teaching behavior profile during practices of an effective ...

ABSTRACT

TEACHING BEHAVIOR PROFILE DURING PRACTICES OF AN EFFECTIVE BASKETBALL COACH IN A

PERFORMANCE COACHING CONTEXT

The purpose of the study was to systematically document the teaching

behavior profile of an effective basketball coach in a performance coaching

context. An interpretative case study approach with multiple methods of data

collection and analysis were employed to develop a teaching behavior profile of a

successful NCAA Division 1 collegiate women’s basketball coach in the practice

setting. Data were collected across the 2010 – 2011 collegiate basketball season

and seven practices were analyzed using the Teaching Effectiveness Sport Coding

System (Gilbert & Riddle, 2011). The Teaching Effectiveness in Sport Coding

System enabled the researcher to code the frequency of 15 instructional non

instructional teaching behaviors. Results from the present study reveal that

instruction was the most frequently observed teaching behavior (34.3%). This

finding concurs with previous research on teaching behavior effectiveness in the

performance sport setting (e.g., Becker & Wrisberg, 2008; Bloom, Crumpton &

Anderson, 1999; Tharpe & Gallimore, 1976). The second most frequently

observed teaching behavior was use of student-athlete first name (20.7%) and the

third most frequently observed teaching behavior was praise (14%). Both findings

support the promotion of an athlete–centred coaching approach (Kidman, 2005)

and an autonomy supportive learning climate (Mageau & Vallerand, 2003).

Matthew Emmett May 2012

TEACHING BEHAVIOR PROFILE DURING PRACTICES OF

AN EFFECTIVE BASKETBALL COACH IN A

PERFORMANCE COACHING CONTEXT

by

Matthew Emmett

A thesis

submitted in partial

fulfillment of the requirements for the degree of

Master of Arts in Kinesiology

in the College of Health and Human Services

California State University, Fresno

May 2011

APPROVED

For the Department of Department Kinesiology

We, the undersigned, certify that the thesis of the following student meets the required standards of scholarship, format, and style of the university and the student's graduate degree program for the awarding of the master's degree. Matthew Emmett

Thesis Author

Wade Gilbert (Chair) Kinesiology

Jenelle Gilbert Kinesiology

Tim Hamel Kinesiology

For the University Graduate Committee:

Dean, Division of Graduate Studies

AUTHORIZATION FOR REPRODUCTION

OF MASTER’S THESIS

X I grant permission for the reproduction of this thesis in part or in

its entirety without further authorization from me, on the

condition that the person or agency requesting reproduction

absorbs the cost and provides proper acknowledgment of

authorship.

Permission to reproduce this thesis in part or in its entirety must

be obtained from me.

Signature of thesis author:

TABLE OF CONTENTS

Page

LIST OF TABLES ................................................................................................ viii

LIST OF FIGURES .................................................................................................. x

CHAPTER 1: INTRODUCTION ............................................................................ 1

Purpose Statement ............................................................................................. 4

Research Questions ........................................................................................... 4

Significance ....................................................................................................... 4

Delimitations ..................................................................................................... 6

Limitations ........................................................................................................ 6

Definition of Terms ........................................................................................... 6

CHAPTER 2: REVIEW OF LITERATURE ......................................................... 10

Coach Behavior ............................................................................................... 10

Impact of Coach Behavior on Athlete Outcomes ........................................... 15

Antecedents of Coach Behavior ...................................................................... 17

CHAPTER 3: METHODOLOGY .......................................................................... 20

Participant ....................................................................................................... 20

Data Collection and Analysis .......................................................................... 21

Validity ............................................................................................................ 29

CHAPTER 4: RESULTS ....................................................................................... 34

Introduction ..................................................................................................... 34

Across Practice Results ................................................................................... 34

Within Practice Results ................................................................................... 41

Coach Perceptions ........................................................................................... 65

Coach Suggestions for Future Research ......................................................... 68

Page

vii vii

Summary ......................................................................................................... 70

Conclusion Table ............................................................................................ 70

