mathe-matical model of known structure and is concerned with thedetermination of optimal policies subject to known structuralrestrictions.

29. COPA, G. H., Identifying Inputs Toward Production FunctionApplication in Education, Technical Report; Research Coor-dinating Unit for Vocational Education, University ofMinnesota, April 1971.

The major purpose of this report is to deal with the problemsof identifying educational system inputs. This does not sub-jugate the problem of identifying educational systems outputsnor imply that inputs should be considered before outputs.

As with other productive processes, education uses inputs toproduce outputs and, thereby, achieve production objectives.Production objectives should indicate output measures whichcan be used as valid gauges of production. When consideringproduction function development, the other measures needed areof the inputs. The objet.tive of this report is to describe a

generalized model for identifying educational system inputs.Only after conceptualizing such a model can the iterative prob-lem of accumulating a data bank be fully elaborated and pursued.

30. MARLOWE, E., ESCOBAR, C., and ROWLAND, G. E., Annual ReportinSupport of Advanced Development Objective 43-1Jr, HumanFactors Technology. Haddon Field, N. J.: Rowland and Cofiiin-iiii-Report No. 1, November 1970.

This report describes the approach used and the progress madein the application of existing knowledge and technology to thetest of computerized techniques which incorporate adaptive

training concepts and improved techniques for the predictionof Naval Flight Student Training success. Because these com-puterized techniques require a unique combination of special

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data inputs, data file organization, and specific computersoftware routines to process the file data, this combinationis called a data management system. The system will consistof a newly defined data bank and file organization of studentpilot selection, performance and administrative data; com-

puterized techniques for processing these data are developedto support a series of 14 system modules. When implemented,the data management system is expected to provide improvedprocedures for the handling of student pilot training. Theseimproved procedures can be expected to result in reducedattrition in the flight syllabus, more effective placementof students in the pipelines, possible changes in the flightsyllabus content, flight hours, and syllabus duration forcertain students.

31. PHILLIPS, P. J., MAJ., USAF., An Evaluation of the DiscriminantAssignment Model. Wright Patterson Air Force Base, Ohio: AirForce Institute of Technology, August 1966, Research ReportGSM/SM/66-14.

A solution to the problem of assigning personnel to trainingschool in a manner that will result in optimum use of humanresources might be in the use of the discriminate assignmentmodel. The model makes a probabilistic prediction that anairman's assignment to a given school is desirable by usingBayes Theorm and historical data of past school performances.Results of a rank correlation test indicate that the modelpredictions have a significant rank correlation with coun-sellor assignment ratings.

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D. MARKOV MODELS

A Mtrkov process represents a particular class of stochasticprocess in which the conditional distribution of any futurestate, given the past states and the present state, is inde-pendent of the past states, and depends only on the presentstate. Holdrege [32] presents a non-technical descriptionof an Air Force system called OSCAR - Optimum Selection,Classification, and Assignment of Recruits. The system con-sists of three independent models; the Tread InformationProjection model utilizes the Markov technique (a majorportion of the paper is devoted to the presentation of ananalog describing the Markov process) to address the trainingschool assignment problem, the Selection and Assignment modeluses an iterative multiple regression technique for determin-ing optimal school assignments based on aptitude scores, andthe Grouping Evaluation Technique uses regression analysis todetermine the predictive efficiency resulting from consideringschools not as entities but as groups of schools.

Merck [33] and Durbin [34] both use the Markov process to des-cribe the flow of individuals through a system to provideprojections of a population at some point in the future underexisting policy conditions. Major problems faced in bothsituations were the state description of the system and thederivation of state transition rates. Merck's state descriptionof Air Force personnel is based on career field and enlistmentterm. Career field is subdivided into highly technical,technical, and semi-technical. Enlistment term is divided ,

into first, second, and three or more. Thus, Merck uses atotal of nine states to totally describe Air Force personnel.The transition matrix was generated as a result of an analysisof personnel records.

Clough, Dudding, and Price [36] use a different approach to analyzethe assignment problem in the Canadian Air Force. A Markovian statedescription based on rank, aircraft qualification, and state (orcurrent assignment) is used to describe the manpower system. Then,based on this system definition, several mathematical programmingmodels are formulated in terms of objective functions and constraints;Ccst Minimization, Selective Promotions Maximization, AssignmentPreference Maximization, and Mission Effectiveness Maximization.

The Russian authors [35] propose a Markov model of the edu-cational system at the national level to assist planningagencies during the process of planning and control of theeducational system.

Merck, and Ford [37] describe a feasibility test on the appli-cation of the Markov chain model to personnel system policyplanning, which was conducted in 1959. This paper represents

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a pioneer effort it the application of the Markov technique tothe study of the personnel flow problem. The authors employedthree variables to characterize the airman population - careerfield, grade, and total years of active service. On the basisof the feasibility test, Merck and Ford recommended that appli-cation of the technique on a larger scale would be practicaland would provide personnel planning agencies with valuableinformation. The authors recommended the development of aninformation system which would provide the basis for the estab-lishment of the state transition rate matrix.

32. HOLDREGE, F.E., COL., USAF., OSCAR: Optimum Selection, Classifi-cation and Assi nment of RecTits: Lackland Air Force tase,exas: t ersonne esearc Laboratory, July 1962,PRI-TDR-62-13.

Three mathematical models, adaptable for electronic processingmachines, are described in non-technical terms and illus-trated by applications to personnel procurement and assignmentproblems. Emphasis is on capability for providing managementwith meaningful information for controlling a complex personnelsystem.

33. MERCK, J.W., A Markovian Model for Pro'ectin Movements ofPersonnel Throua a System. ack and it Force Base, Texas:Personnel Aesear&I Laboratory, March 1965, PRL- TR -65 -6.

A large, centrally controlled organization needs an accurateprojection of future personnel requirements. A computer-processed mathematical model is developed which simulates move-ments of personnel through the system with the movements basedon empirically derived probabilities, the transition rates.Significant variables are selected (career field, LOS, grade)that distribute the system members in a vector of statesupon which a probability matrix operates to produce the esti-mated distribution of personnel at the end of the next timeinterval. Proposed policy changes can be entered into thesystem to forecast their effects. In establishing a model,the basic decision is the selection of variables that willcharacterize the members. The first requirement is that re-liable input data be available for the current and precedingtime intervals.

34. DURBIN, E.P., 1lAppower Programs as Markov Chains. SantaMonica, Calif: stand Corp., October 1968, RM-5741-0E0.

This report indicates how manpower programs (0E0) can beviewed in terms of personnel movement through defined stagesof the program. This dynamic process leads to a character-ization of movement through the program as a Markov process.The objective of such a characterization is to provide asimple informational framework which may facilitate compari-son of programs.

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35. BERMANT, M.A., SEMENOV, L.K., and SULITSKIY, U.N., MathematicalModels and Educational Planning. Arlington, Va.: abint Publica-tions Research service, April 1973, JPRS 58793.

This translation of a Russian-language book discusses the problemsof the application of mathematical methods to the planning andcontrol of the personnel training process. A study has been madeof methods of assigning the requirements for specialists and themethods of educational planning for the satisfaction of theserequirements. An approach is proposed for the construction ofthe mathematical model (utilizing Markov chain technique) of theplanning and control of the process of meeting the requirementsfor specialists in any branch of the Soviet economy. The authorspoint out that because of "the planned nature of the nationaleconomy based on objective economic laws of Socialism," the taskof creating mathematical models of the education process is lessdifficult in the USSR than in capitalistic societies. A surveyof various "foreign" models of educational planning is included.

36. CLOUGH, D., DUDDING, R.C., and PRICE, W.L., Mathematical Program-ming Models of a quasi-independent Subsystem of the Canadian ForcesManpower System,. Waterloo, Ontario, Canada: University of Waterloo,Dept. of Management Sciences, September 1969.

This paper presents a fairly detailed treatment of a possible flow/cost model for pilot training in the RCAF. The model was neveractually used but might be applicable to some portions of the NavyTraining System.

37. MERCK, J.W. and FORD, F.B., Feasibility of a Method for EstimatingShort-Term and Long-Term Effects of Policy Decisions on-thi-ATimanPersonnel System. Lackland Air Force Base, Texas: Personnel`Laboratory, Wright Air Development Center Air Research and Devel-opment Command, June 1959, WADC-TR-59-38.

This report describes a model which simulates the flow of airmenthrough the Air Force personnel system under a given set of poli-cies. The model makes it possible to estimate the effects of thatset of policies at future points in time. These effects may begauged in terms of the future distribution of grade levels, careerfields, or other pertinent information which may be built into themodel.

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E. MATHEMATICAL ANALYTIC MODELS

Mathematical Pnalytic models represent a subset of the total classof deterministic models (other subsets include linear programming,regression analysis, game theory) in which the relationships betweendependent and independent variables can be expressed in the form ofmathematical equations.

Models and model applications covering a wide range of aggregationand complexity and ranging from conceptual formulations to opera-tional systems are included in this section. One end of the spec-trum is represented by Reisman [38] who describes a conceptualmodel to study (at the national level) the production of collegedegrees and their feedback into education. The model is describedthrough a set of approximately 50 differential equations. Imple-mentation seems unlikely since qualitative data for several varia-bles is non-existent while other variables remain undefined.Dieterly's Air Force manpower management model [39] consists ofseven indices, each representing various proportions of personnelstrength figures. Interpretation of these indices by personnelmanagers theoretically pinpoints problem areas and suggestscourses of corrective action.

Bowles [40] and Siegel [41] both discuss macroeconomic models ofthe educational system. Boyles pr000ses a constrained maximiza-tion model with an objective function representing the contribu-tion of the educational system to future national income, measuredby the increment in discounted lifetime earnings attributable toadditional years of education, Siegel attempts to construct atheory of enrollment supply based on institutional utility func-tions. A sea/shore rotation model somewhat analogous to aneconomic model of supply and demand has been constructed byBorgen, Segal, and Thorpe [42] to assist personnel managers inestablishing sea tour lengths in appropriate relationships topolicy prescribed shore tyrs.

Gladston and Swerdlow [43] discuss a Navy version of a computerizedpersonnel projection model which was initially developed by theOffice of the Assistant Secretary of Defense. The Enlisted GradeProjection model focuses attention on the way in which changes inthe force structure, at a period of time assumed to be representa-tive of the predicted near future, will influence a short-termprojection of the force in an aggregate form.

Sands [44,45] describes a Navy application of an analytical tech-nique to determine optimal recruiting-selection strategies. Thebasis for the development of the CAPER model is that the utilityof a selection test is a function of three considerations: (1) abase rate; (2) the validity of the test; and (3) the selectionratio. Relationships between these variables are expanded andexpressed through a series of 20 equations.

The Billet Cost Model (BCM) [46] is a life cycle approach to man-power costing developed by B-K Dynamics, Inc. The 8CM computes

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the costs of manning authorized billets with people having req-uisite skills, in terms of the investment and operation cost tothe U.S. Government. This costing capability is tied to theADSTAP system through the Interim Per Capita Cost Model (INPER)[47] which was also developed by 13-K Dynamics, Inc. INPERutilizes ADSTAP-generated force structure matrices and BCM-generated cost data to compute per capita unit cost matricesfor each rating.

The Computerized Advance Personnel Requirements and Inventory(CAPRI) System [48,49,50] represents one of the more complex andsophisticated systems (with the exception of ADSTAP) encounteredin the course of this technological data review. Although thesystem is reported to be operational, this fact could not beverified since the model users could not be located in the courseof an extensive review of operational Navy models. )ne CAPRISystem objective is to forecast time phased personnel and train-ing requirements. CAPRI consists of two major subsystems; theNetwork Planning and Analysis Subsystem, which is an adaptationof the Program Evaluation and Review Technique (PERT) to person-nel program management fictions, and the Billet and InventorySubsystem which is utilized in support of the Personnel Subsys-tem production phase management functions by providing bothcurrent and projected status through a determination of billetsvs personnel inventory information on a weapon system basis.

Spirer's doctoral dissertation [51] develops a systems-matrixtechnique for describing time-dependent organization informa-tion flows. Current techniques employed by systems analyststo describe information flow are the tabular description,graphic flow chart, and the adjacency matrix. Spirer extendsthe matrix model concept to time-dependent information systems,developing an algorithm which generates results for flow pathenumeration, path specifications, and flow transmission times.The Navy training system has been analyzed and functionallydescribed in Phase I of this training systems project. Thisfunctional description could be supplemented by an analysisof the information flow within the training system utilizingthe matrix techniques developed by Spirer.

38. REISMAN, A., "Higher Education: A Population Flow Feedback."Science, 153(3731): July 1966, pp. 89-91.

This paper discusses a conceptual mathematical nodel to study theproduction of doctorate, master's and baccalaureate degrees andtheir feedback into higher education. The author develops a seriesof differential equations based on the premise that the total rateof flow into a category (e.g., master's degree program), less the

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rate of outflow, is equal to the rate of accumulation or growthof a given category. The resulting model is highly theoretical;several variables are not defined and the quantification of thosevariables that are defined does not appear to be an easy task.

39. DIETERLY, D,L., CAPT., USAF., Simplified Approach to a ManpowerManagement Model. Lackland Air Force Base, Texas: PersonnelResearch Laboratory, December 1968 (TR 68-116).

A manpower management model was designed to reflect four factorsof concern to personnel managers; procurement, training, reassign-ment, and retention. Within the framework of this model, sevenbasic indices were developed to yield simple, reliable, descrip-tive data by which a manpower structure could be assessed. Bymeans of the simple ratio indices, specific manpower problemareas can be identified and force strength can be compared acrossseven dimensions (loss, retention, gain, flow, transfer, utiliza-tion, and stability) ac various levels within an organization.

40. BOWLES, S., "The Efficient Allocation of Resources in Education."Quarterly Journal of Economics. pp. 189-219.

This paper discusses a macro-level model which addresses thequestion of optimal resource allocation in education. The modelmaximizes a weighted function of enrollments in various types ofeducational institutions over time, subject to constraints basedon an educational production technology and given resource avail-abilities.

41. SIEGEL, R.N., Toward a Theory of the Educational Firm. Centerfor the Advanciaaudy of Educational Administration, Universityof Oregon: Revised 1971.

The author discusses the interrelationship of the factors affect-ing enrollment supply, price control, and federal subsidy inrelation to institutions of higher learning.

42. BORGEN, N.I., SEGAL, J.A., and THORPE, R.P., An Equilibrium FlowModel of the Navy's Enlisted Rotation System. San Diego, Calif.:Naval Personnel and Training Research Lab oratory, November 1972.Paper presented at the Joint National Meeting, Operations ResearchSociety of America, The Institute of Management Science, SystemsEngineering Group of AIIE; Chalfonte-Haddon Hall, Atlantic City,New Jersey.

The periodic rotation of enlisted personnel between sea duty andshore duty assignments is a firmly established Navy policy. Theefficiency with which rotation is carried out, however, can havean effect on both the personnel readiness of operating units andthe morale of the individual Navy man. This paper describes thedevelopment of a computer based equilibrium flow model of therotation system which enables personnel managers to test and

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evaluate policies and procedures related to improved planning andcontrol of personnel movements. Examples of actual managementapplications of the model are also given.

43. GLADSTON, K.M. and SWERDLOW, D., The Enlisted Grade ProjectionModel (PROMO): A Management Tool for Navy Personnel Planners.Washington, D.C.: Naval Personnel Research and DevelopmentLaboratory, December 1970 (WRM 71-24).

A Navy enlisted aggregate personnel projection model has beendeveloped to analyze various relationships of changes in forcestructure to changes in personnel inventory. This model examinesa variety of personnel policies and changes in force structurevariables. It is specifically designed to test the future rami-fications of short-term personnel policies and portray the trade-off between short and long-term objectives. Statistical extra-polition, econometric, and mathematical logic have beenaccomplished on such variables as loss rates and promotion ratiosto provide a more exact specification of the model in addition toa better projection capability.

44. SANDS, W.A., A bivariate Normal Version of the Cost of AttainingPersonnel Requirements CAPER Model. Washington Navy Yard:Naval Personnel Research an Deve opment Laboratory, April 1973(Report No. WTR 73-18).

