A conceptual framework for comparing instructional design models

A Conceptual Framework for Comparing Instructional Design Models

[] Gerald S, Edmonds Robert C, Branch Prachee Mukherjee

Instructional design (ID) professionals typically employ models that guide their practice. However, it is unclear how a specific model is selected for an instructional situation. Andrews and Goodson (1980) provided a valuable procedure for comparing instructional design models, but because of the proliferation of variations in instructional design applications during the past decade, the introduction of instructional design into new learning contexts and the emergence of alternative approaches to instructional design, there has emerged a need for a new framework which assesses the potential success of any instructional design model. A framework is presented here which is intended to provide a conceptual tool for determining appropriate instructional design applications.

[] The field of instructional design has grown steadily over the years as school, business, and government leaders increasingly engage instructional designers to facilitate human resource development as a means of achieving their respective goals. "Since the first appear- ance of instructional design models in the six- ties, there has been an ever increasing wamber appearing in the literature of both instructional technology and general education" (Gustafson, 1991, p. 1). The number one trend in educational technology as reported by Ely (1992) was that "The creation of technology-based teaching/learning products is based largely upon instructional design and development principles" (p. 11). The increased practice of the systematic design of instruction has been accompanied by a comparable development in instructional design research, resulting in a proliferation of instructional design theories and related models (Andrews and Goodson, 1980; Gustafson, 1991). Andrews and Goodson (1980) compared a sample of 40 instructional design models, focusing exclusively on systems-theory-based models. More recently, Gustafson (1991) proposed a taxonomy of instructional design models with three categories: (1) classroom focused, (2) product focused, and (3) systems focused. Although scholars and practitioners are confronted with hundreds of models intended to improve the instructional planning process, they lack a method for predicting the potential success of a given model in a specific learning situation. While many instructional improvement models have some claim to being based on instructional design principles, it is extremely difficult

ETR&D, VoL 42, No. 4, 1994, pp. 55-72 LSSN 1042-1629 ~

56 ETR~D, Vol 42, No. 4

for scholars or practitioners to make any mean- ingful comparisons between these models or assess the models against a useful standard. A contemporary conceptual frame of reference, that incorporates a consideration of designer expertise, contexts, traditional approaches to instructional design, as well as emerging approaches to instructional design, for comparing instructional design models at this point becomes necessary.

This is not an argument for more models of instructional design, but rather, a call for ways of comparing existing instructional design models and new models as well. Clark (1989) states: "It is dich6 to talk about the plethora of instructional design models and theories [e.g. Reigeluth, 1983]. The problem is that very few instructional design researchers conduct research that compares one model or theory to another" (p. 59). The continued growth of instructional design as a profession and as an area of study warrants regular review of the various approaches to designing instruction. Self-reflection is a prerequisite for sustained growth. Such reflection strengthens the practices of instructional design within schools, businesses, industry, governments, and at research and development (R&D) labo- ratories.

The purpose here is to offer a comparison framework which might serve as a paradigm for guiding research in instructional design theory, or at least promote thinking about assessing the relative value of instructional design models as applications change. There are four sets of tasks recommended for constructing a conceptual framework for comparing instructional design models. First, review the fundamental components of the instructional design process; second, identify the contexts to which instructional design is commonly applied; third, present a conceptual framework for determining appropriate instructional design applications; and fourth, propose a matrix for comparing instructional design models.

The caveats of constructing a comparison framework become evident when the risks of such an undertaking are reviewed. There is the risk of comparing a model to a standard it never intended to fulfill, or the risk of appearing to advocate an ideal list of dimensions that

all good instructional design models must pos- sess. As formal instructional design processes are increasingly accepted in a greater number of learning contexts, defining instructional design has become a complex task involving many conditional statements for use, and multiple disclaimers of potential effect. Because instructional design has come to mean many things to many people, there is the additional risk of alienating instructional design scholars by recommending common components of instructional design. These and other risks notwithstanding, comparative frameworks such as the one offered here serve important reference functions in the selection of appropriate instructional design applications.

Fundamental Components of Instructional Design

The framework presented in this article is intended for applications of instructional design. The dominant approach to instructional design practiced today is based on systems theory. According to systems theory, a system is a reg- ularly interacting or interdependent group of items forming a unified whole. An instructional system is a human enterprise of a complex nature. The scope of an instructional system has no fixed boundaries (GagnG Briggs, & Wager, 1992). Systems are characterized by input data and output data processes that are dearly specified (Figure 1); an explic- itly defined locus of control; and interrelation- ships of various components which comprise the system. According to Banathy (1987), the systems approach addresses highly complex, large-scale problems; is dynamic, non-linear, synthesis-oriented and holistic; and employs strategies and other tools to represent a set of interrelated concepts and principles. A systems-theory-based model accepts pre-estab- lished goals as its orientation.