CHAPTER 5: DISCUSSION ................................................................................. 74

Introduction ..................................................................................................... 74

Theoretical Implications.................................................................................. 74

Future Research Design .................................................................................. 83

Practical Implications ...................................................................................... 86

Summary ......................................................................................................... 90

REFERENCES ....................................................................................................... 92

APPENDICES ...................................................................................................... 101

APPENDIX A: CONSENT FORM – COACHES ............................................... 102

APPENDIX B: PRACTICE SCRIPT EXAMPLE ............................................... 104

APPENDIX C: TEACHING EFFECTIVENESS IN SPORT CODING SYSTEM ................................................................................... 106

APPENDIX D: PROPOSITION MATRIX AND EXIT INTERVIEW TRANSCRIPT ........................................................................................... 112

LIST OF TABLES

Page

Table 1 Overview of Data Collection and Analysis Procedures ........................... 22

Table 2 Overview of Preliminary Data Collection ............................................... 23

Table 3 Overview of Validity Strategies ................................................................ 30

Table 4 Overview of Reliability Testing ................................................................ 32

Table 5 Overview of Summary Drill Complexity Results ...................................... 34

Table 6 Frequency of Drill Occurrence Across the Seven Intact Practice ........... 36

Table 7 TECSC Teaching Behavior Definitions.................................................... 38

Table 8 Teaching Behavior Rank Across the Seven Intact Practices ................... 39

Table 9 Overview of Practice 1 ............................................................................. 42

Table 10 Overview of Teaching Behavior Profile for Practice 1 ......................... 42

Table 11 Overview of Practice 2 ........................................................................... 45

Table 12 Overview of Teaching Behavior Profile for Practice 2 ........................ 46











Table 23 Conclusions Table .................................................................................. 71

Page

ix ix

Table 24 Practical Implications for Coaches........................................................ 86

LIST OF FIGURES

Page

Figure 1. A working model of coaching effectiveness (Horn, 2008) ...................... 3

Figure 2. Mean drill complexity score across the seven intact practices ............... 35

Figure 3. Across drills drill complexity average score .......................................... 37

Figure 4. Total frequency of teaching behavior across the seven intact practices .................................................................................................. 40

Figure 5. Total percentage of teaching behavior across the seven intact practices .................................................................................................. 40

Figure 6. Total rate per minute (RPM) of teaching behavior across the seven intact practices ........................................................................................ 41

Figure 7. Drill complexity flow score for practice 1 ............................................. 42

Figure 8. Total frequency of teaching behavior for practice 1 .............................. 43

Figure 9. Total percentage of teaching behavior for practice 1 ............................. 44

Figure 10. Total rate per minute score of teaching behavior in practice 1 ............ 44

Figure 11. Drill complexity flow score for practice 2 ........................................... 45

Figure 12. Total frequency of teaching behavior for practice 2 ............................ 47

Figure 13. Total percentage of teaching behavior for practice 2 ........................... 47










Page

xi xi




Figure 26. Total rate per minute score of teaching behavior for practice 5 ........... 58




Figure 30. Total rate per minute score of teaching behavior in practice ............... 61





CHAPTER 1: INTRODUCTION

Collegiate sport is a billion dollar business in the United States of America.

In May 2011 the Pacific 12 Athletic Conference extended their TV contract with

Fox and ESPN networks, signing the richest deal in collegiate sport history. The

deal, worth a staggering $235 million per year ensured that the Fox and ESPN

networks have exclusive rights to Pacific 12 Athletic conference coverage until the

year 2113 (The Spokesman-Review, 2011). Recently USA Today conducted a

salary analysis of 33 National Collegiate Athletic Association (NCAA) Division 1

men’s basketball coaches. Publication of the coaching contracts revealed that in

the 2010 – 2011 season alone coaches could expect to earn an average salary of

$1.7 million (USA Today, 2011). USA Today’s salary report also demonstrated that

women’s collegiate basketball is no exception, with at least five NCAA Division 1

women’s basketball coaches reported to be making over $1 million per year (USA

Today, 2011). Spearheading this list is Tennessee’s Pat Summit, winningest coach

in NCAA Division 1 history. Coach Summit reportedly earned an approximate

salary of $2 million in the 2010-2011 season, illustrating that success on the

basketball court translates to big money contracts for collegiate coaches.