Managers of military and civilian personnel systems justifiablydemand an estimate of the payoff which may be expected to resultfrom the implementation of a proposed selection program. TheCAPER models provide the manager with the information needed toformulate an optimal personnel recruiting-selection strategy.This strategy will minimize the expected total cost of recruiting,selecting, inducting, and training of a sufficient number ofpersons to meet a specified quota. The original version of themodel (CAPER I) employs raw data and evaluates the experimentalselection strategy at each possible cutting score on the newselection test. The data preparation task for CAPER I is tedious.This report introduces a bivariate normal version of the modelCAPER II. CAPER II requires more statistical assumptions thanthe original, but drastically reduces the work involved in inputdata preparation.

45. SANDS, W.A., A Handbook for the bivariate Normal Version of theCost of Attaining Personneirements (C PERWashington Navy Yard: Naval Personnel Research and DevelopmentLaboratory, April 1973 (Report No. WTR 73-19).

Managers of military and civilian personnel systems justifiablydemand an estimate of the payoff which may be expected to resultfrom the implementation of a proposed selection system. The CAPERmode's provide the manager with the information needed to formu-

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late the optimal personnel recruiting-selection strategy. Thisstrategy will minimize the expected total cost of recruiting,selecting, inducting, and training a sufficient number of personsto meet a specified quota, This report provides a detailedexplanation of the steps involved in using the CAPER II model.Application of model equations is illustrated using an exampleproblem. A FORTRAN IV computer program listing is also presented.

46. B-K DYNAMICS, INC., Billet Cost Model Users Manual. Rockville,Md.: 8-K Dynamics, Inc., September f970 (TR-3-159). Preparedfor Bureau of Naval Personnel.

The Billet Cost Model (8CM) was developed in order to providethe Navy with a current means, by use of computer techniques,of computing reasonable accurate manpower resource costs onthe basis of standard uniform cost formulae. This report des-cribes 8CM program operation, details the cost and statisticaldata employed it generating career costs with the BCM, and des-cribes the preparation of the data and card decks for input tothe 8CM. Descriptions of the data elements, their sources, andwhere appropriate, computational methods, and instructions areincluded.

47. B-K DYNAMICS, INC., INPER: Interim Per Capita Cost - ComputationMethods and Operational Controls: RockviTle, Md.: B-K Dynamics,Inc., January T9 1 WR60.17---

This report develops interim Per Capita Cost detailed computationmethods and operational controls for obtaining useful (firstorder approximation) per capita cost values by grade and year ofservice. INPER costs are applied to the force size as defined bythe ADSTAP system thus enabling evaluation of policy and planningdecisions as they affect the long-run costs of the force. INPER

utilizes the operational Billet Cost Model which computes thecost of mauling the authorized billets with requisite skills interms of the investment and operation cost for each year of theexperienced longevity of a given rating.

48. PULSCAK, M.W., RAPHAELSON, EThe CAPRI System for Naval Per- Description and Operation.Research Incorporated, May 1965

R.W., and CLEVELAND, R.H.,r Program Management: Volume I

2,orings, Md.: OperationsNo. ND 65-28).

The Computerized Advance Personnel Requirements and Inventory(CAPRI) System described in this report was developed in orderto provide the Bureau of Naval Personnel (SUPERS) with a manage-ment tool for efficient and effective planning, development,production, and control of personnel required to support bothnew and operational naval weapon systems. The system wasdesigned to be compatible with and, to the greatest extentpossible, to utilize the existing systems, procedures, and

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data banks available within the Bureau of Naval Personnel. TheCAPRI System design encompasses the manpower management functionsinvolved in the complete life cycle of a PS for a new naval weaponor support system. This life cycle spans the period from theissuance of a GOR for the new naval system development throughthe final phase-out of the last operational model of the system.The total cycle can be considered as having two distinct phases;the PS development phase and the PS production phase. In orderto carry out effectively the management and control functionsrequired in each of these phases, two distinct CAPRI subsystemsare utilized - the Network Planning and Analysis (NP&A) Subsystemand the Billets and Inventory (B&I) Subsystem.

49. PULSCAK, M.W., et al., The CAPRI System for Naval Personnel Prog-ram Mana.ement: Volume II - Data Processing Manual. SilverSprings, M..: 'pera ons Researc Inc., ay 96 ORI TR 322Vol. 2 (Report No. 65-29).

A description is provided of the data processing operation of eachof the CAPRI subsystems; Network Planning & Analysis (NP&A) andthe Billets and Inventory (B&I) Subsystems, The emphasis is onelectronic data processing production scheduling proceduresrequired for operation. A description of each computer programis provided including purpose of the run, inputs, and outputs.Detailed procedures describing the operational requirements ofthe system are included in the appendices.

50. PULSCAK, M.w.) et al., The CAPRI System for Naval Personnel Prog-ram Management: Volume III - Advanced Development. SilverSprings, Md.; Operations Research Incorporated, May 1965, ORITR 322 Vol. 3 (Report No. 65-30).

A program of advanced development is being pursued concurrent withthe implementation phase of the operational pruyrdm. This reportdescribes four areas of advanced development: (a) the refinementof the utility of the inventory projection model; (b) the extensionof the parameters of the CAPRI System to include information onrecruit and "A" 'school requirements and inventory for technicalratings; (c) the design of a CAPRI cost system to provide infor-mation on personnel subsystem costs including training aids andfacilities, and (d) the extension of CAPRI capability to includeofficer data, by weapon system.

51. SPIRER, H.F. , Structural Models for Time-Dependent InformationSystems. Phd Dissertation, N.Y.U., School of Engineering andScience. January 1970.

Analysis of information flow has been accomplished by systems anal-ysts using tabular charts, flow charts, and more recently, matrixmodels. The purpose of this thesis is to generalize the concept ofmatr'.x model and extend it to time-dependent information systems.

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Social scientists introduced matrix models for organizations over20 years ago. Subsequently, Lieberman introduced matrix modelsfor a limited set of information systems. Homer developed a moregeneral systems-matrix model. Neither model deals with cyclicsystems, nor provides solutions for time-dependent systems.

This thesis gives two methods for dealing with cyclic informationsystems; one by an ordering algorithm, the other by a matrix modelbased on reachability concepts.

A matrix model for elementary time-dependent systems is presented.Redundancy, as applied to information systems, is defined relativeto the "release" of information from a given system component.Zero redundancy is where only one receipt of an item of data isrequired before release; total redundancy is where the data mustbe received through all paths before release, Partial redundancyconcerns intermediate cases, where some, but not all, receipts ofan item of data are required. Solutions for the two extreme casesare obtained from the matrix model for the elementary time-depen-dent system.

A generalized systems-matrix model for time-dependent informationsystems is developed. This model not only solves the elementarytime-dependent system, but has, as particular solutions, theresults for path enumeration and specifidation of the prior matrixmodels.

The generalized model is extended to the time-dependent systemwith filtering, in which logical functions determine the trans-mission of information between components. This includes alarge set of complex practical situations. Solutions of thegeneralized systems-matrix model with filtering are obtainedfor zero, total, and partial redundancy. The direct applica-tion of the generalized model to the system including partialredundancy produces solutions which can be simplified bytheorems given in this thesis.

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TAEG REPORT NO 12-1

F. SIMULATION MODELS

Simulation is essentially a technique that involves setting upa model of a real situation and then performing experiments onthe model. In the context of this project, the definition ofsimulation will be restricted to experiments on logical andmathematical models only. Hence, all physical, verbal, pictor-ial, and analog models are excluded from our now restricteddefinition of simulation. Mathematical simulation models canbe arbitrarily classified as deterministic, stochastic, static,or dynamic. These classifications are by no means mutuallyexclusive. In deterministic models neither the exogenous(independent or input) variables nor the endogenous (dependentor output) variables are permitted to be random variables, andthe operating characteristics are assumed to be exact relation-ships rather than probability density functions. Those modelsin which at least one of the operating characteristics is givenby a probability function are said to be stochastic models.Static models are those models which do not explicitly takethe variable time into account. Mathematical models that dealwith time-varying interactions are said to be dynamic models.The majority of models discussed in the section can be classi-fied as dynamic and stochastic.

Rubin [52] and Mormile [53] of Research Analysis Corporation,describe the result of Phase I and Phase II efforts to developa Personnel Inventory Analysis (PIA) system for the U.S. Army.Four models are detailed in the Phase I report [52], projectionand distribution models for both enlisted and cMcers. Thesemodels accept information concerning manpower authorizationsdimensioned by time and place, and further accept or developpersonnel asset data, rates, factors, and policies from cur-rent Army records and historical files. Based on data accu-mulated or developed, the models produce reports providing aprojection of worldwide assets based on established prioritiesand distribution guidelines. Only the Officer Inventory Pro-jection model is stochastic; the other three are deterministic.All are dynamic. The Phase II report [53] discusses four addi-tional deterministic models. The Condition Determination modeldetermines the condition of manpower categories after assetshive been distributed to command elements, ranking personnelproblem areas in order of criticality. The Cause Identifica-tion model determines causes for those categories found to bein critical condition. Models exist for both enlisted andofficer categories.

A oynamic stochastic entity simulation model is described byGroover 154]. Tnis model, a generalized military personnelsystem simulation capable of addressing both the officer andenlistec components of all four military services, was devel-oped through the Office of the Assistant Secretary of Defense.

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Procurement, assignment and reassignment, and promotion and lossare simulated in individual system modules. The one drawback ofthe generalized approach, as noted by the author, is that a sub-stantial (two man-month minimum) one-time effort must be investedin model implementation. The bulk of this effort would be assoc-iated with data definition.

A Simulation Model of Personnel Operations (SIMPO) [55] and [56]is a comprehensive set of Simulation models developed by the U.S.Army Behavioral Science Research Laboratory. These models simu-late several segments of the Army personnel system and aredesigned as tools to enable Army management to examine the effectof policy change. The system consists of a combination of aggre-gate and entity flow models, all of which can be classified asdynamic, stochastic simulations. Although developed in the 1968and 1969 time frame with a reported ten man-year effort, thesystem is now reported as "retired" by the Army. Several modelswere noted to be no longer useful while others were reported tohave been replaced by more sophisticated unnamed models.

Gaylord, Farina and Spector [57] describe the Phase I efforts ofan operational analysis of the Naval Personnel System performedin 1959. The approach used in this analysis of the personnelsystem is very similar to that used in the current Training Sys-tem Analysis project. The report presents a top level functionaldescription of the Naval Personnel System. The report does not,however, describe functional interactions; also functional des-criptions are not provided beyond the top level. The authorsdefine a conceptual model of the system encompassing recruiting,classification, training, distribution, utilization, and promo-tion. A deterministic simulation model capable of providingestimates of future personnel availability under alternate modesof personnel operations was designed, based on the conceptualmodel. The Phase II report [58] authored by Gaylord and Knetz,describes the development of a computerized personnel productionmodel which was designed in Phase I, tests of its simulationfidelity, and illustrations of its use. This simulation modelis intended to be used to evaluate the potential impact ofspecific personnel programming decisions affecting such directlycontrollable endogenous variables as procurement and trainingratios, school duration, graduation standards, etc. An addi-tional objective of the simulation is to determine the impactof predicted changes in reenlistment rates and other indirectlycontrollable endogenous variables about which predictions canbe obtained.

Unlike the papers described above, Dellheim [59] does not des-cribe a real-world application of the simulation technique, butpresents a user interface between the modeler and existing com-puter simulation languages, such as GPSS (General Purpose SystemSimulation). Dellheim's Modeling Control Language is model imple-mentation language independent.

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52. RUBIN, A., The Personnel Inventory Analysis SIstem: Part I -

General Descr {ption. McLean, Va.: Research Analysis arPoration,August 1968 (Inter m Report).

The overall objective of the Personnel Inventory Analysis (PIA)System is the development of a methodology to permit rapidqualitative and quantitative analysis of the personnel aspectsof force structure plans. The models discussed in this r .portproject the distribution of personnel resources against projectedauthorizations by MOS for enlisted, and by grade /branch for offi-cers, based upon established priorities and distribution guide-lines for use by personnel planners in manpower capability andanalysis studies of alternative plans. The model is used toproject training input requirements necessary to bring the MOStotal up to operational strength based on training time andattrition rates.

53. MORMILE, G.T., Personnel Inventory Analysis System: The Evalua-tion Phase. Madan, Va.: Research Analysis Corporation, Oct ber1969 (RAC-TP-378).

The overall objective of the PIA system is the development of a

methodology to permit rapid qualitative and quantitative analysisof the personnel aspects of force structure plans making maximumfeasible use of computers. This paper describes a methodology toevaluate the Army manpower situation within the PIA system. Theevaluation phase consists of two parts; determining the manpowercondition of both officer branch/grade and enlisted MOS categories,and determining the cause of any critical condition.

54. GROOVER, R.O., PERSYM: A Generalized Entity - Simulation Model ofa Military Personnel System. Paper presented at the NATO Confer-ence on MatherriifrEal Models for the Management of Manpower Systems,Oporto, Portugal, September 1969.

PERSYM is an operational entity-simulation system designed topermit observation and selective control of system dynamics ofa military personnel system under a variety of policy alterna-tives. The system functions simulated are procurement, assign-ment and reassignment, and promotion and loss. Necessarytraining outputs and transients are identified and reported.Samples of reports are presented and plans for further develop-ment are discussed.

55. NIEHL, E. and SORENSON, R.C., SIMPO-1 Entity_ Model for Determin-ing the Qualitative Impact of Personnel- Policies. Washington, D.C.:U.S. Army Behavioral Science Research Laboratory, January 1968(Technical Research Note 193).

The entity model was designed for integration into the more general-ized SIMPO-1 simulation package for evaluation of personnel and man-

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power policy alternatives. The entity model concentrates on theprocurement, selection, and allocation aspects of the personnelsystem. Other models to be developed which will interface withthe entity model, will be concerned with distribution, tour rota-tion, promotion, and training.

56. OLSON, P.T., SORENSON, R.C., HAYNAM, K.W., WITT, J.M., andABBE, E.N., Summary of SIMPO-1 Model Develo ment. Arlington, Va.:U.S. Army Behi0ori1 Tffence Research a oratory, March 190(Technical Research Report 1157).

The SIMPC 1 effort has been directed towards development of asimulation package for assessing, quantitatively, the cumula-tive impact of personnel policy changes on the allocation,distribution, and utilization of Army personnel, with specialattention to effects of policies on deployability. This pub-lication reports on progress in the production and planning ofthe following models.

DYNAMOD - mass flow models of rotation system; ACCMOD - dynamicmass flow model on non-career enlisted; DYROM II - a dynamic massflow model of the upper five enlisted grades; SIMPO-1 QualityInput Model - an entity simulation model.

57. GAYLORD, R.H., FARINA, A.J., SPECTOR, P., Operational Analysis ofthe Naval Personnel System: Part I. Development of a PersonnelSystem Model. Washington, D.C.: American Institute for Research,December 1959 (AIR-33-59-FR-218).

This report represents a pilot application of the techniques ofoperations research to the analysis of the Naval Personnel Systems(including training). The study addresses the development of apersonnel system model based on a functional analysis of the systemand a conceptualization of the system's major processing elements.A quantitative model was devised which permits the estimation ofpersonnel system effectiveness under alternate programs of person-nel action.

58. GAYLORD, R.H., and KNETZ, W.J., Operational Analysis of the NavalPersonnel System: Part II. Development and Testiaof a MachineSimulation of Personnel Operations. Washington, 0.C.: American

July 1961 (AIR-C3-60-FR-232).

This report discusses in detail, the conversion of a set of generalspecifications for a mathematical model of the personnel productionprocess to an operational computer simulation of the process. Thesimulation provides estimates of the personnel inventory that willbe available at each date of a planning period under the constraints'of various selected personnel policies. Included in the report is astep-by-step description of the development of simulation computerprogram and of the validation and accuracy testing performed. Datasources and conversion routines are provided in the report appendix.

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59. DELLHE1M, J.L., A ModelinControl Lan ua e. Poughkeepsie, N.Y.:International BusTiss Mac Ines~ orporation, June 1972 (TR 00.2325).