The instructional design process is systematic because of the way in which the input-process- output paradigm is inherent to the process. Instructional design is also systemic where the outcomes of each component directly or indi- rectly impact every other component of the instructional design process to some degree, thus

COMPARING INSTRUCTIONAL DESIGN MODELS 57

Figure 1 [ ] Input-process-output paradigm

4 -1 Input f Process

Conditions Methods Information Actions

Data Procedures Environment Development

f Output Results

Outcomes Products

Ideas

Figure 2 [ ] Fundamentals of the Instructional Design Process

9 ~

producing a ripple effect. Instructional design is intended to be responsive to the educational environment, learner-centered, goal-driven, procedural and sensitive to each relationship that occurs during the instructional episode. However, instructional design processes are often modeled to facilitate multiple contexts or reconfigured to conform to situational parameters. The variations of instructional design models can also be attributed to the evolution- ary stages of the field of instructional technology. Figure 2 depicts the typical relationships between the fundamental components of the instructional design process.

Metatheoretical Approaches to Instructional Design

Constructing a framework for comparing various instructional design models provides a method to consolidate the knowledge base of the field by identifying the various components of models. By developing an understanding of the variety of approaches to instructional design, scholars, students, teachers, and practitioners can interpret instructional design in a more flexible, useful and discriminating man- ner (Litttejohn, 1989). Therefore, the first step in constructing a comparison framework is to

58 ETR&D, Vol 42, No. 4

understand the theoretical contributions to the fundamental components of the instructional design process.

In order to guide theoretical improvement efforts in instructional design, it is instructive to study the stages by which related fields have matured. Communication studies are acknowl- edged as one of the roots of instructional design (Richey, 1986) and therefore appropriate for comparisons between fields. In the early years of communication research, communication theories and models were categorized and delineated in attempts to advance theory and model construction relative to concepts in communication (Littlejohn, 1989). The components of a variety of models were identified, which were intended for situations and contexts in which communication took place. Different levels of communication were divided into categories, such as intrapersonal communication, interpersonal communication, group communication, organizational communication and mass communication. The fundamental components of the communication process were inherent to each category of communication model.

Communication models were then classified on the basis of these broad levels. Similar communication models were compared among themselves; mass communication models were compared with other mass communication models rather than mass communication models being compared with interpersonal communication models. A similar approach is recommended to compare instructional design models.

Instructional design theorists, such as Reigeluth (1983) and Gropper (1983) presented arguments for similar categorizations of instructional design models over a decade ago. Reigeluth (1983) presented a case for "building [of] a common knowledge base that integrates the independent and piecemeal 'knowledge bases' that presently characterize the discipl- ine" (p. xi). Reigeluth also referred to the dis- agreement about the relationship between the scope and utility of instructional design theories; whether they should be "narrow and local" as proposed by Snow (Reigeluth, 1983, pp. 31-32), or "broad and comprehensive" as proposed by Scandura (Reigeluth, 1983, pp.

32-33). Perhaps such a debate as this is less appropriate than comparing narrow models to other narrow models.

Another important reason for the lack of broad and comprehensive instructional design theories can be attributed to the absence of suitable metatheory. Reigeluth (1983) mentions the emergent "learner-control" metatheory proposed by Merrill and Reigeluth as a viable metatheory (p. 33). Metatheories for instructional design initiated a quest to move instructional design into the realm of science. Responding to this challenge, Gropper (1983) proposed a metatheory for quantitative comparisons of instructional design models:

bl t l b2t2 b3t 3 bnt n Instruction = ~ alcl + + • • • +

a2c2 a3c3 anCn t = delivery of a treatment for an

identified problem b = degree of attention provided by

treatment c = presence of a problem a = estimate of the degree of difficulty

posed by the problem (p. 45)

Gropper 's (1983) metatheory allows the comparison of the value of instructional design theories and models on the basis of their predictiveness. The metatheory works by quantifying the obstacles to the intended learning objectives, and selecting the appropriate degrees of treatments for overcoming the obstacles. Gropper presents a mathematical function relating instruction and achievement. However, Gropper 's hypothesized function fails to address a variety of situations because it sets specific conditions to zero, resulting in an unsolvable function. For example if a or c is set to zero the function is undefined:

~ b3t3 bntn Instruction = ~ + + - - ~ • - . +--~--

= undefined

Although Gropper's metatheory is intended for comparing instructional design theories and models, Reigeluth, advocating the need to inte- grate existing knowledge, proposes that Gropper's metatheory could also be used to improve existing theories and models (Reigeluth, 1983, p. 38). Attempts to quantify


the context and process of instruction are unsatisfactory, as they reveal little about the complexities of instruction.