Despite the ever increasing salaries and the tremendous appeal of collegiate

coaching there is a lack of research on effective coaching in performance sport

settings. A review of 610 coaching science articles published between 1970 and

2001 found that only 57 studies focused specifically on coaching effectiveness,

predominantly at the youth sport level (Gilbert, 2002; Gilbert, & Trudel, 2004). As

a consequence there is a lack of academic literature to support what constitutes

coaching effectiveness in the collegiate basketball setting. Collegiate sport in the

United States of America is considered to be a performance context as it is

2 2

characterized by high levels of competition with teams regularly competing for

regional and national honours. Therefore coaches working in the performance

context are required to provide highly structured training regimes to meet the

demands associated with high level sport performance (Côté, Young, North, &

Duffy, 2007).

Despite these shortcomings, over the past 40 years coaching research has

endeavoured to increase understanding of coaching effectiveness in the

performance sport setting. In the quest to understand coaching effectiveness

several frameworks have been presented to help organize what has been learned.

One of the first empirical frameworks’ of performance sport coaching was

presented by Côté, Salmela, and Trudel (1995) study of 17 gymnastics coaches.

Following interviews with the 17 gymnastics coaches, an inductive analysis

resulted in the creation of the Coaching Model. The Coaching Model consisted of

three components (a) competition (b) training and (c) organization. In defining the

three central duties of the coaches’ work, Côté, and colleagues provided the first

empirically based mental model intended to represent how performance coaches

organize their work.

Seven years later Lyle (2002) introduced A Model for Coaching. Lyle’s

model is intended for practitioners, illustrating the process of ‘what a coach needs

to do’. Lyle’s model, in its simplest form provides coaches with a systematic

overview of ‘what coaching is about’. This includes all phases of the coaching

process; planning, monitoring, goal setting and regulation in the training and

competitive arenas. Lyle’s model for coaching provided a holistic view of the

coaching process and was intended to serve as a research tool for promoting

further investigation on the coaching process.

3 3

In 2008 Horn presented yet another model of coaching effectiveness that

could be applied to performance sport settings. Building on previous models and

theories (Chelladurai & Saleh, 1978; Smith & Smoll, 1978; Mageau & Valleraud,

2003) the Working Model of Coaching Effectiveness is an organizing framework

for understanding coaching effectiveness. Horn’s model provides a simplified

framework for organizing the literature, touching on all aspects of the coaching

process (see Figure 1).

Figure 1. A working model of coaching effectiveness (Horn, 2008)

The Working Model of Coaching Effectiveness provides the framework for

the present study. Through the working Model of Coaching Effectiveness Horn

illustrates that coach behavior is influenced by a number of antecedents. These

antecedents include the sociocultural context (box 1), the organizational climate

(box 2), the coaches’ personal characteristics (box 3), and the coaches’

expectancies, values beliefs and goals (box4). The Working Model of coaching

Effectiveness demonstrates that coach behavior has a direct impact on athletic

4 4

performance and behavior (box 6), athletes’ self–perceptions (box 9), and the

athletes’ level and type of motivation (box 10). Finally, these athlete outcomes are

filtered through athletes’ perceptions of coaching behavior (box 8). For the

purpose of the present study the Working Model of Coaching Effectiveness is

intended as a guiding framework serving to help make sense of and give context to

the study of coach behavior. Specifically, the focus of the present study was coach

behavior (box 5).

Purpose Statement

The purpose of the present study was to systematically document the

teaching behavior profile during practices of an effective basketball coach in a

performance coaching context.

Research Questions

1. What is the teaching behavior profile during practice of an effective

basketball coach in a performance coaching context?

2. How does a coach’s values, expectancies, and goals influence this

behavioral profile?