MCL, Modeling Control Language, is JCL-like, simple to learn, andeasy to use. The model user, regardless of his degree of inputstream stipulations or of modeling sophistication, will be ableto control his unique model run requirements with minimal training.A design point for MCL is a common modeling control language foruse with the VS1, VS2, and EDOS operating systems and operationalenvironment system models.

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G. MODEL SURVEYS

In the process of compiling this technological data base, severalpapers were encountered which either presented assessments of theimpact of mathematical modeling applications in the field ofeducation and training or simply surveyed existing educationalsystem models. Hammond [60] presents an indication of the typesof models that have been constructed, the variety of purposes forwhich models have been used, and the difficulties of adequatelymodeling educational systems. Although the models surveyed weredeveloped outside of the military, the modeling concepts areapplicable to all areas of educational research. Hammond statesthat because of the complexity of education and training systems,mathematical models can be used effectively to explain the behaviorof educational systems and to assist in making decisions relativeto better design and operation, improved cost-effectiveness,capacity, and quality. In his concluding remarks Hammond reiteratesthe following point which has been stressed by several individualsin the modeling business; recent modeling efforts have had animportant impact as an aid to data collection, in pointing outwhat kinds of data are needed, and in encouraging a systematicapproach to data collection. Durstine [61] presents a brief surveyof the role of technical methods of management as applied to educa-tional processes, which highlights the accomplishments, promises,limitations, and perils of those methods. Ourstine cautions againsta wholesale application of modeling techniques in the educationalfield. He points out the existence of a tendency toward overexpec-tation from these methods, and a corresponding tendency on the partof practitioners to oversell them. Ourstine also notes that thereis a gap between the technical sophistication of much tnat isproposed to aid management of educational processes, and the abilityof the managers to use these aids. Weitz [62] reviews fifty-sixdocumented applications of operations research techniques in theeducational field. Because Weitz believes that educational systemplanning models are of particular significance and hold the mostpromise for assisting the educational administrator, the majorityof applications reviewed are in this category. That Weitz is morebullish than either Hammond or Durstine regarding the applicationof operations research techniques to educational problems is evi-denced by his concluding remark, "Decisions will be made in anyevent, hence why not make the assumed relationships explicit byincorporating them in a decision mode."

Item 63 consists of three chapters from the Review of EducationalResearch. In the first (Chapter V), "Concepts anTlechniquesiirEducational Planning," Chirikos and Wheeler review some of theaggregate models and techniques that have been either suggested

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or actually used for the preparation of national educational plans.The second chapter (Chapter VI), "Strategies for Allocating Humanand Material Resources" by Nystrand and Bertolaet, reflects onallocative strategies in which pupils, staff members, materials,and facilities are considered resources which can be organized invarious mixes to produce educational experiences. Literaturereviewed in this chapter includes sources which report currentpatterns in the allocation of such resources, and studies whichcomment upon the outcomes associated with particular allocativepatterns. Benson, in the third chapter (Chapter VIII) includedin item 63, reviews several economic dissertations dealing withthe measurement of the economic benefits of education, educationalplanning, efficiency criteria, and adequacy of revenue sources.

Hutchins, et al. [64, 65], describe a technical review of availablemanpower/personnel management planning and resource managementcomputer models. The report emphasizes operational Navy modelsbut includes nearly 130 models from the Army, Air Force, MarineCorps, Federal Government agencies, State and local governmentagencies, and private industry. Since training is an integralpart of personnel management, several training related models weredocumented in Hutchins' model compendium. However, as pointed outAppendix B, the model compendium also illuminates the fact that ofthe few existing training related models which are identified, noneis operational within the CNET organization.

Prior to the release of Hutchins' computer model compendium, theIBM study team had conducted an independent model survey with thesingular objective of identifying operational training relatedmodels and existing data bases. Several of the characteristicsof the Navy modeling environment noted by the IBM team werealso noted and identified in the Hutchins' report. Among themost important of these:

o With the exception of some personnel data files whichhave been preserved by NPRDC, very few historical data(manpower requirements, staffing criteria, performancestandards) are available within the Navy.

o Of the existing models, training-oriented as well asthose dealing with other aspects of the personnel system,there was no common organizational approach. All modelswere apparently created in a vacuum.

o While very few models exist in some areas, such as training,other areas, such as personnel inventory projection, exhibitnumerous models which solve similar if not identical problems.

o A serious communications gap exists in the manpower/personnelmanagement community with regard to modeling applications.

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60. HAMMOND, A., Mathematical Models in Education and Trainini.Santa Monica, The Rand Corporation, September X970(Report No. RM-6357-PR). Prepared for the U. S. Air ForceProject Rand.

A nontechnical introduction to the state-of-the-art in modelingeducation systems, prepared for Rand's Air Force technical training study. Input-output models are convenient for examiningvoluminous data on student flows for short periods or forrelatively static institutions. Manpower planning models seemleast useful. Optimization and simulation models are complemen-tary. Optimization models show resource allocation choicesexplicitly, yield plans and priorities, and stimulate policy-level discussion. Simulations can help in management and short-term planning if enormous quantities of data are available. Amodel need not be realistic if it gives useful answers, nor isthere one best way to model a situation. Simple models are bestat our present level of understanding of the educational process.Included are a review of the literature and a selective bibliog-raphy. Mathematical details are given in an appendix.

61. DURSTINE, R.M., "Technical Trends in Educational Management:Opportunities and Hazards." Management Comparative EducationReview, October 1970, 327-334.

An extremely general, philosophical paper on the benefits andproblems encountered when using models of any kind as manage-ment aids in education.

62. WEITZ, H., An Assessment of the Contribution of Operations Researchto Educational Planning. Paper presented at the Joint NationalMeeting of American Astronautical Society (15th Annual) and Opera-tions Research Society (35th National), Brown Palace and CosmopolitanHotels; Denver, Colorado, June 1969.

During recent years, the methods of operations research and systemsanalysis have been increasingly applied to problems of education.The developments considered fall into the categories of, a) educa-tional research, b) program planning and budgeting, c) gaming forinstruction and administrative training, d) design of instructionalsystems, e) the evaluation of computer systems for administrationand instruction, and f) educational system planning models. Majoremphasis in this paper is given to identification of a pattern indevelopment of models for educational system planning; projectionof enrollment populations, structuring of resource requirements,allocation and assignment of resources, and evaluation.

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63. CHIRIKOS, T. N., NYSTRAND, R. O., and BENSON, C. S., Reviewof Educational Research CH. V, Vol XXXVIII, No. 3, June lgel;R. NI, Vol XXXVII, No. 4, October 1967; CH. VIII, Vol XXXVII,

No. 1, February 1967.

While these chapters purport to cover "Concepts and Techniquesof Educational Planning," "Stragegies for Allocating Human andMaterial Resources," and "Economics and Education," they arehigh level, philosophical treatments of these topics. Manyreferences are made to other works which may or may not be atthe same level of generality.

64. HUTCHINS, E.S., Jr., FLINT, B.D., PARTNER, R.C., BAREFOOT, D.B.,and LETSKY, M., CoTputer Models for Manpower and Personnel Manage-ment: State of Current iethnolo with Emphasis on Nav 0 era-ITOWT75.0117WinTngton avy ar : ava Personne Researchia-avelopment Laboratory, April 1973, Report WTR 73-25.

Within the selected field of manpower and personnel managementover 230 computer models are reported and a significant numberare exposed to an examination of their techniques and areas ofapplication. In addition, 102 related studies and programs areidentified. A strategy for performing a technical evaluationis developed and reported, and a functional taxonomy of computermodels in this selected discipline is designed and applied. Areview of the questionnaire technique employed in the data acqui-sition phase of the project, with appropriate recommendations forimprovement, is also included. The analysis of acquired modeldata within the taxonomy framework provides both quality andquantity' appraisals with respect to application areas coveredand techniques employed. An expanded glossary 7f selectedmodeling terms and a bibliography of considerabse size whichresulted from this research effort should prove most beneficialto interested model developers and users. Guidelines for future,needed endeavors are also presented. A by-product of this researchis the sizable Compendium of Models and Related Manpower/PersonnelPrograms and Studies (listed as Appendix "A" and published underseparate cover as WTR 73-25A).

65. HUTCHINS, E.S., Jr., FLINT, B.D., PRATHER, R.C., and BAREFOOT, D.B.,Computer Models for Manpower and Personnel Management: State ofCurrent Technology, &ith Emphasis on Navy Operational Models) -

Appendix "A" - Compendium of Models and Related ManpowergersonnelPrograms and Studies. llashin-geonNaVy Yard: Naval PersonnelReS-bi77-iiidDTvelopment Laboratory, April 1973, Report No. WTR73-25A.

This document is a supporting appendix to a NAVPERSRANDLAB researchstudy which was conducted in response to the desires of the DeputyChief of Naval Operations (Manpower) to ascertain the current state

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of computer modeling technology in the Navy, specifically, thearea of manpower/personnel management planning and resourcesmanagement. Computer model information acquired in the studywas obtained through literature searches and a questionnaireprocess. Data were gathered on Navy, other services, andselected models from industry and other government agencies.The acquired .information has permitted the development of a

very important by-product, "Compendium of Models and RelatedManpower/Personnel Programs and Studies." The Compendium hasimmediate use and application for the research community aswell as operating managers. Because of its size and unique-ness, the Compendium has been separately bound and tailoredto stand alone. The level of detail obtained in the Compendiummakes it the most complete systematic display of computer modelinformation available in the selected field of manpower andpersonnel planning. Its uniqueness lies in its ability todisplay models within a basic model taxonomy framework (themodel taxonomy concept employed is summarized in the Compendiumand discussed at length in the research report), and the func-tional attributes of models are thus grouped to permit tracingof the logical flows between model classes.

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III. EDUCATIONAL TECHNOLOGY

The reports and articles reviewed in this section discuss selectedtopics from nearly all training system functions outlined inSection VI. The literature has been classified according to subjectmatter, which did not result in a one-to-one correspondence with thetraining functions. For example, three of the topic classifications;Educational Planning, Systems Approach to Education/Training, andTask Analysis, all relate to Function 3.0 Analyze and Plan Training.Four of the topic sections; Counseling, Educational Information

System, Training Technique/Media, and Course Design, refer to Func-tion 4.0 Implement Training. The classifications included in thissection are:

o Counselingo Educational Information Systemso Educational Planningo Training Techniques/Mediao Training Feedbacko Course Designo Learning Process Analysiso Systems Approach to Education/Trainingo Task Analysiso Training Cost Analysis

A. COUNSELING

Counseling, as pointed out by Mims and Gains, who are bothmembers of the research branch of the Naval Technical TrainingCommand, plays an important role in the education of an enlistedman.

Mims and Gaines [66] describe the effects of intensified counsel-ing administered to potential failures versus the normal post-failure counseling. They found that intensified counseling provedto be better than the normal counseling. The number of failureswere significantly reduced.

They also performed a study on prescriptive remediation versus thenormal one-week remediation. Prescriptive remediation consistedof a one-hour programmed text of remedial instruction covering a

review of the units most often misunderstood content areas. Thenormal one-week remediation consisted of a review of the materialcovered in a unit of instruction. Their conclusions were thatthere was no significant difference in the number of failures aftertaking either remediation. The only significant conclusion was thefact that one method was a week long and the other was only an hourlong.


Gaines [67] also performed a study on counselor effectiveness as afunction of a personality variable. His study resulted in four con-clusions:

1) Counselors with low scores on the California F-scale, a measureof authoritarianism, are more effective than counselors withhigh F-scale scores.

2) Counselors with low scores on the California F-scale are moreefficient in terms of evaluation by students.

3) There is a positive correlation between authoritarianism on theCalifornia F-scale and authoritarianism of the counselors asmeasured by the authoritarianism items of the counseling evalu-ation questionnaire.

4) The students' estimates of help received and performance changecriteria is positively correlated.

66. MIMS, D. and GAINES, R. N., Preventive Counseling and PrescriptiveRemediation. Millinnton, Tenn.: Chief of Naval Technical Training,Research Branch Report 9-73, March 1973.

This report evaluates the effects of redefining the role of a coun-selor in the AV(A) School so that intensified counseling is admin-istered to potential failures before the trainee takes the unitexamination, as opposed to normal post-failure counseling. Inaddition, two types of remediation were evaluated. An existingsystem of one-week setback review remediation was compared witha self-paced programmed instruction.

Intensified preventive counseling was found to be significantlybetter than the normal post-examination counseling, resulting inan increased proportion of students completing the course. Theone-hour remediation program was not found to be significantlydifferent from the one-week setback program. Trainees did betteron a post-remediation examination than they did on an examinationgiven immediately prior to the remediation program.

67. GAINES, R. N., Counselor Effectiveness as a Function of a PersonalityVariable. Millington, Tenn.: Chief of Naval Technical Training,Research Branch Report 12-73, June 1973.

In military technical training and educational establishments, thelarge number of students compared with the number of professionallytrained counselors, psychologists, and psychiatrists has resultedin the military services' reliance on their senior enlisted mento perform as counselors in many situations. These men have littleformal training as counselors but are experienced instructors/

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supervisors, as well as having much experience in their owntechnical specialty. This study investigates the role of apersonality variable in military designated counselors inrelation to the subsequent grade performance of the studentscounseled. The counselors were also evaluated on the basisof counseling evaluation forms filled out by the students.It was hypothesized that counselors with low scores on theCalifornia F-scale would be more effective as measured byboth measures.

Twenty-five Chief Petty Officers and Marine Corps Senior Non-Commissioned Officers from the Avionics Technician School atthe Naval Technical Training Center, Memphis, working ascounselors, volunteered for this study. The counselors filledout the California F-scale and subsequently recorded the nameof each student that they contacted during a specified periodof dm.

The study was cross-sectional in that it sampled all partici-pating counselors and their student contacts during one unitor phase.

Results of the study support the hypotheses that counselorsthat scored lower on the F-scale were better counselors inthat their students did better or had positive changes ingrades, where counselors with higher F-scale scores had stu-dents that did not improve or got negative grade changes.

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B. EDUCATIONAL INFORMATION SYSTEMS

An example of an educational information system already in useis described by Wright [68). The system is used as a pupiltracking/teacher monitoring system. Braunfield and Fosdick[69) describe an automatic teaching device designed to teacha number of students concurrently, but independently, by meansof a single, central, high speed computer. Bushnell and Borko[70) describe information retrieval systems and the role theycan play in education.

68. WRIGHT, D.L., "The Mesa Arizona Pupil Tracking System," JPL Quar-terly Technical Review, Volume 2, Number 4, January 1973.

A computer-based Pupil Tracking/Teacher Monitoring System wasdesigned for Mesa Public Schools, Mesa, Arizona. The estab-lished objectives of the system were to:

1) Facilitate the economical collection and storage ofstudent performance data necessary to objectivelyevaluate the relative effectiveness of teachers,instructional methods, materials, and applied con-cepts.

2) Identify, on a daily basis, those students requiringspecial attention in specific subject areas.

The system encompasses computer hardware/software and integratedcurricula progression/administration devices. It provides dailyevaluation and monitoring of performance as students progress atclass or individualized rates. In the process, it notifies thestudent and collects information necessary to validate or invali-date subject presentation devices, methods, materials, and meas-urement devices in terms of direct benefit to the students. Thesystem utilizes a small-scale computer (e.g., IBM 1130) to assurelow-cost replicability, and may be used for many subjects ofinstruction.

69. BRAUNFELD, P.G. and FOSDICK, L.D., The Use of an Automatic ComputerSystem in Teaching. Urbana, Illinois: University of Illinois,September 1062.

Plato II is an automatic teaching device designed to teach anumber of students concurrently, but independently, by meansof a single, central, high speed computer. Only two studentsites have been constructed thus far, but, in principal, thenumber of students that can be taught by Plato II is limitedonly the capacity and speed of the central computer. Thepower of such a computer based teaching system stems from itsability to ask complex questions, judge the students' answersto these questions, and take an appropriate course of action

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on the basis of student responses. The computer also keepsdetailed and accurate records of student performance, whichare extremely useful guides to improving course content.The paper reports in some detail, a study using Plato IIto teach nine undergraduate students a portion of a coursein computer programming. Some analysis and interpretationof data gathered by the computer during the study are repre-sented. The apparent effectiveness of Plato II as ateacher, as well as the kinds of problems encountered inpreparing lesson material for an automatic system, isdiscussed.