The first task in constructing a common framework for divergent models is to select certain elements or dimensions of comparison. In the history of instructional design, Andrews and Goodson (1980) proposed a four-dimensional framework for comparing a sample of 40 instructional design models. Besides Gropper's 1983 metatheory, Andrews and Goodson is the one and only example of such a framework in instructional design. Andrews and Goodson started by defining systematic instructional design and the purposes of systematic instructional design. Andrews and Goodson drew a sample of 40 instructional design models based on systems design principles, comparing and categorizing them according to the dimensions outlined in Table 1.

Constructing a common framework does not necessarily imply values being placed on models, or suggesting that Model A is better than Model B, or that Model A is the correct model. Instead, a frame of reference illustrates how Model A is different from Model B. Per-

haps Model A is suited for a different context, level, purpose and application than Model B. Instructional design models often do not con- vey comprehensive descriptions of the total design activities, but instructional design models do represent a variety of perceptions of the instructional design process. It is not the purpose of this article to enter into the debate over which instructional design model is better, or whether the field is already saturated with instructional design models, but to provide a framework for the comparison and interpretation of instructional design models.

Instructional design models share a number of common characteristics such as categorization, context, and level, in addition to prescrip- tions about information arrangement and sequence. Categorization, context, and level of models can be used to classify various kinds of approaches to instructional design.

The following sections explain categorization, context, and level relative to the application of instructional design models. A structural representation of a conceptual framework for comparing instructional design models will then be presented to stimulate

Table I [ ] Dimensions of instructional design models outlined by Andrews and Goodson (1980]

CODE DIMENSION

1.0 1.1A 1.1B

1.2 2.0 2.1

2.2 2.3

3.0 3.1 3.2

3.2A 3.2B 3.2C 3.2D 3.3

4.0 4.1 4.2

Origin Total model (includes general systems theory or other total approach) One or some of the components (includes adult learning theory and other learning theories)

Empirical Theoretical underpinnings Emphasis on learning or instructional theory (includes constructs about adult learning requirements) Emphasis on control/management/monitoring functions of systems theory Emphasis on analysis function (includes content, tasks, and learning analysis of systems theory) Purposes and Uses Teach instructional design Produce viable instructional products(s) or activity(s)

Non-formal (includes military, industrial, governmental, vocational, adult education) Formal (includes public, higher and professional education) Small-scale lesson/course/module development Large-scale curriculum/system/programs development

Reduce costs of training/education Documentation Documentation, application or validation data relating to use of the total model Documentation, application, or validation data relating to part of the model (the mere outline and description of model being insufficient to qualify as documentation)

60 Em~, Vo~ 42, No. 4

discussion about the potential for comparing existing instructional design models, as well as adding instructional design models which may subsequently emerge in the field.

Constructing a Conceptual Framework

Given the plethora of existing instructional design models, how does one know, without having to study each model in detail, which is the most appropriate model for a particular problem? Instructional design scholars should be able to form critical opinions about divergent instructional design models, compare and contrast them, and build metatheories to address the complexities of instructional situations.

Andrews and Goodson (1980) made a sig- nificant contribution to the field of instructional technology by suggesting a metatheory which could be used to address the numerous theories as a body of work with common origins. The trends in instructional design practice since Andrews and Goodson's work more than a decade ago, has resulted in a vast number of new instructional design models. Conse- quently, their four-dimensional framework, presented in Table 1, does not account for recent developments in instructional design theory. For example, models which are not based on general systems theory are excluded from the Andrews and Goodson (1980) comparison. Further, ambiguity arises due to the great latitude of interpretation of Andrews and Goodson's (1980) dimensions, and the emergence of five additional factors that have been perceived as important in recent years which currently influence instructional design theory and practice: (1) determining the purpose of a model; (2) determining the context for which the model is intended; (3) determining the level of experience the designer should have in order to apply the model; (4) determining whether the model adopts a systems-theory approach or alternative approach; and (5) determining the type of learning tasks the model will support.

These five emerging factors in instructional design practice have been integrated into the conceptual framework offered here. The proposed framework is centered on four classifica-

tions: (1) type of orientation, (2) type of knowledge, (3) required expertise, and (4) theoretical origins.

Type of Orientation: Prescriptive or Descriptive

It is important to determine the intended purpose of an instructional design model. For example, models can be descriptive, prescriptive or both. Based on practical experiences of teaching and learning [instruction], descriptive models describe a given learning environment and speculate how the variables of interest will be affected in such an environment. Prescrip- tive models outline how a learning environment can be altered or constructed in order to affect the variables of interest in a certain way or bring about the desired outcome (Reigeluth, 1983; Landa, 1983). Instructional design models which are both descriptive and prescriptive speculate and recommend organizational strategies, and are typically comprehensive and explicit in the amount of detail for application.