Significance

In 2006 College Sports Television (CSTV) became the first network

dedicated to bringing uninterrupted athletic coverage of the National Collegiate

Athletic Association (NCAA) to homes across America. CSTV now showcases

over 35 men’s and women’s collegiate sports and holds multimedia rights to an

additional nine NCAA championship events (CSTV Networks, 2007).

Furthermore, in 2010 basketball emerged as the most popular sport in the world,

with International Basketball Federation (FIBA) president Ivan Mainini

5 5

announcing that the game now boasts 211 affiliated national federations and over

4 million participants around the world (FIBA Copyright, 2011). With the

popularity of collegiate sport ever increasing and the recent emergence of

basketball as the world’s premier sport there is an associated need for research on

coaching effectiveness in this setting.

With greater emphasis now being placed on the role of the coach, there has

been a call for coaching science research findings to be included in future coach

education initiatives (Gould, Giannini, Krane, & Hodge, 1990). Current coach

education programs fail to reflect the messy and complex nature of real world

coaching practice (Lyle & Cushion, 2010) and therefore coaches typically do not

value formal coach education. Rather coaches typically attribute much of their

learning to on the job experience (Trudel & Gilbert, 2006). Therefore the present

study provides coaches and coach educators with an evidence–based summary of

coaching effectiveness in action.

The recent introduction of the Journal of College Sport and the imminent

release of the Routledge Handbook of Sports Coaching (Potrac, Gilbert, &

Denison, in press) demonstrate that progress in the quest to understand coaching

effectiveness in performance sport settings has been made. Therefore by

presenting an example of this phenomenon in action, the present study contributes

to our understanding of the complex and dynamic nature of effective coaching in

the performance sport setting. Finally, with self-reflection being a crucial tool in

raising the self-awareness of coaches (Côté & Gilbert, 2009) the present study has

potential to be of great practical significance for the study participant. Therefore

findings from the present study will increase one coach’s self awareness and

provide the stimulus for evolution of the coach’s teaching behaviors.

6 6

Delimitations

For the purpose of the present study the following delimitations are

identified:

1. The study focused on the teaching behaviors of one women’s collegiate

basketball coach.

2. The study focused on teaching behavior in the practice setting.

3. The study focused on instructional and non-instructional teaching

behaviors.

Limitations

For the purposes of the present study the following limitations are

identified:

1. It is assumed that the coach exhibited naturalistic teaching behaviors

during data collection periods.

2. The importance of practices recorded may vary according to time of

season, conference standing, upcoming opponent, etc.

3. The coach’s knowledge of observation may have influenced exhibited

teaching behaviors.

4. Results from this study are not generalizable to the wider coaching

population and are representative of one women’s collegiate basketball

coach.

Definition of Terms

Athletes’ perceptions of coach behavior: Individual interpretation and

evaluation of actual coaching behavior. The ultimate effects of coaching behavior

are mediated by the meaning that players attach to them (Smith & Smoll, 1989).

7 7

Coaching effectiveness: The consistent application of integrated,

professional, interpersonal, and intrapersonal knowledge to improve athlete’s

competence, confidence, connection and character in specific coaching contexts

(Côté & Gilbert, 2009).

Coach behavior: Reactive or spontaneous behaviors exhibited by the coach

in direct response to athlete behavior (Horn, 2008).

Coaches’ beliefs: Often stereotypical and are likely to affect how coaches

interact with their athletes (Horn, 2008).

Coaches’ expectancies: The coach’s preconceived expectation of athlete

performance. These expectations are likely to affect how coaches treat their

athletes and can determine actual athletic performance (Horn, 2008).

Coaches’ goals: The goal orientation held by the coach is likely to affect

their outlook on their sport programs and can affect the behaviors they exhibit

toward their athletes (Horn, 2008).

Coaches’ personal characteristics: The coaches’ background including

age, gender, coaching experience, formal education and motivations for coaching

are likely to affect the behaviors coaches’ exhibit toward athletes (Horn, 2008).

Coaches’ values: A core set of beliefs that the coach subscribes to. These

values are likely to affect how coaches behave and interact with their athletes in

the sport domain (Horn, 2008).