70. BUSHNELL, D. and BORKO, H., Information Retrieval 6ystems andEducation. Presented at the American Psychological AssociatedConvention, St. Louis, Missouri, September 1962.

An information retrieval system is defined as a man-machinesystem combining human intelligence and electronic and photo-copying equipment for the purpose of gathering, classifying,and storing of factual and textual material, and for retriev-ing and disseminating this information upon demand.

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C. EDUCATIONAL PLANNING

The planning stage of an educational system is the key to itssuccess or failure. Kraft [71] points out the need for pre-dictive models which will help educational administrators indecision making. With such models, educational administratorscould predict the success or failure of an educational systembefore it was implemented. Bailey [72] describes the role ofhuman factors in an educational system, and how proper planningshould account for these factors. Thompson and Harrison [73]describe a self audit system. No matter how well an educationalsystem is planned, the variables used in planning are constantlychanging. These changes should be absorbed by the educationalsystem through a self audit system.

71. KRAFT, R.H.P., "Manpower Planning and Its Role in the Age ofAutomation," Review of Educational Research, Volume 40, Number 4.

The author discusses the kind of occupational training and tech-nical education the American school system should supply, andthe constant renewal and development of that education by changesin knowledge and in the manpower needs of industry.

72. BAILEY, S.K., "Educational Planning: Purposes and Power," PublicAdministration Review. May/June 1971.

The author enumerates five subpurposes or instrumental goals ofeducational planning in an urban context and discusses the meansof achieving these goals.

1 Mastery of basic language tools2 Exposure to variety of domains of work and pleasure3 Experience in multiple contacts with a variety of peoples4) Mastery of (or appreciation of) manipulative skills5) Knowledge of consequences in the field of both ecological

and human relationships.

73. THOMPSON, B. and HARRISON, C., Educational Self Audit. Orlando,Florida: Naval Training Equipment Center, July 1972.

The training self audit is used by an activity to determine whereit is; where it is heading under present policies, procedures andprograms; what its goals should be; and whether revised plans oractions are needed to meet those goals.

The self audit has been developed into a systematic and detailedprocedure through similar studies of Naval training programs.For clarity and simplification, the program has been divided intothe following six separate but related segments:

1) Philosophy and Goals2 Buildings and Facilities3 Management4 Staff and Faculty5) Curriculum6) Instructional Support.

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O. TRAINING TECHNIQUES/MEDIA

The papers reviewed in this category included one survey paper,one paper dealing with performance prediction, two studiescomparing Computer Assisted Instruction (CAI) with ProgrammedInstruction (PI) and conventional classroom, and nine papersand reports dealing with the design selection and implementa-tion of training media.

Since media implementation and training methodology are oftenindistinguishable, no attempt was made to separate techniquesfrom media where both were discussed in the same paper or re-port.

Seidel [74] contends that the introduction of the computer withits attendant capability for student interaction (e.g., CAI) re-quires that the traditional training process be reviewed in orderto take full advantage of these capabilities.

Long, O'Neal and Schwartz [75] and O'Neal [76] present data in-dicating that mere replacement of conventional instruction withCAI does not automatically reduce completion times or improvelearning performance or student attitudes. Their findings showthat extensive course revision should accompany the introductionof CAI and that similar course revision might produce comparableresults when applied to conventional instruction.

In the realm of training media and selection, a rough divisioncan be made between those studies concerned with the Physicsof Learning in an artificial environment and those directed atimprovement or replacement of existing training systems andthe design of new operational training systems.

Brown and O'Neil [77] discuss the problem of media selection(in this case teletype vs CRT terminals) when rapidly chang-ing technology may remove cost differentials between media.Individuals tasked with media selection must remain cognizantof all advances in instructional technique regardless of current'media cost because of the condition of constant change.

Parker [78] and Braby, et al., [79], each present formal methodsfor media selection where a large number of potential media may beapplicatle. Parker concentrates on translation of learning object-ives into media characteristics and aims at the nonspecialist.iiraby, et al., propose a system requiring expertise on the partof the user but one which includes a computerivi cost optimizationmodule.

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Attempts to measure the effectiveness of particular trainingtechniques and the use of measured data in system design andprediction of performance, represents an important sub-setof the general topic of media selection and system design.Hansen [80] discusses the application of various measurementtechniques specifically to CAI courses. Difficulties inmeasurement of CAI vs conventional instruction, are enumerated,again indicating that the two instructional methods are notamenable to direct comparison. Caro [81] presents a formalmethod for evaluation of the general learning objectiveswhich can be achieved using different devices with the in-tention of measuring the potential of any device if applied toa training situation for which it was not specifically de-signed. The study indicates that such substitution is oftenemployed without adequate prior analysis, resulting in infer-ior training. Predictions of performance in a learning situa-tion, based on mean task scores and quantitative task indexvalues, is discussed by Whaton [82]. Findings indicate thatthe proposed methodology is more effective early in the learn-ing cycle, but results were deemed sufficiently successful towarrant further investigation; a conclusion which was notshared by the reader.

Application of task analysis and analysis of human factors intraining devices and in performance aids, are considered bySmode [83] and Folley [84]. Smode postulates a formal methodfor evaluating the human factors aspects of a synthetic train-ing system and discusses the application of the proposed methodto an existing training system. Similar methods are requiredin the design of performance aids which can be considered asspecial types of training equipment to be used on a continuingbasis in an operational environment.

A nine-year program of research into maintenance of electronicequipment is synopsized by Rigney [85]. The subject matter,which ranges from panel design to high order languages fordevelopment of CAI modules, does not permit further condensa-tion. This is an excellent, broad spectrum reference. Adapt-ive training, in which the system automatically adjusts taskdifficulty to student proficiency, is discussed by Kelley [86].Three methods of adaptation are discussed, but no generalizedinferences concerning the application of adaptive trainingare drawn.

Generic methods for student motivation, not necessarily re-lated to instructional methodology, media, or technique, arecovered extensively by Ugelow [87]. This report is moreapplIcable to instructor training at a theoretical level thanto design of media-oriented systems.

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74. SEIDEL, R.J,, "Computers In Education -'The Copernican Revolutionin Education Systems.' Computers and Automation; March 1969.

The exploitation of the computer as a tool remains to be accom-plished. Educational research is at the very beginning of estab-lishing the new premises for instructional theory development andrevolutionizing the horizons of education and training. In thepast, research in psychology had been directed toward describingthe learning process, and subsequent to this, attempts had beenmade to prescribe for the instructional process.

The author concludes that, with the computer and the environmentsit makes possible, man stands at the threshold of being able tocoalesce the study of learning and the prescribing of instruction.

To accomplish this, however, man has to relinquish his egocentricrole as usually understood in teaching. Instead, interdisciplinaryteams will produce instructional materials. The interdisciplinaryinstructional team of the future will design the contents of courses,but not as it prevails in traditional instruction. The system forinformation exchange between learner and knowledge will become farmore explicit, more efficient, and more reliable.

The use of computerized educational and training systems will pro-duce astonishing successes.

75. LONG, H.S., O'NEAL, L.R., and SCHWARTZ, N.A. Exploratory Resultsfrom the Application of Computer Assisted Instruction to IndustrialTraining. Poughkeepsie, New York: International Business MachinesCorporation,Systems Development Division, January 24, 1969,TR 00.1790.

Since late 1963 the Field Engineering Division of the InternationalBusiness Machines Corporation has been investigating the feasibilityof using computer assisted instruction to provide a means for solvinga number of its training problems. As a part of this investigation,a series of four research studies was carried out by the authors.These studies were:

1) A Study of Computer Assisted Instruction in Industrial Training.

2) A Study of Remote Industrial Training via Computer AssistedInstruction.

3) A Model of a Nationwide Computer Assisted Instructional System.

4) Computer Assisted Instruction Applications Research in IBMField Engineering Education.

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This paper summarizes the studies by providing the setting foreach, the intent, a systems description, and the major findingsthat have contributed to the implementation of a nationwide fie14instructional system in the Field Engineering Division. Theimplementation is based, in part, on the study results whichindicated that employees taught via remote terminals developedfavorable attitudes toward CAI and generally learned as effectivelyand efficiently as when taught via other forms of self-study or theconventional classroom.

76. O'NEAL, L.R., CAI Applications Research in IBM Field EngineeringEducation. Poughkeepsie, N.Y.: InternatiFirBusiness MachinesCorporation, Systems Development Division, April 17, 1968, TR00.1726.

This paper summarizes Field Engineering Education's CAI applicationsresearch activity during 1967. It describes the rationale for theselection of specific CAI projects. it outlines the research pro-cedure employed, including the development of measurement tools,establishing control and experimental groups, administration oftests, analyzation of data, and report preparation. A summary ofthe data from each project followed by a comparison chart for allprojects is shown and the significant findings discussed.

Significant differences were found favoring three CAI courses in"time to complete" and two CAI courses in "attitude toward course."Significant differences were found favoring two conventional coursesin "performance score," one conventional course in time to complete,and two conventional courses in attitude toward course. In the re-maining course comparisons, no significant differences were foundin performance score, time to complete,or attitude toward course.

77. BROWN, B.R., and O'NEIL, H.F., Computer Terminal Selection; SomeInstructional and Psychological Implications. Tallahassee, Fla:Trorida State University, 15 May 1971, Report No. CAI-TM-37.

Factors which have previously provided the basis for decisions as tothe use of CRT or teletype terminals in computer-assisted instructionmay be decreasing in importance. Specifically, differential costfactors and teleprocessing capability may no longer provide a basisfor differentiating between CRTS and teletypes. In the paper, inwhich findings from several experiments are reviewed, instructionalani psychological implications of instructional terminals are dis-cussed. The major terminal characteristics discussed are cost, tele-processing capability, presentation rate, and display mode. Themajor terminal characteristics discussed are cost, teleprocessingcapability, presentation rate, and display mode. The major instruc-tional and psychological implications discussed are device memory loadfactors and instructional time and efficiency. Student characteristicsof intelligence and anxiety are discussed in relation to instructionalterminal characteristics.

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78. PARKER, J.F., Jr., and DOWNS, 3.E., Selection of Training Media.Arlington, Va.: Psychological Research Associates, Mitrix Corp.,

.September 1961, ASD TR 61 -473,

The selection of training media in support of military trainingprograms represents an important area of concern. Training equip-ment exercises considerable influence on the way in which trainingprograms are conducted, upon their effectiveness in accomplishingobjectives, and upon the total cost of the program. This report isdesigned to assist a training analyst faced with the problem ofselecting specific training aids and devices to be used in supportof the development of the personnel subsystem of a military system.The translation of statements of desired personnel performances andcapabilities, as presented in Qualitative and Quantitative PersonnelRequirements Information and task analysis documents, into trainingobjectives is discussed. The effectiveness of various trainingmedia in meeting specific training objectives is indicated andjustified in terms of available objective evidence. An example ispresented illustrating the manner in which training media areselected in support of a typical Air Force operator position.

79. BRABY, R., DR., MICHELI, G.S., DR., MORRIS, C.L., Jr., and OKRASKI,H.C., P.E., Staff Study on Cost and Training Effectiveness of Pro-posed Training Systems. Orlando, Florida: Training Analysis andEvaluation Group, Naval Training Equipment Center, 1972, TAEGReport 1.

This report describes the activities performed during a staff studyon the cost and training effectiveness of proposed training systems.

Development of a Training-Effectiveness and Cost-Effectiveness Pre-diction (TECEP) model has begun. It will eventually contain thefollowing elements; task description and analysis, characteristicsof student population, training tasks and training stages, a methodfor the determination of useful media options, media cost factors,guidelines for substitution and transfer, training program of prim-ary media and allowable substitutions, linear program to optimizefor least cost, and a report including economic analysis andrecommendations.

An application of the TECEP model using the TA-4 advanced jet train-ing system was performed to test the feasibility of the model. In-cluded in the discussion of the application are a training analysis,training media mix options, cost factors for the TA-4 aircraft andtraining media, and TA-4 training system cost/training effectiveness.

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80. HANSEN, D.N., and JOHNSON, B.F., Measurement Techniques for Indivi-dualized Instruction in CAI. Tallahassee, Fla.: Florida StateUnTWrsity, 1 May TOTTPeport No. CAI-TM-35.

Individualized instruction presents problems in measurement whichchallenge the conventional measurement paradigms. Taking into con-sickration the problems of item variance characteristics of CAI, idio-syncratic learning sequences, and lack of a model for effectivenessassessment, the paper reviews various measurement techniques used atthe Florida State University CAI Center. The R&D strategies focuson two major goals; measurement providing information on prioritiesfor revision within the CAI course materials, and measurementspeaking directly to the effectiveness of the instructional process.Measurement techniques are related to three levels of coursecharacteristics; microframe, concept segments within a CAI course,and course effectiveness models. Foreseeable future trends arebriefly discussed.

81. CARO, P.W., Equipment- Device Task Commonality Analysis and Transferof Training. exandria, Va.: Human Resources Research Eganization,June 1970, Report No. HUMRRO-TR-70-7.

Procedures were developed to enable training personnel, system-atically and objectively, to determine the potential utility oftraining devices for teaching how-to-perform missions in operationalequipment. The procedures allow comparison of operational taskstimulus and response elements with corresponding elements in syn-thetic training equipment. On the basis of such information, train-ing programs consistent with the psychological principles underlyingtransfer of training may be developed. The procedures, termed TaskCommonality Analysis, were developed in connection with an Armyrotary wing instrument flight training program.

82. WHATON, G.R., MIRABELLA, A., and FARINA, A.J., Trainee and Instruc-tor Task Qualification: Development.of QuantitativkIndices and aPFRIEfTW7MRETTOTogy. Darien, Conn.: Dunlap and-71-soc., inc.,Muary 1971.

An exploratory study was undertaken as part of a program to developquantitative techniques for prescribing the design and use of train-ing systems. As a first step in this program, the present studyattempted to compile an initial set of quantitative indices, deter-vine whether these indices could be used to describe a sample oftrainee tasks and differentiate among them, develop a predictivemethodology based upon the indices, and assess that methodologyusing studies in the literature. The compilation included thedisplay-evaluative "Index, a set of panel layout indices, and aset of tas:: rating scales. These indices were applied to taskar.alyt'c data, collected on Sonar operator trainers at Fleet Sonar

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lACG RPORT NO. 12-1

School, Key West, Florida. Application of the indices proved feasi-ble, and differentiation among three training devices, and withinfour trainee sub-tasks (set-up, detection, localization, and class-ification) was possible. The predictive method which was generatedwas an adaptation of the standard multiple regression model. Meantask scores replaced the usual individual criterion scores, andquantitative task index values were used as predictor scores. Thisadaptation was tested using data from published studies on tracking.Significant multiple correlations using task indices were found forcriterion data obtained during early stages of practice. A combin-ation of task and training indices did predict later performance.This result supported the contention that a prescriptive methodmust include "training" as well as "task indices" in order toaccount for advanced levels of proficiency.

83. SMODE, A.F., Human Factors Inputs to the Training_Device DesignProcess. Darien, Conn.: Dunlap and Assoc., Inc., September 1971.

The report presents guidelines for achieving human factors inputsto the design of synthetic training systems. It provides a methodfor design and organizes training concepts and data supportive tothe human factors specialist in deriving the functional specifica-tions for the design of any complex training device. Three majorsections are provided. The first of these presents an organizedmethod for achieving human factors inputs to training systemdesign. Another section presents concepts and data applicable tothe design of training devices. The final section provides ademonstration of the human factors design process for a complextraining system.

84. FOLLEY, J.D., Jr., A Preliminary Procedure for SystematicallyDesigning Performance Aid-s. Pa.: American institutefor Research, OcUber 1961.

Performance aids are devices or documents that facilitate task per-formance by humans in a system. These supplementary aids to perfor-mance can enhance the overall quality of a system by assisting inachievement of more nearly optimal man-macnine function allocation,by reducing the_level of requirements on selection, training, andmanning, or by raising on-the-job performance levels. Four stepsin the design of performance aids are presented:

1) Identification of task elements for which aids should beprovided.