Descriptive theories or models outline a given learning environment and imply how the variables of interest will be affected in the environment based on practical experiences of instruction and learning. Prescriptive theories or models describe how a learning environment can be altered or constructed, in order to affect the variables of interest in a certain way or bring about desired outcomes (Reigeluth, 1983; Landa, 1983).

Type of Knowledge: Procedural or Declarative

It is equally important to determine the type of tasks the model is intended to support: either procedural (how to reach a goal), or declarative (why we reach a goal). The kinds of instructional and student variables emphasized by a model depend on whether the model is procedural or declarative (Clark 1989, p. 60). Clark (1989) elaborates:

Procedural theories tend to focus on examples, non- examples, short sequences, lower verbal load materials, practice with correct feedback, and criterion- referenced evaluation. Individual differences in apti-


tude, other than prior knowledge of the subject mat- ter, will be less important because treatments tend to produce acceptable criterion performance by increasing the learning of lower-general-ability learners while reducing the learning efficiency of higher-ability learners. Declarative models tend to emphasize analogies, discovery-type instruction, and norm-referenced evaluation. Individual differences in intelli- gence are much more important since less instructional support is given to learn more abstract material (p. 60).

Required Expertise: Novice, Intermediate or Expert

Instructional design models vary in the amount of expertise required by individuals to apply the model. Some instructional design models provide step-by-step descriptions of the process of designing instruction which are more useful for a novice or inexperienced instructional designer to employ, while other models rely on an expert's intuition and experience to guide the process. For example, the Dick and Carey (1990) model (Figure 3) might be appropriate for a novice instructional designer, while

Wedman and Tessmer's (1991) Layers of Necessity model (Figure 4) might be more appropriate for an expert instructional designer.

The expertise category is arranged as a continuum from novice to expert (Figure 5). The instructional designer's level of skill deter- mines which models are useful for the designer. Some models provide algorithmic steps and procedures which are appropriate for novice instructional designers while other models provide only broad heuristics as reference points and rely more on experience and prior knowledge. Heuristic models are more suitable for an expert instructional designer.

Theoretical Origins: Hard systems, Soft Systems or Intuition

As the field of instructional design evolves, there arises a need to include instructional design models that may not be based on systems theory. Some instructional design models, such as Tripp and Bichelmeyer's (1990) Rapid Prototyping model (Figure 6), are not

Figure 3 [ ] Dick and Carey model of instructional design

Identify Inst~cdonal Goal(s)

$ Conduct Instructional A~lys~

Identify Enuy Behavi~s~ ~ar~teristics

I I

I i I I I I I I

" " I ', ', I I Select ~ Conctuct

Inst~cUonal [W" 1 Formative Materials l i Evaluation

!

H Develop H Develop H Write Criterioct lr~u*uctional Per fcxemance Referenced Strategy Objectives Test Items

: i Design & Conduct

Surm~6ve Evaluatio~

,,,,.. ,,.

Figure 4 [] Wedman and Tessmer's Layers of Necessily model of instructional design

Simple ID Process

Complex ID Process

Quality

6~ ETR&D, Vol 42, No. 4

Limited Time/ Resources

Ample Time/ Resources

Figure 5 [] Novice/Expert Instructional Design Continuum

Algorithm Approach

I~,,=

Novice Instructional Design

Heuristic Approach

=1 Expert Instructional Design

Figure 6 [] Tripp and Bichelmeyer's Rapid Prototyping model of instructional design

i Assess Needs & Analyze Content i Set Objectives I , , , , ,

i Construct Prototype (Design)

I Utilize Prototype (Research) H . i i

I

I I

Install & Maintain System I

COMPARING tNSTRUCllONAL DESIGN MODELS 63

based on systems theory. You's (1993) description of chaos theory and its application to instructional design raises the possibility of the introduction of other non-system-based models. The inclusion of a systems-theory approach as an eligibility criterion results in excluding instructional design models that are very much a part of instructional design practice.

This category is conceptualized essentially as a distinction between systems theory and alternative theories. General systems theory (GST) stresses the interdependence of elements that constitute a system, recognizing the dynamic nature of this interdependence, as well as the environment in which a system exists. The assumption is that systems cannot be understood by decomposing them into their constituent parts and assumes the existence of irreducible wholes. In order to identify and generalize the problem-solving methods to new systems, GST seeks to identify common principles of organization of systems across different disciplines. All theories seek to explain through generalization, or by identifying similarities among varied phenomena. In contrast to traditional mechanistic and reductionist theories that promote a "shared substance" common to all objects, for example, GST seeks to identify the "shared aspects of organization" across objects. Additionally, different common- alities exist at various levels within a true system. Thus, a person is understood as one who shares certain personality traits with other members of his or her family; or qualifications with other members of a profession; or characteristics with other living beings (Laszlo, 1972). Sutherland (1973) states that a precept of GST is "A belief in the scientific utility of (and the limited existence of) phenomenal isomor- phisms" (p. 19). In doing so, GST can explain the similarities across disciplines, as well as differences or gaps, and promote cooperative communication among seemingly diverse fields. Caution, however, must be taken to ground empirically the similarities across disciplines, rather than assume them (Van Gigch, 1974). General systems theory provides the complex response to the equally complex situations that typify instructional environments.