Effective coach: A consistent track record of obtaining appropriately

defined athlete outcomes in specific coaching contexts (Côté & Gilbert, 2009). In

the United States collegiate basketball setting the primary outcomes are defined as

overall team success and student-athlete educational attainment.

Performance Coach: A coach working with athletes at the highest

competitive level. Performance coaches’ genuinely spend most of their time

8 8

preparing athletes for highly intensive and formalized competition events (Lyle,

2002).

Instructional behavior: Verbal statements that encompass the pedagogical

and cognitive aspects of coaching. This often involves teaching individual skills

and tactical strategies. Instructional behavior can also include general management

of the coaching environment. This can involve directing coaching staff and

regulating drills (Bloom, Crumpton, & Anderson, 1999).

NCAA: Founded over a hundred years ago as a way to protect student-

athletes the National Collegiate Athletic Association (NCAA) is the governing

body of collegiate sport in the United States of America. The NCAA has 1084

affiliated members across three divisions (NCAA Division 1 – 3) and emphasizes

athletic and academic excellence (NCAA, 2011).

Non-Instructional Behavior: Non instructional behaviors do not provide

players with specific information towards learning a skill or strategy. For example,

non-instructional behaviors may include a non-verbal gesture of encouragement

e.g., a smile or a nod (Bloom, et al., 1999).

Organizational climate: A set of priorities or standards perceived directly

or indirectly by all involved within a particular sport organization. These standards

and priorities may influence how coaches behave in their sport environment

(Horn, 2008).

Systematic observation: Systematic observation allows a trained person

following stated guidelines and procedures to observe, record, and analyze verbal

and non-verbal interactions with the assurance that others viewing the same

sequence of events would agree with the recorded data (Darst, Mancini, &

Zakarjek, 1983).

9 9

Teaching Behavior Profile: A summary of instructional and non-

instructional teaching behaviors exhibited by the coach during practice (Bloom et

al., 1999).

Training: Sometimes referred to as the practice setting, this is the primary

environment in which the coach attempts to apply knowledge toward helping

athletes acquire and perform skills. In the performance coaching context training

often involves preparing athletes to perform according to their potential during

competition events. (Côté, Salmel, Trudel Baria, & Russell, 1995).

CHAPTER 2: REVIEW OF LITERATURE

The purpose of this chapter is to explore in greater detail boxes 2, 3, 4, 5,

and 8 of the working model of coaching effectiveness (Horn, 2008). First, box 5,

coach behavior which is central to this study will be examined. Specific emphasis

will be placed on previous behavioral studies conducted on collegiate basketball

coaches. Second, athlete perceptions of coach behavior will be reviewed, with a

specific focus on how these perceptions can influence athlete motivation and

performance (box 8). Finally, to identify the underlying intentions of coach

behavior boxes 2, 3 and 4 of the working model of coaching effectiveness will be

examined. This will help to demonstrate how the coaches’ personal characteristics,

beliefs, values and goals impact athlete perceptions, behaviors and performance.

Coach Behavior

Behavioral analyses first emerged as a legitimate area of study in the

1970’s, with research focusing on the description and analysis of physical

education instructors (Lawson, 1990). Research in the physical education domain

provided information in regard to the type and quality of teaching instruction (e.g.,

DeMarco, Mancini, & Wuest, 1996) and as a result investigations focused on

observable coach behavior grew out of this. Coach observation studies have been

conducted across a number of different sports and at all levels of competition (e.g.,

Rejeski, Darracott, & Hutslar, 1979; Lacy & Goldstone, 1990). The vast amount

of work that has been undertaken has provided insight into a number of sports

across a variety of sport settings, and has resulted in the production of research

articles that have shed light on different aspects of coach behavior. However, the

performance sport setting has received limited attention and subsequently ‘what

11 11

does an effective performance coach do?’ is a question that warrants further

investigation.

In attempts to address this question, over the past forty years of coaching

research practitioners have entered the worlds of performance sport coaches.