2) Determination of appropriate functional characteristicsof aids for these task elements.

3) Specification of the physical design characteristics ofthe aids to carry out the functions.

4) Evaluation, modification, and updating of the aids.

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Supplementary data on capabilities of performance aids are presentedfor use with the procedure. The procedure is .untried and of neces-sity uses stopgap solutions to problems on which much research ordevelopment is needed.

85. RIGNEY, J.W., Research in Electronics Maintenance and Maintainability,Multidimensional Scalin tom uter Personnel Selection, Technician1rainth . os ngeles, a outhern California University,cto er 969.

Research was performed in four major areas; maintenance and maintain-ability of electronic equipment, multidimensional scaling, computerpersonnel selection, and technician training. Examples of researchresults were criterion measures for computer programmers and systemsanalysts, and a job aid and troubleshooting manual for troubleshoot-ing a transceiver. Other significant contributions were the devel-opment of quantitative models of the troubleshooting process, thedevelopment of an automated procedure for estimating time costs ofserial tasks, the application of multidimensional scaling to iden-tifying psychological variables in understanding electronic circuitsand in threat evaluation in CIC, the development of job task perfor-mance tests for maintenance of communications and radar equipment,the specification of training objectives for this equipment, andthe development of a program for implementing computer assistedperformance training that generates the interaction with the stu-dent from models of the tasks to be learned.

86. KELLEY, G.R., What is Adaptive Training? Santa Monica, Calif.:Dunlap and Assoc., Inc., December 1969, Report No. P547-556.Presented at New England Psychological Association Annual Meeting,November 29-30, 1968.

Adaptive training is training in which the problem, the stimulus,or the task is varied as a function of how well the trainee per-forms. The concept and techniques of adaptive training are intro-duced and a comparison drawn between different methods of adapta-tion. The preferred method keeps measured performance constantby changing the difficulty of the task. Fundamental Characteris-tics of adaptive trainers are enumerated and contrasted with fixedtrainers. The implementation of an adaptive training system isthen discussed under the following headings:

1) Choosing an adaptive variable

2) Measuring performance

3) The adaptive logic

4) Error standard and difficulty level

5) Knowledge of results displays.

A concluding section cautions against expecting adaptive techniquesto correct training devices with inherently poor training validity.

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87. UGELOW, A., Motivation and the Automation of Training, A LiteratureReview. Wright-Patterson AFB, Ohio: Aerospace Medical Division,6570th Aerospace Medical Research Laboratories, March 1962, ReportNo. MRL-TOR-62-15.

Contr-olling the motivation of learners in their continuing use ofthe new auto-instructional devices could become a serious problem,since neither the devices themselves nor the performance knowledgethey provide seems:sufficient to maintain extended participationin the instruction. A selective review of the literature on know-ledge of results, praise and reproof, competition, task interrup-tion, and readability suggests techniques for better controllingsuch participation. Potentially useful applications are discussed,and limited try-out of variations, both within the program andinstructional environment, is encouraged.

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E. TRAINING FEEDBACK

Training feedback is a significant part of an educational system.Federico [88] describes the critique form method of obtaininguseful information for training feedback. Standlee, Bilinski,and Saylor [89] describe the structured interview method ofobtaining training feedback on the maintenance of Navy elec-tronics systems. Biliniski and Saylor [90] show another exampleof the interview method of obtaining training feedback in a non-electronics, Class "A" curriculum environment. Angell, Shearer,and Berlinger [91] demonstrate that analytic techniques can beapplied successfully in dealing with what often seems the hope-lessly complex and disorderly business of training performanceevaluation. In addition, new directions are pointed out whichhinge on the development and application of computers to train-ing tasks.

88. FEDERICO, P., Development of Psychometric Measures of StudentAttitudes Toward Technical Training: Reliability and FactorialValidity. Brooks AFB, Texas: Air Force Human Resources Lab,November 1970, Report No, AFHRL-TR-70-37.

This investigation is the Phase 1 effort of a task which under-takes to develop a new student critique form for Air TrainingCommand (ATC). Specifically, it deals with the identificationof valid and reliable psychometric measures of student attitudestoward Air Force technical training. Two critique form prototypeswere developed using a Likert -type and a Guttman-type configuration.These were administered in a counterbalanced order to samples ofofficers, NCO, and airmen enrolled in an ATC technical school.Multiple-factor analyses and multiple discriminant function anal-yses were performed for the scored responses of the subjects tothese critique forms. Test-retest reliability and factorial anddiscriminative validities were established for each of the proto-types. On the basis of the statistical analyses of the two forms,the Likert configuration was recommended for further development.Eight Likert factors, or unidimensional scales, were defined;Instructor Competence, Training Management, Specialty Training,Training Impressions, Training Facilities, Repetitious Instruction,Intelligible Media, and Textbook Utility. Because of demonstrateddifferences between rater groups, it was also recommended thatgroup-specific forms be developed.

89. STANOLEE, L. S., BILINSKI, C. R. and SAYLOR, J. C., Proceduresfor Cbtaining Trainiqgjeedback Relative to Electronics Main-tenance. San Diego, Calif.: Naval Personnel and TrainingResearch Lab, January 1972, SRR 72-13.

This report compares different methods of obtaining trainingfeedback; experimental, mail-out questionnaires, performancediary, analysis of existing records, rotation of Fleet and

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training personnel, and structured interview. The reportdescribes how the structured interview is used to collectfeedback information on six electronics systems. The fieldtest results are summarized. The authors conclude that thestructured interview is a "highly satisfactory method ofobtaining training feedback information."

A bibliography covering previous field studies for obtainingtraining feedback information is included in the report.

90. BILINSKI, C. R. and SAYLOR, J. C., Training Feedback to theNavy Storekeeper Class "A" School. San Diego, Calif.: NavalPersonnel and Training Research Lab, January 1972, SRR 72-114.

Data was obtained from Storekeepers, both from the Fleet andshore, concerning their experiences in performing assignedtasks. Findings include the most frequently performed tasksand those causing the most difficulty. Specific recommenda-tions for training are included.

91. ANGELL, D., SHEARER, J. W., and BERLINGER, D. C., Study ofTraining Performance Evaluation Techni ues. Palo Alto,Ca if.: American Institute for Research, October 1964,NAVTRADLVCEN- 1449 -l.

This report discusses performance evaluation in the trainingenvironment, specifically in training situations involvingthe use of simulators and other complex training equipment.The important variables involved in developing a system ofperformance evaluation are seen as (1) types of behaviors,(2) types of measures or mensural indices, and (3) types ofinstruments for recording performance. Factors relating tothese variables are discussed, and some of the interrela-tionships among the three variables are presented. Ani;lustrative application of an automatic training evaluationsystem is given.

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F. COURSE DESIGN

Rundquist [92] describes a systematic procedure for the designof training courses. It also has implications for the designof training programs. The procedure is developed in a mannerwhich (1) takes account of principles from the many technicaland professional fields contributing to training technology,(2) keeps course design completely job assignment oriented, and(3) puts the emphasis on the instructor's dealing directly withthe student to facilitate his learning. Stern [93] points outthat when subject-matter experts are used for developing orrevising course content, care should be exercised in the selec-tion of these judges. West and Rundquist [94] demonstrate thatthe course design procedure is flexible and can be adapted foreffective revision of a high level officer training course.

92. RUNDQUIST, E. A., Job Training Course Design and Improvement(Second Edition). San Diego, Calif.: Naval Personnel andTraining Research Laboratory, September 1970, SRR 71-4.

The second edition of the course design manual is a thoroughrevision of earlier editions. The manual is designed to assistinstructors in developing and improving job-related trainingcourses. Major changes from earlier editions include morecareful definitions of training and training related terms;a general clarification of concepts and procedures, especiallythose concerned with job and skill analysis for trainingpurposes; more emphasis on principles of developing training

exercises; a more thorough consideration of the importance andmeans of adapting individual differences; and more emphasison the significance of the course mission for course design.Examples from a wide variety of duty assignments are included.

93. STERN, H. W., The Reliability of Expert Opinion in SpecifyingCourse Content. San Diego, Calif.: Naval Personnel and Train-ing Research Laboratory, December 1970, Technical BulletinSTB 71-4.

In the development and revision of curricula, subject-matterexperts are frequently called upon to aid in specifying skillor knowledge requirements and to provide opinions on the degreeof importance associated with the requirements for the establish-ment of a curriculum. If, however, these expert judgments arenot reliable, their validity is automatically questionable. Theeffect of individual differences in reliability may not be givensufficient consideration.

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In order to evaluate this problem, data from a previous studywas supplemented and analyzed for rate-rerate reliability of agroup of Navy subject-matter experts, including an analysis ofindividual differences.

The rate-rerate reliability for all 16 judges over a six-monthperiod was .59. Absolute changes in rating averaged slightlyover half a scalar unit on a 6-point scale. When four raterswere selected on the basis of their individual reliability,their combined rate-rerate reliability was .68. Other measuresindicate the selection of raters on an index of individualstability may increase relaiability, although the effect thishas on validity is not known. These findings indicate that alarge number of raters does not insure high reliability, andthat selecting a subset may result in an increase in precisionin overall reliability.

94. WEST, C. M. and RUNUQUIST, E. A., Ex loratory A lication ofCourse Design bious

Command d-Orientatiom Course: A ProposalfVrImplementation.San Diego, Calif.: NavalliFSonnel and Training Research Lab,March 1972, Research Report SRR 72-16.

Describes how the course design procedure was applied to theredesign of a high level Navy officer training course. Containsa model for course organization, specification of example train-ing tasks and methods of presentation, and enumeration of generaldevelopmental considerations.

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G. LEARNING PROCESS ANALYSIS

Dyer [95] describes the problems of measuring the performance ofan educational system using indicators such as student-teacherratios, the physical plant, or system output as measured byachievement test scores. Pask [96] describes a two-part studyof learning strategies and learning set. The first part involvesexperiments with real-life subjects. The second part is concernedwith a computer simulated model of learning, which, when inter-preted, constitutes a theory of learning. Tucker [97] gives asummary of activities which involved development and evaluationof theories and techniques for investigating the structure ofindividual differences in psychological phenomena. Taylor,Montague, and Hauke [98] describe a three-phase project toassess the impact of aptitude differences on learning perfor-mance. Thomas [99] describes her procedure for validating thebasic test battery. The basic test battery was developed to pre-dict performance in Navy schools. Narendra and Shapiro [100]and [101) discuss the concepts of automata theory and mathe-matical psychology learning theory in relationship to the usualnotion of a performance index in a control system and as amethod for the determination of optimal parameter values forcontrol systems with multimodal performance criteria. Studyof the actual process of learning remains one of the major prob-lems facing educators today. The sampling of articles in thissection brings this point home loud and clear. The first hurdleto be overcome is the identification of the variables which con-trol the process. The majority of papers reviewed address thisproblem, There seem to be as many approaches to this problemas there are researchers. Everyone has solved a small part ofthe problem, yet no one has the total answer.

95. DYER, H.S., "Can We Measure the Performance of Educational Systems?"National Association of Secondary Schools, Bulletin 54, May 1970.

This article deals, in general terms, with the problem of measur-ing the performance of an educational system. It points out faultsin measurement by physical plant and student-teacher ratios, aswell as problems using standard achievement tests.

96. PASK, G., Learning Strategies and Teaching Strategies. Richmond,England: System Research, Ltd., June 1960.

Results are reported 9f human learning experiments and computersimulations. Experiments focused on - (1) how a subject directshis attention and explores the problem environment created bythe task to be learned and (2) how the subject's learning processcan be facilitated by conversational, or partially cooperative,teaching systems, in practice, CAI systems. In all experiments,the subject interacted with an automaton responsible for con-trolling the experimental environment. Under some conditions,

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the automaton was a procedural device and imposed behavioral con-straints that represented rules of the task but permitted thesubject freedom, particularly in his choice of a strategy. Underother conditions, the automaton was a simple adaptive teachingmachine or a conversational machine. The simulation incorporatedsubprograms representing the subject and automaton respectively.The gross action of the metasystem is explained in terms of thetheory of self-organizing systems. Different subjects exhibiteddifferent strategies for learning the same skill. The strategiesmay or may not be able to be fitted to aspects of mental organi-zation of which the subject is often imperfectly aware. Resultsshow that an adaptive metasystem is a better instructional instru-ment for the skill studied than either the attention directingprocess in a free learning subject or a more restricted, singlestrategy teaching system. The computer simulation of the learn-ing process in the subject is a psychologically oriented artifi-cial intelligence program, not a stochastic mode. It is heter-archic in that its structure involves several separable butinteracting hierarchic systems.

97. TUCKER, L.R., Final Report For Contract U.S. Navy/00014-67-A-305-0003. Urbana, Illinois: Illinois University, Dept. pf Psychology,February 1971.

A summary is given of activities which involve development andevaluation of theories and techniques for investigating the struc-ture of individual differences in psychological phenomena. Partic-ular areas of investigation were; differences in predictive systemsfor individuals, differences in psychological scaling, differencesin learning and growth, factor analysis (including three-modefactor analysis), and analysis of binary data.

98. TAYLOR, J.E., MONTAGUE, E.K., and HAUKE, R., The Interrelation-ships of Ability Level, Instructional System, and Ski-11 Acquisi-tion. Alexandria, Va.: Human Resources Research Organization,December 1970, Presented at the symposium of American Psycho-logical Association Convention, held at Miami Beach, Florida, onSeptember 1970.

This paper describes an assessment of the impact of aptitude dif-ferences on learning performance. As a result of these tests,instructional strategies are being developed to make efficienttraining programs for men of differing aptitude levels. Obser-vations were that the high level group did better when left with-out a structured training program; that the middle range was alsoable to work at its own speed. Low aptitude groups, however,required a complete structured program in which the instructionalsequence is kept down to small steps presented on an elementarylanguage level.

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99. THOMAS, P.J., The Relationship between Navy Classification TestScores and Final School Grades in 98 Class "A" Scgols. SanDiego, Cafi?.: Naval Personnel and Ti-A-acning Researanaboratory,April 1972.

There are substantial correlations between the Basic Test Batteryand "A" school grades. Ninety-five percent of the relatively lowaptitude was graduated successfully. Changes (lowering or raising)of the cutting scores for certain schools should be considered.

100. NARENDRA, K.S., and SHAPIRO, I.J., The Use of Psychological Learn-ing Theory Models in the Design of Adaptive Systems. New Haven,Conn.: Yale University, October 1969, Reporto. P 103-7.

A method for the determination of optimal parameter values forcontrol systems with multimodal performance criteria is based onthe theory of finite-state automata. This method is discussed interms of its implications in the dual context of learning modelsin mathematical psychology. The various mathematical models con-sidered in the literature are described, the design and applica-tion of the optimal automaton are discussed, and the implicationsof this model in learning theory are considered.

101. SHAPIRO, I.J., and MARENDRA, K.S., Use of Stochastic Automata forParameter Self-Optimization with MultimodirPerformance Criteria.New Haven, Conn.: Yale University, Uept. of Engineering and AppliedScience, October 1969, Report No. P 352-360.

The application of stochastic automata to adaptive parameter optimi-zation problems is considered. The fundamental problem is that ofrelating the concepts of automata theory and mathematical psychologylearning theory to the usual notion of a performance index in acontrol system. Consideration is given to a number of possibleautomata structures, linear and nonlinear. One particular linearmodel is derived with optimal rather than expedient properties ofconvergence. A basic feature of this model is that it is based ona system response set of rewards and inactions. The latter beingsubstituted for the more common penalty responses. This choice ofresponse set is directly related to the achievement of the desiredbehavior. Simulations are described for the maximization of multi-modal performance functions intentionally constructed to demonstratethe use of the method in situations where relative extrema occur.An example is also given of the automaton as a direct adaptive con-troller for a third order control system.

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H. SYSTEMS APPROACH TO EDUCATION /TRAINING

The great majority of papers in this category addressed verygeneral questions in general terms.