A systems approach should not be confused with a simplistic, linear, procedural approach

which is systematic, but not systemic. The systemic aspect stresses the application of creative problem-solving methods. Models based on systems theory generally provide algorithms for designing effective instruction. An algorithm is not the same as a solution. More than one algorithm is often required to solve a problem. Further, the successful application of most algorithms is dependent on specific needs. The absence of an algorithm requires understanding the entire conceptual framework and theoretical origins of a task, such as a winning chess move or using a 1040 form to calculate the correct tax refund. True systems-based instructional design models also utilize a cyber- netic component to regulate the system and provide feedback. The emphasis of true systems theory is on process. Therefore, systems theory remains the theoretical origin for the ma- jority of existing instructional design models.

Alternatives to the systems approach for the design of instruction have been proposed, where instruction is perceived as a human enterprise comprised of human interactions (Hlynka & Belland, 1991). A systems approach is mistakenly perceived as being governed by rigid formalized rules, procedures and routines while alternative approaches to instructional design contend to allow for a more flexible design based on site-specific needs. The alternatives to system-based models offer the prem- ise of being comprised of soft systems and intuitive approaches. Checkland (1985a), a pio- neer of soft system methodology, conceptual- izes hard systems as seeking the efficient attainment of goals and goal-seeking as an acceptable model of human behavior (p. 765). Hard-system advocates contend that the world contains systems which can be "engineered" and that models of those systems can be constructed. Hard systems identify problems and seek solutions to rectify those problems (Checkland, 1985b). Checkland (1985a) notes that "the 'soft' tradition does not regard goal- seeking as an adequate model for much of what goes on in human affairs" (p. 765). Soft- system advocates do not support the idea that the complexity of the world can be reduced to systemic models, and hence regard "system models produced within the 'hard' tradition not as "models of X' but only as 'models of the

64 ETR&D, Vo142, No, 4

logic of X'"(Checkland, 1985a, p. 765). Soft-system models are used to argue about situations and phenomena and the models are not to be taken as models of the world. Checkland (1985a) states that "this leads to 'learning' replacing 'optimizing' or 'saftisficing'; this tradition takes the language of 'issues' and 'accommodations' rather than 'solutions'" (p. 765). Certainly accommodating learning is the ultimate goal.

There are instructional design researchers who subscribe to the notion that a systems- based approach is limiting and that instructional situations are chaotic and require much more intuition than systems theory provides. You (1993) proposes chaos theory as an alternative to traditional instructional system

design (ISD). Limitations of ISD according to You (1993) include linearity, deterministic pre- dictability, closed systems and negative feedback. Alternative approaches to hard systems theory allow for the designer's intuition and site specific constraints to impact upon the process of design, as well as the final design itself. In the proposed framework, the relationship between hard systems, soft systems and intuition is viewed as a continuum from hard systems to intuition (Figure 7).

In order to construct a visual representation of the conceptual framework, the first dimension representing the four basic classifications of instructional design processes are arranged in four layered circles (Figure 8). The center ring represents the decision of whether an

Figure 7 [ ] Hard Systems---Intuitive Continuum

I i I Hard Soft Intuitive

Systems Systems

Figure 8 [ ] Categorization of instructional design models

/ t


instructional design model is descriptive or • prescriptive in orientation. The innermost ring represents whether an instructional design model is primarily procedural or declarative. The middle ring represents the degree of expertise required to use an instructional design model. The outer ring in Figure 8 represents theoretical origins associated with an • instructional design model. Conceptually, the outer rings are rotated to match the procedural or declarative orientation.

• Expert~System-Based is characterized by expert instructional designers who have the expertise to use complex system models that operate on a variety of levels. The Inter- • service Procedures for Instructional Systems Development (Branson, 1975) model (Figure 9) is an example of an expert/system-based instructional design model.

Novice~System-Based represents models that are system based and are used by novice instructional designers, for example Dick and Carey's (1990) model (Figure 3). This model provides step-by-step guidelines for the systematic design of instruction.

Expert~Soft-System-Based is an instructional design model that relies on expert instructional designers to make decisions and to use models which rely on their experience to guide the design. The Layers of Necessity (Wedman and Tessmer, 1991) is an example of this dass of model (Figure 4).

Novice~Soft-System-Based is an instructional design model that is meant for novice instructional designers who have knowledge and expertise in a specific context such as teachers. A teacher has expertise in

Figure 9 [ ] Interservice Procedures for Instructional Systems Development model of instructional design

F2 , , Select Oon,tru Job Analyze Tasks/ Performance Job Functions Measures

~,, I I1.t 11.2 Describe ] , - ~ Develop Develop Entry , Objectives Tasks Behawor

, i

II1.1 Specify

- , ~ Learning Events/ Activities

,i ,

IV.1 Implement Instructional Management Plan

i i I

V.1 Conduct

" ~ internal Evaluation

'111.2 specify Instruction Management Plan & Delivery S y s t e m

i

Conduct instruction

V 2

Conduct External Evaluation

F 1.4 Analyze Existing Courses

11.4 Determine Sequence & Structure

, ,i ,,,,,

IlL3 tlL4 Review/Select Develop Existing Instruction Materials

V.3 Revise System

1.5 Select Instructional Setting

,,,,,, ,,

,,, Instruction I !

66 ~ , Vo; 42, No. 4

instruction but may be a novice in terms of the formal instructional design process. Geflach and Ely's (1980) model (Figure 10) is an example of this type of model.

• Expert~Intuitive-Based is an instructional design model that relies on expert instructional designers to make decisions and to use intuitive models that rely on heuristics, past experience, knowledge and intuition to guide the design. Rapid Prototyping (Tripp & Bichelmeyer, 1990) is an example of this class of model (Figure 6).

• Novice~Intuitive-Based is a category in which few, if any, instructional design models are placed. This model assumes that the user of the model is a novice instructional designer who relies on heuristics, past experience, knowledge and intuition to guide the design. The authors of this article at the time of publication are unaware of any viable instructional design models that would be classified in this category.

Instructional Contexts

One criticism of past evaluations of instructional design models is that instructional

design ignores the context and level for which the model was intended to be applied. Andrews and Goodson (1980) divided context into non-formal and formal, as well as small- scale lessons and large-scale curriculum. Taylor (1986) notes:

Andrews and Goodson's approach to the problem has been to ignore the fact that models belong to different classes and are intended to be used in different contexts. The forty models they addressed include development models and design models intended for a variety of contexts, grouped together into a common pool. This has put Andrews and Goodson in the position of comparing models designed to accomplish different ends (p. 30).

Instructional design is practiced most often in one of the following four contexts: K-12 education, higher education, business training, and government training. Each context is characterized by features which make it unique. Just as instruction designed for one context is not necessarily appropriate for another, a model developed for a particular context may not be suitable for another. One must be able to determine the context in which an instructional design model is applicable in order to maximize resources and provide effective

Figure 10 [ ] Gerlach and Ely's (1980] model of instructional design

Specification of

Content

,,,,,,, ,, I

Objectives

~men t of Entenng Behaviors

D~elmination Of Strmegy

Allocation of T~e

Allocation of Space

Sek~ion of Resounms

l l l l l l l

Evalum~n of ! Performance

i Analysis of Fee6back


instruction. Many instructional design models originated in a certain context, in response to the particular needs of that context. For example Diamond's (1989) model (Figure 11) was developed for a higher-education context and may not be appropriate for other contexts. Applying a model developed for use in a military context for example, may not be the best choice for solving the instructional problems of children with special needs. Concepts, theories, and models have an ecology, a context within which they are developed and within which they function. Importing a theory or model from a significantly different context, without attention to contextual differences, violates this ecology, and subsequently results in inefficient solutions to instructional problems.

The second set of circles of the instructional design comparison framework represents the four most common contexts in which instruc-

tional design is practiced: (1) K-12 education, (2) higher education, (3) business training, and (4) government training (Figure 12). For example, Diamond's (1989) model (Figure 11) is intended for a higher education context while the Interservices Procedures for Instructional Systems Development (Branson, 1975) model (Figure 9) is intended for a military context.

Six Levels of Instructional Design Models

Similar to communications theory, instructional design is applied on a variety of levels. Communication occurs on a variety of levels, relative to the size of a population, for example: mass (a television program broadcast to a large audience), organizational (a manu- facturer's report on company sales), group (a college course), interpersonal (a face to face conversation), and intrapersonal (a personal

Figure 11 [ ] Diamond's model of instructional design

Project Selection and Deldgn

BasK: Plant, rag Inputs (Project-Speckled)

• Domain of knowledge • Student knowledge ,

attitudes & ptlOnties • Societal needs • Research - Educational prio~tms

Pmjec~ ~peofio Factors

• Research • Goals • Time • Resources

H~-nan Materials Facilit~s Fiscal

• Students Number Location

t t ~'~d Selec~on SelectJan S~uence

ProducUon, lmp~mentatlon, and Ev~lu~on for Each Unit

F " ) ~ i Oes'gn evaiuati truments and pr°ced S . . . . . , . . . . i .... . ~ ' , ......... ~

I . . . . . . . /_l ot I I rod°o.n.