Hartley [102] and Burgess [107] both issue caveats; Hartleyagainst inappropriate use of systems analysis and too readyacceptance of results. Burgess warns against design faultsresulting from failure of elements within a system designteam to recognize the system, rather than subsystem, goals,

Three of the papers are tutorial in nature, intended to acquaintthe now-expert with various phases of human and systems engi-neering. Mayer [104] deals with human engineering, gives abrief history of this discipline, and examples of applied humanengineering techniques. Ammerman [105] describes the role ofthe human in complex systems and suggests that, in this context,the human must be considered in a different way from thetraditional man-machine problem if his role in the system isto be optimum. .Coulson [108] describes the application ofsystems analysis to educational systems, at a general level,and attempts to make more explicit some of the jargon used bysystems analysts and misunderstood by educators.

Sisson [103] is concerned specifically with training in theNavy. He outlines an approach to the analysis of the navaltraining system and advocates the formation of a trainingengineering group. The goals and methods outlined by Sissonare very similar to ADO 43-03X.

The remaining two papers describe analysis done for, or on,specific training systems. Kodama [106] introduces a formalmathematical approach to training evaluation and describesthe application of this technique to the training of craneoperators. Hall [109] gives an overview of a study on CoastGuard air training, designed to optimize the mix of flight,simulator, and classroom training. Consideration is alsogiven to training effectiveness evaluation in this context.

102. HARTLEY, H. J., "Limitations of Systems Analysis," Phi DeltaKappan, 50: 515-519, May 1969.

The primary objective of this article is to identify majorlimitations of the various systems approaci;es to educationalplanning. Most of the current systems literature tends to bedescriptive rather than critical. It is Mr. Hartley's hopethat the focus on limitations -- he lists twenty-five -- willprovide a more realistic understanding of the advantages ofsystems analysis.

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103. SISSON, R. L. Orivizingand Planning for Engineerin Im rovedTraining Systems. Princeton, N. J.: Mathematica, Inc., tiarch1911, NO0014-70-C-0362.

This is one of the studies which is directly related to ADO 43-03X.Several different kinds of models are discussed. A strong needis stated for the development of a Training Improvement Engineer-ing Group in the Navy. Some of the suggested approaches are verysimilar to those being used in the current IBM approach.

104. MAYER, S. R., Human Engineering in the Design of InstructionalSystems. Bedford, Mass.: tlectronic Systems Division, AirForce Systems Command, September 1964.

A conceptual model is proposed for use in the application of humanengineering principles and techniques to the design of instruc-tional systems. The trainee and instructor are viewed as operatorswithin an information system. To illustrate this model and itsapplication, examples are drawn from the literature and fromcurrent research on instructional systems. A preliminary humanengineering guide is outlined which presents factors critical todesign decisions for instructional systems. The model and guideattempt to counteract current tendencies toward premature standard-ization of instructional system structure, and to bring instructionalsystem development into the main stream of the applied science ofhuman engineering.

105. AMMERMAN, H. L., and MELCHING, W. H., Man in Control IL119101.Automated Systems. Alexandria, Va.: Human Resources ResearchOrganization, May 1971. Presented at the annual Army Human FactorsResearch and Development Conference (16th), Fort Bliss, Texas,October 1970.

The identification of what man should do as a decision maker andcontroller in the newly evolving man-machine systems is considered.Among the topics discussed are man's underlying basic functionsin a complex system, task activities for individual jobs and theiranalyses, and training and the design of operational job positions.

106. KODAMA, F., " An Approach to the Analysis of Vocational Educationand Training Requirements," Mana ement Science, Vol. 17, No. 4,December 1970, Report No. PB 8-B 91.

Systematic approaches to the problems of education and trainingare difficult because so many social and psychological variablesare involved.

As education and training can be viewed as a system, system analysiscan toe aoplied. Therefore, in this study, the education and train-ing system is formalized in the form of a matrix which shows the

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relationship between curriculum and the behavior of the skilledworker who is adequately educated and trained. Based on thematrix, the optimal time allocation in the curriculum was solved.Crane work in the Japanese steel industry was selected as thesubject of the study and the procedures by which the formal-ization can be applied to a practical problem were developed.

107. BURGESS, J. H., "Ego Involvement in the Systems Design Process,Human Factors, 12(1), 7-12, February 1970, Report No. P7-12.

Psychological interactions among members of a systems designteam are frequently of major importance in the design process.Problems arise from specialized design interests as well asfailure in systems discipline. Such problems can be resolvedonly by understanding the nature of the individual and hisinvolvement in interpersonal design conflicts. Several areasmay be considered for improving interpersonal relations in thesystems design effort. Through increasing emphasis on signif-icance of systems design, greater personal and professionalinvolvement in the systems approach may be possible. Attentionis required at the corporate-management organizational level toorient individual engineering professional goals in terms oftotal system perspective. Indoctrination and discipline insystems philosophy and practices also require increased emphasis.Comprehensive design team training might be considered as a meansfor improving the systems design process. Further study issuggested.

108. COIL SON, J. E., and COGSWELL, J. F., Systems Analysis in Education.Santa Monica, Calif.: System Development Corp., January 1965.

The paper is concerned with systems analysis in education, whichcertainly includes some highly complex man-machine systems. Tomake these words more than a catch phrase, the system analysisprocess is described in fairly concrete terms, giving specificexamples of the procedures and products of such analyses. At theconclusion of the paper, some possible implications of systemsanalysis procedures for educational data banks are discussed.

109. HALL, E. R., and CARO, P. W., System Engineering of Coast GuardAviator Training. Alexandria, Va.: Human Resources ResearchOrganization, August 1971, Presented at the Psychology in theAir Force Symposium held at Colorado Springs, Colorado, April 1971,

This paper describes a total-program application of the systemsengineering concept to the U. S. Coast Guard Aviation TrainingPrograms. The systems approach used treats all aspects of themost cost-effective integration of academic, synthetic, and

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flight training for the production of graduate Coast Guardaviators. The paper describes the techniques used to developjob-relevant terminal behavioral objectives (the Coast GuardSearch and Rescue Flight Mission provides the operationalcontext), the assignment of objectives to academic, synthetic,and flight training, the integration of these components intoa systems-engineered training program, the development ofrelatively objective proficiency assessmen% techniques, andthe development of a flying training quality control systemfor maintaining and enhancing instructional efficiency andmanagement of the training system.

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TASK ANALYSIS

With the single exception of Reardon [114), all of the reportsreviewed in this classification fall into two categories;methods for collecting task analysis data or task analysisfor a specific job type. Generally, those reports that dealwith data gathering methods also include an anlysis of aspecific job type, but such analysis was not the primarythrust of the research. Ancillary support systems such ascomputerized data retrieval systems are also covered in somecases.

The only general conclusion that can be drawn from these reportsis that task analysis is not done in any uniform, systematicmanner. Methods described vary from job-type to job-type andfrom service to service. While some of the reports do postulatethe extension of a particular task analysis methodology to abroad spectrum of job types, no data are presented which indicatethat this is being done.

Cullison [110] covers three methods of questionnaire adminis-tration, and describes the use of the Computerized OccupationalData Analysis Program (CODAP/370) in the analysis of theAerographer Mate and Air Controlman ratings.

MacAlister [111] deals specifically with the Boilerman (BT) rat-ing, but the research was also intended to demonstrate the taskanalysis approach developed by the Naval Personnel Research andDevelopment Center (NPRDC).

Perhaps the most generalized approach is taken by McDowell [112].Here the emphasis is on the basic problems of common course develop-ment and rating restructuring for the Engineering and Hull ratings.

Wilson [115] and Ellis [116] are both concerned with task analysisapplied to derive human^factors data to be used in system design,although Ellis deals with a much more specific methodology.

Sass [113] and Shriver [117] both deal with task analysis for aspecific rating (or in the case of Shriver, a Military Occupa-tional Specialty) where the analysis is done primarily to improvethe training for, or structure of, that ratinc. Shriver treatselectronic maintenance training and does so in a more generalfashion than the approach taken by Sass. Though the word fore-casting is used to describe the purpose of Shriver's research,this is somewhat misleading because forecasting, as used in thisreport, means to derive those attributes of a proposed systemthat will shape training needs.

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110. CULLISON, M.D., Occu ational Anal sis: Resort on Data Collectionof Navy-Wide Test o roup IXRif ngs. Was ngton 'avy 'ar.:Nivel Personnel Research and bevelopment Laboratory, June 1972,WRM 72-35.

Data gathering techniques and data gathering instruments weretested in the Aerographers Mate (AG) and Air Controlman (AC) rat-ings to determine their feasibility in the building of a Navy en-listed occupational data bank. A 20-page response packet wasdeveloped to accommodate responses to a questionnaire concerningspecific task statements, items of equipment, watches, types ofaircraft, and worker characteristics. Three methods of question-naire administration and participation by billet incumbents re-vealed most and least desirable methods. Computerized Occupa-tional Data Analysis Program (CODAP/370) is described and itsusage for providing occupational data for analysis is stressed.

111. MCCALISTER, E.H. and MCCUTCHEON, R.E., JR., The Develo meet ofa Task Inventory for Training Purposes for t e o erman Rating.aTiliTTIF75).: Naval Personnel and Training Research Labora-tory, Nov. 1971, Research Report SRR 72-10.

The report presents a detailed task inventory of the Boilerman (BT)rating. The inventory was developed at the request of the NavalDevelopment and Training Center (DATC), San Diego. The reportedinventory is an update of an earlier version. The purpose is toimprove training and use as a basis for pretests.

112. MCDOWELL, H.C. and HULEGAARD, G.S., New Concepts to Improve Train-inland Shipboard Manpower Utilization in the engineering and-Hull Ratfngs: ttatistical Analysis. San Diego, Dal.: NWETPersonnel and Training Research Laboratory, June 1972, SRR 72-26.

This report describes the method used to utilize job analysisapproaches to problems of; common course development, curriculumplanning, rating restructuring, qualifications for advancementdevelopment, job satisfaction, billet restructuring, and dis-tribution/assignment. Data was collected, analyzed, and dis-played as computer printouts, which were published for each rat-ing as SRM 72-13 through 72-22. A task commonalty is beingpublished as SRM 72-26.

113. SASS, D.H. and SWERDLOW, D., The Ships Serviceman Rating :_ NewConce is to Im rove Trainin , Assignment, er ormance, ant, izat on. Was ington, .C.: -Navy Personnel Research and

15v4175Tarit Laboratory, March 1972, WRM 72-23.

This report contains an analysis of the Ships Serviceman (SH)rating. It contains specific recommendations for improvingperformance, retention of personnel, assignment, and training.The report covers, in some detail, the sources of problems inthe SH rating.

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114. REARDON, S.E., Computerized Human Factors Task Data HandlingTechni ues: User's and Co7117617r7rsOre7tiFiri6 Guides. Dayton,

System NWlopment Corp. , ga7-61§68TTRI:n=t7-226.

Instructions are presented for the operation of an experimentalcomputerized data handling system. These instructions were de-veloped as part of the overall research into a user orientedcomputerized system to store, retrieve, and process human factorstask data. These instructions are in'Anded as a model for futureoperating guides.

115. WILSON, D.A., Alication of Automatic Data Processin TechniquesTo Task Analssoarammiii- . -San 'sego, a 'ava ersonnelResearc ctiv ty, ctober 967.

The purpose of this exploratory research is to develop a methodwhich will make it economical to furnish a detailed, up-to-datepicture of operator and technician tasks to a variety of per-sonnel responsible for system design, equipment design, humanfactors, manning, and training.

This project is directed toward the application of automatic dataprocessing (ADP) techniques to the construction and revision oftask analysis diagrams during final development of a new system.

116. ELLIS, R.H., Task Analysis Reduction Technique (TART) for theQuantification of 46man Performance. San Diego, Calif: NavalPerson-nel and Training research la6, September 1970, SRM -71 -7,

A task analysis reduction technique (TART) for collecting humanfactors information was developed and applied to the anti-submarinewarfare tactical data system. TART is a specific procedure foranalyzing the man/machine interface which allow' the researcherto analyze sequential properties of the man/machine interaction.The technique is based on an analysis of the interface it a tasklevel and uses closed circuit television aid video talc record-ing apparatus. A trial application was performed using fourair detector/trackers who were presented a one-hour air scenarioin the anti-submarine warfare tactical data system. The resultssection presents various breakdowns of the TART data and indi-cates that TART can provide valuable insight into man/machinedesign and training effectiveness decisions.

117. SHRIVER, E.L., A Procedural Guide for Technical Im lementationof the Forecast Methods of Task an S i 1 na ysis. as ington,15'. C.: George Washington University, July 1961, TP--61-4251.

The objective of Task FORECAST of the Human Resources ResearchOffice is to develop methods for accurately forecasting thetraining demands imposed by new electronic weapon systeiris.The FORECAST maintenance method of electronic system analysisbasically involves arranging the individual parts of the systeminto groups of parts termed "troubleshooting blocks."

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J. TRAINING COST ANALYSES

Synder and Luchsinger [118] present a procedural techniquewhich quantitatively evaluates an educational institution'sdegree programs in terms of costs and financial benefits tosociety. Weiher and Horowitz [119] describe a study todetermine the relative costs of formal and onthe-job train-ing for Navy enlisted occupations. Although the main resultsare far from conclusive, the findings have important impli-cations for training policy. Henry [120] analyzes thecircumstances and consequences related to reenlistment andnon-reenlistment to determine pertinent cost factors andstrength data required for a practical reenlistment/costmethodology. Clary and Creaturo [1211 describe a studypertaining to the need for Navy manpower program managersto obtain up-to-date officer training and procurement costdata for such purposes as planning, budgeting, and theofficer retention effort.

118. SNYDER, H. H. AND LUCHSINGER, V. P., A Systems Analysis BasisFor Allocation of Resources in Educational Institutions.Presented at the third annual meeting of American laUtutefor Decision Sciences, October 1971.

This report presents a procedural technique which quanti-tatively evaluates an educational institution's degree pro-grams in terms of costs and financial benefits to society.The evaluation is manifested in a "benefit-cost ratio" foreach degree program, permitting a convenient base for com-paring programs through a version of input-output analysis.The evaluation would result in greater effectiveness in theallocation of limited resources.

119. WEIHER, R. and HOROWITZ, S. A., The Relative Costs of Formaland On-the-Job TrinifistedOccusations.San Ramon, CaTiTeriiiiRCseiT.0107iv.isioneralNucleonics, November 1971, CNA Professional Paper.

This report covers a questionnaire study of OJT vs "A" schoolgraduate costs, trainability, and performance on tests foradvancement in rating. Includes several pertinent variablesthat should be covered. It recommends more studies sincesome of the opinions gathered may be questionable. While re-sults are not conclusive, it does show that all the ratingsmay be learned by OJT, but with varying degrees of successunder the present approaches used.

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120. HENRY, G.L., The Man owe). Cost Im lications Associated WithChanges in Nan een istment Rates: Met odo o .

Washington, 6. C.: Naval Personne Researc an DevelopmentLaboratory, July 1970, WRM 71-2.

The circumstances and consequences related to reenlistmentand non-reenlistment were analyzed to determine pertinentcost factors and strength data required for a practical re-enlistment/cost methodology. An effort was made to minimizethe number of factors employed while maximizing output ofuseful information. The major costs associated with changesin reenlistment bonus, medical care of additional dependents,and retirement. The study concludes that the cost of retire-ment outweighs any measurable savings that are associatedwith reenlistment. None of the cost factors included in thestudy were time discounted.

121. CLARY, J.N. and CREATURO, J.T., Officer Personnel Costs:

IllgiAOCIAVELLNAITALAROIC:Ca_NROTC-R, and Naval Academy.Washington Nava l Yard: NavaTPerionnel Research and Develop-ment Lab., February 1971, Report No. WOS -7l -4.

This report presents up-to-date officer training and procure-ment cost data for various Navy officer programs such as,OCS, AOC, AVROC, NAVCAD, NROTC-C, NROTC-R, and Naval Academy.The data is presented in three appendices.. A - Surface, Sub-marine, Nuclear Power; 8 - Pilot Cost; C - Naval FlightOfficer Cost.

C-I11-31


IV. BIBLIOGRAPHY OF PERTINENT NAVAL INSTRUCTIONS AND REFERENCES

Numerous forms, reports, and non-numbered references are not included.References are grouped into broad general categories.

Curriculum Development and Review

Reference No. and Date

CNTECHTRAINST 1540.213 September 1972

NAVAIRINS1 1500.118 March 1968

CINCPACFLTINST 1550.326 June 1971

COMTRALANTINST 1550,1H19 May 1972

OPNAVINST 1550.67 January 1971

MCOP 1510.23A7 November 1972

NAVORD OD 23520 (SecondRevision)15 February 1973

NAVORD OD 45240 (FirstRevision)20 November 1972

NPTRL Research ReportSRR 71-4,

September 1970

Title

Technical Training Development

Review of Navy Training Courses and SchoolCurricula in Support of Naval Aviation

Review of Navy Formal School Curriculaand Instruction Literature

Development and Processing of CurriculaWithin the Training Command, U. S. AtlanticFleet

Review of Navy Formal School Curricula andInstructional Literature

Design of Courses of Instruction

FBM Training System Development, Production,and Support Requirements

FBM Weapon System Curriculum Acquisition andMaintenance Plan

Job Training Course Design and Improvement(Second Edition)

C-IV-1

Missions, Functions,


CNTINST 5450.611 January 1972

CNTINST 5450.7A17 May 1973

CNATRASTAFFINST 5400.1K15 September 1972

OPNAVNOTE 545016 August 1972

COMTRAPACINST 5400.1C1 August 1969

CNTINST 5450.426 October 1971

CNTINST 5450.3A14 September 1972

CNTINST 5450.25 October 1971

CNTINST 5450.121 September 1971

NAVDESCOLINST 5400.1E16 August 1971

NAVOFFTRACENINST 5450.11 July 1972

CNATRAINST B5452.1A11 May 1970

FCDSTCPINST P5400.1C


Title

Naval Training Command Orgabization

Chief of Naval Training Support; Missionand Functions

Chief of Naval Air Training Staff Organization

Establishment of FITCLANT, Norfolk, Va.and FITCPAC, San Diego, Calif.

COMTRAPAC Staff Organization

Missions, Functions and Tasks Assigned toNaval Training Command Shore Activities

Chief of Naval Air Training Mission andFunctions

Chief of Naval Air Reserve Training, Missionsand Functions

Chief of Naval Technical Training; Missionsand Functions

Navy Destroyer School Organization

Naval Officer Training Center - OrganizationManual

Mission and Functions of NABATRACOM AirStations

Fleet Combat Direction Systems TrainingCenter, Pacific Organization Manual

C-IV-2

Requirements


OPNAVNOTE 150026 April 1973

OPNAVINST 5300.32 August 1967

OP 122F18 December 1972

OP 991C/JSJ9 March 1973


Title

Naval Flight Officer and Air IntelligenceOfficer Training Program - FY-74 and FY-75

Development and Review of Enlisted ManpowerRequirements in Naval Ships

Enlisted Requirements Plan, Fiscal Years1973-77

FY 74-78 NEC "C" School Input Plans (SampleOnly)

OP 991 Six Year Training Requirement and SchoolCapacity for USN Training (Sample Only)

FY 74-78 Class "C" (NEC) Training Input Re-quirements (Sample Only)

Enlisted Class "A" School Training Plan (SampleOnly)

Enlisted Class "B" School Training Plan (SampleOnly)

OP 991C1/1211 December 1972

SUPERS 212-7415 November 1972

SUPERS 213-7431 October 1972

Implementation

COMTRALANTINST 1550.3A19 December 1972

COMTRALANTINST 3500.5H3 April 1972

CNATRAINST 5230.118 May 1972

CNATRA N-31CNATRA Report 1542-7 & -3

CNATRAINST 1500.1A

OPNAVINST 1500.24A17 December 1971

OPNAVINST 1500.21A20 July 1966

Centers of Excellence; Establishment of

Quarterly Training Utilization Summary

Naval Aviation Training Information System(NATIS) Manual

Aviation Statistical Reports

Naval Air Training Instructional Procedures((NATIP) (Formerly Pilot)

Programmed Instructional Material

Navy Formal Schools Catalog

C-IV-3

Deference No. and Date

OPNAVINST 1500.19B23 June 1970

NATTCMFINSTR 1080.588 February 1973

SECNAVINST 1510.21 October 1968

OPNAVINST 1552.181 January 1971

OPNAVINST 1541.2D27 April 1968

OPNAVINST 1500.3828 March 1972

NAVPERS 92566AApril 1965

NAVPERS 93904NAVSHIPS 0900-032-60101968

CNTECHTRAINST 1540.174 October 1972

CNATRAINST 3740.58 November 1972

CNATRAINST 3510.22 February 1972

CNATRAINST 1500.19 August 1972



MIL-STO-1379 (Navy)5 March 1972


Title,

Authority and Responsibility for Shore-BasedSurface/Subsurface Training Other ThanMedical and Naval Reserve

Student Personnel Check-In/Check-Out Procedures

Project Transition Certificate of Training

General Aviation Training Literature Program

Fleet Use of Navy Electronic Warfare Simulator(NEWS)

Professional Correspondence Course Study Planfor Officers and Warrant Officers on ActiveDuty

Specifications for the Preparation of Instruc-tor's Guides and Trainee's Guides on NavalEquipment

General Specification for Training Operationsand Materials

Standardized Training Time Units; Establishmentof

FIST - Flight Instruction Standardization andTraining Program

NATOPS (Naval Air Training and Operating Pro-cedures Standardization) Program

PILOT (Performance-Centered, Individualized,Learner-Oriented, Training) System

NATRACOM Monthly NFO training StatisticalReporting

NATRACOM Monthly Pilot Training StatisticalReporting

Military Standard - Training Operations andTraining Data

C-1V-4

Personnel


NAVPERS 15658.30 September 1972

BUPERINST 1510.108C8 August 1972

CNATRAINST 1300.326 October 1972

Research

OPNAVINST 3960.1D4 December 1967

CNATRAINST 3910.131 March 1972

SECNAVINST 5430.6729 June 1964

CNTINST 3910.110 December 1971

Analysis and Planning

OPNAVINST 1500.3318 June 1970

OPNAVINST 1500.8G28 June 1972

SECNAVINST 4000.29A13 January 1971

OPNAVINST 1500.2E3 April 1973

OPNAVINST 4100.3A6 November 1972

OPNAVINST 4490.2811 November 1971


Title

Navy and Marine Corps Military PersonnelStatistics

Management of Formal Training Data System(FTDS)

Assignment of Newly Designated NavalAviators

Prosecution by the Operating Forces of CNOAssigned RDT&E Projects

Training Research Program

Assignment of Responsibilities for Research,Development, Test, and Evaluation

Training Research Program

Navy Training Priority System

Preparation and Implementation of NavyTraining Plans for New Developments

Development of Integrated Logistic Supportfor Systems/Equipments

Establishment and Coordination of FactoryTraining Programs for Military and CivilianPersonnel

Department of the Navy Integrated Logistic(TLS) System

Availability of Equipment for Training Purposes

C-IV-5

Reference No, and Date

OPNAVINST 3500.34A20 August 1971

OPNAVINST 1500.2513 May 1968

OPNAVINST 1500.22A19 December 1969

OPNAVINST 1500.12C7 May 1968

OP 092/CAC3 December 1970

BUPERINST 1510.110 CM 124 March 1972

OPNAVINST 1551.1025 July 1969

OPNAVINST 1543.3824 October 1972

OPNAVINST 1542.32 February 1972

OPNAVINST 1540.283 November 1967

OPNAVINST 1500.3424 September 1970

NAVPERS 18068C5 May 1971

NAVMATINST 5450.1710 January 1969

NAVTRADEVCENINST 5720.621 September 1971


Title

Personnel Qualification Standards Program (PQS)

Computer Aided Instruction Program, Opera-tional Planning and Introduction Responsi-bilities and Procedures

General Military Training

Naval Air Reserve Aviation Technical TrainingProgram; Policy and Responsibilities

Mission of Fleet Operational IntelligenceTraining Center, Pacific: Revision of.

Establishment of Navy Skill Centers

Instructional Television (ITV) Program

Navy Training Plan for Ships 3-M (Maintenanceand Material Management) System

Command Aircraft Crew Simulator TrainingProgram

Naval Air Maintenance Training Program;Policies and Procedures

Fleet Readiness Aviation Maintenance Personnel(FRAMP) Training Program

Manual of Qualification for Advancement

NAVTRADEVCEN; Status, Command Responsibility,Mission and Functions, Relationship withOther Commands

Public Release of Unclassified NAVTRADEVCENTechnical Information

C-IV-6



OPNAVINST 1500.2615 July 1968

CNTECHTRAINST 1540.3130 June 1972

OPNAVINST 1500.28A15 June 1972

OPNAVINST 3500.23B5 May 1972

CNTECHTRAINST 1540.814 September 1972

NAVMATINST 4000.20

WS-13580A1 June 1972

WS-1358I1 January 1971

NAVTRA 38002

NAVORD OD 43180

Evaluation

OPNAVINST 5040.1228 April 1971

OPNAVINST 5040.7F28 April 1971

NAVSECNORDIV Report 25-7219 July 1972

COMTRALANTINST 1500.61 March 1971

CNTECHTRAINST 1540.1224 January 1973

Title

Responsibilities for Factory Training ofNavy Military Personnel

Task Analysis as the Basis for Training

Fleet Ballistic Missile Weapons SystemTraining Program

Assembly, Organization and Training of Crewsfor U.S. Navy Ships Commissioned in Time ofPeace

Schedules; Preparation of

Integrated Logistic Support Planning Procedures

Training Path System, General Specification for

Personnel Performance Profiles, GeneralSpecification for

Submarine Training System PersonnelPerformance Profiles (Volume 1) (Revision 1)

FBM/WS Personnel Performance Profiles andTraining Path System (Revision 1)

Naval Command Inspection Program for ForcesAfloat

Naval Command Inspection Program

Electronics Equipment Training and ManningSurveys

Fleet Training Evaluation Data Collection

Evaluation of Instruction

C-IV-7


NAVSECNORDIV Report No. 4-738 February 1973

CNATRAINST 1610.2F28 July 1967

CNATRAINST 81610.7E8 November 1968

CNATRAINST 81610.6C30 March 1970

WS-136061 April 1971

NAVTRASUPP Form No. 2

Resource Management

OPNAVINST 1000.16C5 February 1973

CNATRANOTE 71109 April 1973

NAVPERS 15163April 1972

CNTECHTRAINST 7310.2/7310.621 March 1973/8 December 1972

FLETRACENSDIEGONOTE 71008 February 1973

OPNAVINST 5040.8810 April 1969

NAVCOMPTINST 7110.8E26 February 1968

SECNAVINST 5000.1608 January 1970


Title

3M Policy Committee Presentation - NAVSECNORDIV

Standards of Performance for Students Under-going Pilot or NAO/NFO Training

Procedures for Students with Low Flight Marks

Method of Computing Academic. Training GradeWeight Factors

FBM System Training Program Test Items, GeneralSpecification for

Educational Self-Audit

Manpower Authorizations; Policies and ProceduresRegarding Changes to

Preparation and Submission of FY 74 Apportion-ment

Navy Military Manpower Billet Cost Data forLife Cycle Planning Purposes

CNTECHTRA Resources Analysis Branch - Code 53

O&MN, Fiscal Year 1974 Apportionment; Requestfor Information

Management of Inactive Aircraft Inventory

Financial Responsibility for the Training andInstruction of Military Personnel

Policy, Roles, and Responsibilities WithinDept. of Navy for Implementation of DODPlanning, Programming and Budgeting System

C-IV-8


SECNAVINST 4860.44A27 October 1971

SECNAVINST 5000.1310 October 1961

OPNAVINST 1000.10(Enclosure to)

OPNAVINST 5311.4A22 May 1969

CNTINST 7300.1A6 November 1972

CNTINST 7043.213 March 1973

CNTECHTRAINST 7310.68 December 1972

SECNAVINST 5000.1608 January 1970

OPNAV 90P-1C15 February 1969

NAVSO P-10002 April 1970

NAVSO P-245710 July 197

NAVSO P-3006$ July 1972

CNTECHTRAINST 1500.9A25 July 1073


Title

Commercial or Industrial Activities Program

Glossary of Terms Used in the Areas ofFinancial, Supply and Installation Manage-ment

Composition of the Manpower Allocation/Re-quirements Plan (MARP)

Responsibility for Programming ManpowerRequirements

Resource Management. System (RMS) ReportingRequirements Within the Naval TrainingCommand

OPN (Other Procurement, Navy) Budget Procedures

Mechanized Course Cost System Test

Policy, Roles, and Responsibilities Within theDepartment of the Navy for Implementation ofthe DOD Planning, Programming, and BudgetSystem (PPBS)

Navy Programming Manual

Navy Comptroller Manual - Budgeting,Volume 7

Department of the Navy, RDT&E Management GuidePart I: System Description

Financial Management of Resources .

(Department and Field Activities)

Naval Technical Training Command Activities,Schools and Courses; Reporting System for

C-IV-9


BUPERSINST 1510.108C8 August 1972

CNATRAINST 5230.118 May 1972

Philosophy, Policy


OPNAVINST 1500.19C7 July 1972

OPNAVINST 1500.11F27 April 1972

OPNAVINST 9860.5A20 August 1971

DOD Directive 1322.10SECNAVINST 1520.4A

OPNAVINST 1510.8A20 July 1971

OPNAVINST 1500.27.

Courses /Syllabi

CNATRAINST 1542.1920 November 1972

CNATRAINST 1550.1F4 December 1972

CNATRAINST 81542.63)8 February 1973

CNATRAINST 131542.74A29 July 1970


Title

Formal Training Data System (FTDS); Managementof

NATIS (Naval Aviation Training InformationSystem) Manual

Navy Training Policy

Authority and Responsibility of Fleet Commandersin Chief for Naval Training Activities Ashore

Naval Aviation Training Program Policies,Responsibilities, and Procedures

Incorporation of Self-Contained TrainingCapabilities Into Shipboard Equipment andSystems

Policies On Graduate Education for MilitaryOfficers

Project Transition

Interservice Formal School Training

Syllabus, Basic Training (JET), T-2A/B/C

Flight and Academic Training Syllabi

Basic Academic Training Syllabus

Indoctrination Syllabus for Student NavalFlight Surgeons, Aviation Psychologists,and Aviation Physiologists

C-1V-10



CNATRAINST 1542.2227 December 1972

NAVDESCOLNOTE 1520 & 1520A7 Feb. 1973 and 24 Apr. 1973

FITCPAC/24: JCS 15001 September 1972

Miscellaneous References

CNTECHTRA Research BranchReport 9-73March 1973

NAVSHIPS 0900-060-038015 August 1972


NPTRL Research ReportSRR 72-13January 1972

NPTRL Research ReportSRR 72-14January 1972

Title

TA-4J/TF-95 Flight Instructor and AncillarySyllabi

Navy Destroyer School Curriculum Outlines

Pacific Fleet Intelligence Training Center -Bulletin of Instruction - CY 1973

Preventive Counseling and PrescriptiveRemediation

Ship Life Cycle Management SupportManual-Planning Guide for Training Supportof Ship Introductions and Modifications

Glossary of Navy Education and TrainingTerminology

Procedures for Obtaining Training FeedbackRelative to.Electronics Maintenance

Training Feedback to the Navy StorekeeperClass "A" School

C-IV-11

FLORIDA

(I)

(TN)

(TN)

(OP)

TENNESSEE

TEXAS


APPENDIX 0

ACTIVITIES/LOCATIONS VISITED

KEY:

TN - Training, not in the CNET Command

OP - Operational Organization

I - Interface Organization

Naval Education and Training CommandNaval Training Support CommandNaval Aerospace Medical InstituteNaval Air Maintenance Training DetachmentFleet Aviation Specialized Operational Training GroupNaval Air Technical Training CenterFleet Aviation Specialized Operational Training GroupNaval Air Maintenance Training DetachmentAmmander Patrol Wing ElevenNaval Training Equipment CenterService School CommandAdvanced Underseas Warfare Weapons School

Naval Technical Training CommandNaval Air Technical Training CenterNaval Air Maintenance Training GroupNavy Training Publications Center