. . . . . . . . I

68 ETR&D, Vol 42, No, 4

reflective communication). Instructional design models are also intended to plan instruction for different levels of implementation depending on the size of the population targeted by the instruction. For example, mass-level instruc-

tional design might involve planning a global AIDS-awareness initiative or a national birth- control program; institutional-level instructional design might occur for all the professional training staff at Motorola University or for all

Figure 12 [] Categorization and contexts of instructional design models

Figure 13 [ ] Conceptual framework for comparing instructional design models

COMPARING INSIRUCTIONAL DESIGN MODELS 69

enlisted personal for the United States Army; curriculum-level instructional design could be for a degree program such as a bachelor's in mathematics at the University of Botswana; course-level instructional design could be sequencing the subjects such as in Calculus 256; unit-level instructional design would determine specific topics or tasks to be learned; lesson-level instructional design would be concerned with the actual events that would occur during specific episodes of instruction; and module-level instructional design would address micro details such as the formula f{x} sin, f{x} tan. The level of application becomes a very important comparison variable for instructional design models.

Some instructional design models are intended to create instruction for lessons, such as Rapid Prototyping, while other models such as Interservice Procedures for Instructional Systems Development (IPISD) [the whole 1200 pages] are intended to create instruction on an institutional level (U.S. Army). The seven levels upon which instructional design are applied are represented as the outermost ring of the conceptual framework (Figure 13).

A Classification Context-Level Matrix

Establishing the four application categories allows the researcher to construct a comparison framework similar to the one proposed above. The comparison categories represent the first stage of determining the appropriate instructional design model for a given instructional situation. The second stage involves applying the comparison framework to instructional design models with which readers may be familiar or models that readers are considering for use in planning instruction. A classification context-level matrix based on the circular conceptual framework is arranged to indicate the degree of applicability using a three-point scale (Table 2), to achieve the second stage of instructional design model comparison. The instructional design comparison matrix was the first step in testing the comprehensiveness and utility of the framework proposed in the paper. Subsequently, a sample of instructional design models is assessed, using the proposed frame-

work, providing comparison along a broad range of shared dimensions. As a result of this initial comparison it can be concluded that the framework fulfills its intended purpose of providing a multi-dimensional frame of reference for comparing a wide variety of models.

SUMMARY

School, business and government leaders increasingly engage instructional designers to facilitate human resource development as a means for achieving their respective goals. Instructional design professionals typically employ models that guide their practice. While many instructional improvement models have some claim to being based on instructional design principles, there remains a need for a contemporary conceptual framework for comparing instructional design models which accounts for theoretical origin, contextual application, and instructional design ability.

Instructional design, as a domain of educational technology, has historically been systems-theory based in its origin of application. While a systems approach enables us to explore, understand, and describe hierarchical characteristics, relations and interactions, parameters, dynamic patterns, results of inte- gration and synthesis, and modifications in system patterns, there remains a need for the explicit articulation of intuition in the practice of instructional design. Therefore, a meta-ana- lytical observation about the utility of instructional design models informs current and innovative instructional design practices. The comparison framework presented here is intended to serve as a metatheoretically-based approach to instructional design models.

Andrews and Goodson (1980) provided a valuable procedure for comparing instructional design models, but because of the proliferation of variations in instructional design applications during the past decade, there has emerged a need for a new framework which assesses the potential success of instructional design models, including a multitude of instructional contexts and alternative theoretical origins. The caveats of constructing a comparison framework are evident as one reviews

Tab

le 2

[]

Sel

ecte

d In

slTu

cfio

nal D

esig

n M

odel

s C

ompa

rison

Mat

rix

ID M

odel

O

rien

tatio

n K

now

ledg

e St

ruct

ure

Exp

ertis

e Le

vel

Stru

ctur

e C

onte

xt

Leve

l

Dic

k &

Car

ey (

1990

) B

A

D

A

A

,B,C

,D

A,B

,C,D

Rap

id P

roto

typi

ng (

1990

) C

C

A

B

,C

A,B

,C,D

A

,B,C

Lay

ers

of N

eces

sity

(19

91)

B

B

A,B

B

A

,B,C

,D

A,B

,C,D

,E,F

Dia

mon

d (1

989)

C

C

A

,B

B

B

A,B

,C,D

,E,F

Rom

izow

ski

(198

1)

A

B

A,B

D

A

,B,C

,D

A,B

,C,D

Ger

lach

& E

ly (1

989)

A

A

D

A

A

,B

A,B

,C,D

Dic

k &

Rei

ser

(198

9)

C

A

D

A

A

A,B

,C,D

Kem

p (1

985)

C

C

D

B

,C

A,B

,C

A,B

,C,D

Van

Pat

ten

(198

9)