Naval Air Training CommandTraining Wing 4Training Wing 3

CALIFORNIA

Commander Training Command, U. S. Pacific FleetFleet Combat Direction Systems Training Center,Pacific

Fleet Intelligence Training CenterFleet Training CenterFleet Anti-SubmaHne Warfare School

0-Z-1

PensacolaPensacolaPensacolaCecil FieldCecil FieldJacksonvilleJacksonvilleJacksonvilleJacksonvilleOrlandoOrlandoOrlando

MillingtonMillingtonMillingtonMillington

Corpus Christi

Corpus ChristiBeeville

San Diego

San DiegoSan DiegoSan DiegoSan Diego


CALIFORNIA (Continued)

Service School Command San DiegoIndividual Learning Development Group (ILDG) San DiegoNaval Development and Training Center San Diego

(I) Naval Personnel Research and Development Center(NPRDC) San Diego

MNaval Hospital Corps School San DiegoVF-121 Replacement Air Group Miramar

VIRGINIA

Commander Training Command, U. S. Atlantic Fleet NorfolkFleet Combat Direction System Training Center,Atlantic Dam NeckFleet Training Center NorfolkAtlantic Fleet ASW Tactical School NorfolkNavy Amphibious School Little Creek

l?'Pd

Commander Naval Air Force, U. S. Atlantic Fleet. NorfolkFleet Aviation ,Specialized Operational TrainingGroup Atlantic Norfolk

(OP) Commander Amphibious Force, U. S. Atlantic Fleet Little CreekNaval Guided Missiles School Dam Neck

(TN) Missile Training Unit Atlantic Dam Neck(TN) VF-101 Replacement Air Group Oceana

Central Test Site - Personnel and TrainingEvaluation PrograM Dam Neck

(I) Naval Ships Engineering Center - Norfolk Division Norfolk

SOUTH CAROLINA

Education and Training Support Detachment

Fleet Ballistic Missile SUbmarine Training CenterFleet and Mine Warfare Training Center

ILLINOIS

Naval Training CenterRecruit Training CenterService School CommandBasic Electricity and Electronics School

CharlestonCharlestonCharleston

Great LakesGreat LakesGreat LakesGreat Lakes


ILLINOIS (Continued)

Propulsion Engineering School

Opticalman/Instrumentman SchoolInstructor Training SchoolFire Control Technicians SchoolElectronics Technicians SchoolNaval Examining Center

Great LakesGreat LakesGreat LakesGreat LakesGreat LakesGreat Lakes

RHODE ISLAND/CONNECTICUT

Naval Submarine SchoolGroton (Conn.)

Naval Destroyer SchoolNewport

Fleet Training CenterNewport

Naval War CollegeNewport

Naval Officer Training CenterNewport

Education and Training Support Detachment Newport

WASHINGTON, D. C. AREA

1 Nuarv;6RegjZilgPersonnel

1 Office of Naval ResearchI,TN Naval Operation-Submarine Warfare (NAVOP 29)I,TN Naval Operations - Surface Warfare Training (NAVOP 39)I,TN Naval Operations - Air Warfare (NAVOP 59)I) Office of Research,,Development, Test and EValuation

(NAVOP 98)(I,TN) Director of Naval Education and Training (NAVOP 099)(;) Naval Operations Manpower Manning and Control Division

(NAVOP 100)

1

I IN) Strategic Systems Project Office (NSP-15)I Naval Ships Systems Command - Training Support DivisionI N6V01 5hips Engineering Center (NAVSEC 6161); Naval Personnel and Retearch Development Center

(Washington, b. C. Branch)'(I) DeCision SySteMs ASsociates (OSA)

D-I-3


APPENDIX E

GLOSSARY

(Contains Acronymns and Abbreviations)

AAA - Authorization Accounting ActivityA/C - AircraftAcquis. - AcquisitionAcct. - AccountingAct./Act'y - ActivityACV - Air Cushioned VehicleAdmin. - Administration/AdministrativeADO - Advanced Development ObjectiveADP - Automatic Data ProcessingADS - Automated Data SystemADSTAP - Advancement, Strength, and Training PlanAdv. - AdvancedAmt. - AmountAPF - Amphibious Projection ForcesAOB - Average On BoardAppn. - AppropriationARI - ArithmeticASW - Anti-Submarine WarfareATP - Allied Tactical PublicationsAvail. - AvailableAVF - All Volunteer ForceAvg. - AverageAWT Awaiting

BE/E - Basic Electricity and ElectronicsBQT - Basic Qualification TestBT - Boiler TechnicianBUMED - Bureau of Medicine and SurgeryBUPERS - Bureau of Naval Personnel

CAI - Computer Assisted InstructionCCI COmputer Contr011ed InStructionCEB

.- CNO Executive Board

CENTRA - Centralized Training Material Management SystemChg. - ChangeCHNAVTRASUPP - Chief of Naval Training SupportCINCLANTFLT - Commander in Chief% U.S. Atlantic FleetCINCPACFLT - Commander in Chief, U.S. Pacific FleetCIVSUB - Civilian Substitution Program

E-I-1

sr

TAEG REPORT NO 12-1

Cmd, - CommandCMI - Computer Managed InstructionCNATRA - Chief of Nival Air TrainingCNET - Chief of Naval Education and TrainingCNM - Chief of Naval MaterialCNO - Chief of Naval OperationsCNT - Chief of Naval Training (now,CNET)CNTECHTRA - Chief of Naval Technical TrainingComp. - CompareCOMTRALANT - Commander, Training Command, Atlantic FleetCOMTRAPAC - Commander, Training Command, Pacific FleetCPAM - CNO Program Analysis MemorandumCtrl. - ControlCurr. - Curriculum

DCP - Development Concept PaperDecrmts. - DecrementsOepr. - DepreciationDept. - DepartmentDNET - Director of Naval Education and TrainingDNFYP - Department of the Navy Five-Year ProgramDOD - Department of DefenseDOTS - Design of Training SystemsOP - Data ProcessingDPPG - Defense Policy and Planning Guidance

EAM - Electronic Accounting MachineEduc. - EducationEMT - Enlisted Master TapeEnl. - EnlistedEquip. - EquipmentEst, - EstimateEW - Electronic Warfare

FBM - Fleet Ballistic MissileFdbk. - FeedbackFRAMP - Fleet ReplaceMent Aviation Maintenance ProgramFTC - Fleet Training CenterFTDS - Formal Training Data SystemFLociFunct. - FunctionFuricti - FunctionalFYOP - Five-Year Defense Program

GCT - General Classification TestGOR - General Operational Requirement

Hdr. - HeaderH.S. - High School

E-I-2


ICBM - Intercontinental Ballistics MissileID - IdentificationIFRS - Integrated Facilities Requirements SystemIFTIS - In-Flight Training Information SubsystemILDG - Individualized Learning Development GroupILS - Integrated Logistics Support, Individualized Learning

SystemILSMT - Integrated Logistic Support Maintenance TeamIMI - Instructor Managed InstructionIMRL - Individual Material Readiness ListIncl. - Include/IncludingIPE/Ind. Plt.Equip. - Industrial Plant Equipment

Info. - InformationINST - InstructionInst. - InstructorInstall. - InstallationInstrs. - InstructionsI.Q. - Intelligence QuotientIUT - Instructors Under Training

JCS - Joint Chiefs of StaffJFM - Joint Forces MemorandumJIEP - Joint Intelligence Estimate for PlanningJLRSS - Joint Long-Range Strategic StudyJPA - Job Performance AidsJRDQD - Joint Research and Development Objectives PlanJSOP - Joint Strategic Objectives Plan

Lab. LaboratoryLOSC Law of the Sea ConferenceLST Landing Ship Tank

MAA - Master-at-ArmsMaint. Maintenance

Mat. - MaterialMCRF - Master Course Reference FileMEA - Maintenance Engineering AnalysisMECTERP - Mechanized Training Equipment Requirements PlanMgmt. - ManagementMILCON - Military Construction (Appropriation)Milpers - Military PersonnelMisc. - Miscellaneous

3M - Maintenance and Material ManagementMM - Machinist's MateMods. - ModificationMos. - MonthsMOTV - Mobile Technical Unit

E-I-3

TAEG REPORT NO. 12l

Mpwr. - ManpowerMRP - Maintenance, Real PropertyMSP - Management Support PlanMS - Management System

NARM - Navy Resource ModelNATIS - Naval Aviation Training Information SystemNAVCOMPT - Office of the Comptroller of the NavyNAVORD - Naval Ordnance System Command HeadquartersNAVMAT - Naval Materiel Command HeadquartersNAVPERS - Naval Personnel Command HeadquartersNAVSEC - Naval Ship Engineering CenterNAVSECNORDIV - Naval Ship Engineering Center, Norfolk DivisionNAVSHIPS - Naval Ship Systems CommandNAVTIS - Naval Training Information SystemNAVTRA - Naval Training Command HeadquartersNAVTRAEQUIPCEN - Navy Training Equipment CenterNCFA-ADS - Navy Campus for Achievement - Automated Data SystemNCIS - Navy Cost Information SystemNEC - Navy Enlisted ClassificationNETS - Naval Education and Training SystemNFO - Naval Flight OfficerNFOTR - Naval Flight Officer Training RateNITRAS - Navy Integrated Training and Resources Administration

SystemNLRG - Navy Long-Range GuidanceNMRG - Navy Mid-Range GuidanceNo. - NumberNOA - New Obligational AuthorityNOBC - Navy Officer Billet ClassificationNPROC - Naval Personnel Research and Development CenterNPTRL - Naval Personnel and Training Research Laboratory (now NPRDC)NROTC - Naval Reserve Officer Training CorpsNSS - Navy Strategic StudyNTEC Naval Training Equipment CenterNTF Navy Technological ForecastNTP - Navy Technological ProJections; Navy Training PlanNTPC - Navy Training Plans ConferenceNwrp - Naval Warfare Information PublicationsNWP - Naval Warfare Publications

OWN Operation and Maintenance, Navy (Appropriation)08 Operating BudgetOBT - On-Board TrainingOCR - Optical Card ReaderOff. - OfficerOJT - On-the-Job TrainingOMB - Office of Management and Budget

E-I-4


ONR - Office of Naval Research°PEVA. - Operational EvaluationOper. - OperationOPN - Other Procurement, Navy (Appropriation)OPNAVINST - Chief of Naval Operations InstructionOSO - Office of the Secretary of Defense; Operational Sequence

Diagram

P&T - Personnel and TrainingPAMN - Procurement of Aircraft and Missiles, Navy (Appropriation)PBD - Program/Budget DecisionPCS - Permanent Change of StationPDM - Program Decision MemorandumPers. - PersonnelPL - Public LawPing. - PlanningPOM - Program Objectives MemorandumPPBS - Planning-Programming-Budgeting SystemPPGM - Planning-Programming-Guidance MemorandumPPP - Personnel Performance ProfilePQS - Personnel Qualification StandardPrelim. - PreliminaryPreps. - PreparationsProb. - ProbabilityProc. - ProcurementProf. - ProfessionalProg. - ProgramProp, - PropertyPTA - Proposed Technical ApproachPTEP - Personnel and Training Evaluation ProgramPIR - Pilot Training Rate

RAG - Replacement Air GroupRed. - RecordR&D - Research & DevelopmentRDT&E Research, Development, Test and EvaluationRepro. - ReprOdUctionReqs./Rqmnt./Rqmnts. - Requirement(s)

R.F. - Radio FrequencyRqd. ReqUiredREP - Request for ProposalRMS - Resource Management SystemApt. ReportRTM - Rate Training Manual

SA - Strategic AssumptionSCN - Shipbuilding and Conversion, Navy (Appropriation)Scol. - SchoolSCRR - System Capabilities/Requirements and ResourcesSCS _ - Sea Control Ship

E-I-S


SD - System DesignSECDEF - Secretary of DefenseSECNAV - Secretary of the NavySER - Shore Establishment RelocationSHOROC - Shore Required Operational CapabilitySim, - SimulationSLBM - Sub-Launched Ballistic MissileSMD - Ship Manning DocumentSMF - Student Master FileSNA - Student Naval AviatorsSOR - Specific Operational RequirementSPD - Ship Project DirectiveSpec. - SpecialistSSAN - Social Security Account NumberSSN Nuclear SubmarineSSPO - Strategic Systems Project OfficeStud, - StudentSTAPLAN - Status - Time- Attrition PlanningSubsys. - SubsystemSum. - SummarySupp. - SUpportSWA - Strategic Working AssumptionSync. - SynchronizationSYSCOM - SystemS Command

Tact. - TacticalTAD Temporary Additional DutyTAEG. Training Analysis and Evaluation GroupTAMARS - Training Aids Materiel Automated Reporting SystemTAO - Tactical Action OfficerTOP - Technical Development PlanT&E - Test & EvaluationTech. - TechnicalT-F - True-FalseT/0 - Trade OffTPC Training Program CoordinatorTPOM TentatiVe PrOgram Objectives MemorandumTP&P - Transients-, Patientt-$ and PrisOnersTRAD - Training Administration SySteMTRAPS - Training Requirements and Planning SubsystemTrng,TSOR

- Training- TentatiVe Specific Operational Requirement

TYCOMS - Type Commanders

Utl, - Utilization

VA - Attack Squadron (Naval Air)VF - Fighter Squadron (Naval Air)VSTOL - Very Short Take-off and LandingVTOL - Vertical Take-off and Landing

WO - Watch Officer

E-I-6

UnclasstfledSOctintv Classicicaltort

DOCUMENT CONTROL DATA R &,$ectirily rimimilirafiuri of Mk% boar ut obsitiftl end itittextry,onotari,o nJuNI be entered

D

%hen the uverall rdeurt as eloastriedto. REPOAt SECURITY CLASsiFICATION

Unclassified

I. Or NA TING AC WO' r't (Commits ou.Phot)

International Business.Machines CorporationFederal Systems Division, Cape Kennedy FacilityCape Canaveral, Florida 32920

tb. GROUP

N/A1. 0* rerari? TITLE

DESIGN OF TRAINING SYSTEMS, PHASE I FINAL REPORT APPENDICES, Volume II of II

4 DESCRIPTIVE NOTES (Type of ropoff and tackle:ye deter)Final Report Appendicess AU THOPIIS) (it nani;mild e Antal, last name)

Harold J. Bellamy, Lawrence R. Duffy, Albert Elkin, Robert E. Hallman, Ronald E.iYanko

6 REPS ORT /SATE

December 1973sa, TOT AL NO. OF PAGES

230lb. NO. Or ArPS

121177-67tiTRACT OF GRANT NO

N51339q3.!C0097b. PAOrEC t NO.

cl.

9a. ofliOsNAToR,S A EPORT NUMBER'S/

IBM-FSD-ESC 73-535-004

9b. OTHCR REPORT NOIS1 (Any other numbers that may be assignedehle report)

TAEG Report No. 12-1, Vol. II10. OISTMOuTION STATEMENT

Approved for public release; distribution unlimited.

si.iSuPfstAmENTAAT NOTES It. SPONSORING MILITARY ACTIVITY

Naval Training Equipment CenterTraining Analysis and Evaluation GroupOrlando, Fla. 32813

M ABSTRACT

This report presents a functional descriptive model of the current Naval Education andTraining System and idealized concepts oriented toward a 1980 time frame. While tech-.nolegioal gaps and problem areas are presented, no organizatiOnal elements are'spect-Med, since the priMe areas of interest are the functionS performed. In additiOn, therationale for selection of candidate mathematical mOdels to be deVeloped in Phase1I-is given,

Strategic working assumptions for the 1980's are presented in Volume 2 of this report.

: i I

The study was performed by IBM for the Training Analysis and Evaluation Group of theNaval Training Equipment Center, Orlando-, Florida (Contract No. N61339- 73- C- 0097).

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SetOrity aatSifiOlition

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MOL INT

Training System

Training Organization Management

Functional Analysis

Descriptive Functional Model

Mathematical Model

Strategic Assumptions (1980).

DC) 1Ttlit14173 (BACK){PADS

Unclassifiedsoptitity ctioriticatlon

Design of Training Systems, Phase I Final Report 234p. - ERIC

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