A

A

QA

, B

A

A,B

,C,D

A

,B,C

,D,E

,F

Les

hin,

Pol

lack

&

C

A

A,B

A

A

,B,C

,D

A,B

,C

Rei

giel

uth

(199

2)

Ber

man

& M

oore

(19

90)

C

A

C

A

C

E

IDI

(197

1)

C

A

C

A

A

A,B

,C,D

See

ls &

Gla

sgow

(19

90)

C

A

C

A

A,B

,C,D

D

,E,F

IPIS

D (1

975)

A

A

A

A

C

,D

E

Cha

os (

1991

) B

B

A

A

A

,B,C

,D

A,B

,C,D

,E,F

Oth

ers

Ori

enta

tion

Kno

wle

dge S

truc

ture

Ex

pert

ise L

evel

St

ruct

ure

Con

text

Le

vel

A.

Pres

crip

tive

A.

Proc

edur

al

A.

Exp

ert

A.

Syst

em

A.

K-1

2 A

. U

nit

B.

Des

crip

tive

B.

Dec

lara

tive

B.

Inte

rmed

iate

B

. So

ft-S

yste

m

B.

Hig

her

Ed.

B

. M

odul

e

C.

Ele

men

ts o

f bot

h C

. E

lem

ents

of b

oth

C.

Nov

ice

C.

Intu

itive

C

. B

usin

ess

C.

Les

son

D.

Suita

ble

for

all

D.

Asp

ects

of e

ach

D.

Gov

ernm

ent

D.

Cou

rse

E.

Inst

itutio

nal

F.

Mas

s

Z

O

COMPARING INSTRUCTIONAL DESIGN MODELS 7 !

the risk of comparing a model against a dimension it never intended to include, or the risk of appearing to advocate an ideal list of dimensions. These risks notwithstanding, comparative frameworks such as the one offered here serve important reference functions in the selection of appropriate instructional design applications.

An important issue that is implicitly associated here is the notion that all new instruc, tional design models introduced to the field of instructional technology, such as Gentry's (1994), would only be accepted as such after the new model has been tested or validated in some way. A comprehensive discussion about the acceptance of new instructional design models is beyond the scope of this presenta- tion, however, any discussion of that sort ought to include the acceptance of existing instructional design models which do not offer any validation data about their potential for success. Therefore, any self-proclaimed instructional design model can be compared within the conceptual framework.

Probably most important regarding models of instructional design at this time is the inclusion of ideas about process orientation, required knowledge and skills, and level of implementation as each affects the situational application. Subsequent research in this area should consider ways in which instructional design processes match people with negotiated outcomes. The framework which has been presented here is merely intended to provide a conceptual tool for determining appropriate instructional design applications.

The degree of understanding about various instructional design models becomes stronger and more focused by delineating categories, contexts and levels as dimensions of differences, conceptualizing. Classifying models promotes the notion that the design of instruction is not done using a blanket approach. The categorization, context and level of various instructional design models illustrate the ways in which the process of instructional design is flexible and offer practical instructional planning assistance for a variety of subjects, situations, contexts, and learners. [ ]

Gerald S. Edmonds, Robert C. Branch, and Prachee Mukherjee are with the Department of Instructional Design, Development and Evaluation at Syracuse University.

REFERENCES

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Gagn~, R.M., Briggs, L.J., & Wager, W.W. (1992). Principles of instructional design (4th ed.). Chicago: Holt, Rinehart & Winston Inc.

Gentry, C. G. (1994). Introduction to instructional development: Process and technique. Belmont, Califor- nia:Wadsworth Publishing Company.

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Gustafson, K.L. (1991). Survey of instructional development models. (2nd ed.) [with an annotated ERIC bibliography by G.C. Powell]. Syracuse University: ERIC ClearinghOuse on Information Resources. (IR-91)

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Hlynka, D. and Belland, J.C. (Eds.) (1991). Paradigms regained: The uses of illuminative, semiotic and post- modern criticism as modes of inquiry in educational technology. NJ: Educational Technology Publications.

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Reigeluth, C.M. (Ed.). (1983). Instructional-design theories and models: An overview of their current status. NJ: Lawrence Ertbaum Associates, Publishers.

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CALL FOR MANUSCRIPTS ETR&D invites papers dealing with research in instructional

development and technology and related issues involving instruction and learning.

Manuscripts that are primarily concerned with research in educational technology should be sent to the Editor of the Research Section:

Steven M. Ross Research Editor, ETR&D Foundations of Education Memphis State University Memphis, TN 38152

Manuscripts that are primarily concerned with instructional development and other educational technology applications should be sent to the Editor of the Development Section:

Norman Higgins Development Editor, ETR&D School of Education Dowling College Oakdale, NY 11769-1999

Guidelines for preparation and submission o f manuscripts are provided under "Directions to Contributors" on the inside back cover.

..... J

A conceptual framework for comparing instructional design models

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