These studies were undertaken to determine if there are any common practice

behaviors amongst successful performance coaches (e.g., Becker & Wrisberg,

2008; Bloom et al., 1999; Jones, Armour & Potrac, 2003; Gould et al., 1990).

Tharp and Gallimore’s (1976) study of legendary collegiate basketball coach John

Wooden is often credited as the landmark study in coach observation research.

During the 1973-1974 season coach Wooden was observed across 15 practice

sessions during his final season of teaching at UCLA. Using the Coaching

Behavior Recording Form (CBRF; Tharp & Gallimore, 1976) Tharp and

Gallimore were able to code a number of coach Wooden’s instructional teaching

behaviors. The CBRF is a 10 category instrument, similar to those employed in

classroom settings to asses teaching effectiveness. Following eight observations of

coach Wooden, Tharp and Gallimore decided to add two additional behavioral

categories to the CBRF. The first of these behaviors was ‘scold reinstruction’; a

criticism followed instantly by ‘how to do it right’. The second category was

‘hustle’; a verbal statement employed to reinforce practice intensity.

Results from the Tharp and Gallimore (1976) study evidenced discrete acts

of teaching with instruction (50.3%) and hustle (12.7%) the most commonly

exhibited behaviors. Instruction compromised over half of coach Wooden’s

behaviors. During practice coach Wooden was frequently observed delivering a

continuous stream of instruction to his athletes in attempts to communicate ‘what

to do’ and ‘how to do it’. Hustle statements, the second most observed behavior

was employed to raise and maintain the intense nature that characterized coach

12 12

Wooden’s practice sessions. Tharp and Gallimore’s landmark study of coach

Wooden provided the first insight into teaching effectiveness in the performance

coaching context.

Tharp and Gallimore’s 1976 study served to spark an unparalleled activity

in the field of coach behavior research, and since 1976 over 1, 800 studies have

been undertaken (Kahan, 1999). These studies have been conducted across a vast

majority of sport settings, playing witness to the development of new

observational instruments as practitioners attempted to capture a wider array of

coaching behaviors. Despite the degree of work that has been undertaken, to our

knowledge there have only been two other published observational studies that

have focused on the practice behaviors of collegiate basketball coaches. Following

the study of legendary basketball coach John Wooden nearly two decades passed

before Bloom et al. (1999) systematically observed the practice behaviors of coach

Jerry Tarkanian. At the time coach Tarkanian had been coaching NCAA Division

1 men’s basketball for twenty six years and had accumulated a 667–145 win / loss

record. Coach Tarkanian was observed across 10 practices during the 199 -1997

season whilst coaching the men’s basketball team at California State University,

Fresno. Observations were conducted using a revised version of the Coaching

Behavior Recording Form (CBRF; Tharp & Gallimore, 1976). The revised

instrument contained 12 behavior categories. Ten of the categories related to

instructional coaching behaviors, and the final two behaviors were defined as

‘humour’ and ‘uncodable.’ In addition to the 12 behavioral categories notes were

taken during periods of observation, allowing the researchers to establish a better

feel for the structure of coach Tarkanian’s training sessions. Results revealed that

tactical instruction was the most frequently occurring teaching behavior (29%).

The second highest coded teaching behavior was hustle (16%). Due to these

13 13

findings, at the end of the season Bloom and colleagues opted to conduct a follow

up interview with coach Tarkanian. The interview revealed that coach Tarkanian

deliberately focused on teaching offensive and defensive strategies to his team

during practice time. The explanation of practice behavior provided a rationale for

coach Tarkanian’s approach to in practice teaching. Based on coach Tarkanian’s

insight Bloom and colleagues were able to propose that coaching behavior is

specific to the context in which the coach works, suggesting that effective coaches

recognize and tailor their behaviors to the needs of their athletes. In this specific

case Bloom and colleagues identified that certain aspects of coach Tarkainian’s

behavior may differ from the practice behaviors of non-performance sport

coaches. By recognizing the strengths of his athletes, coach Tarkanian was able to

draw upon raw athletic ability and focus practice time on teaching tactical aspects

of play.

The most recent study of coach behavior within the collegiate basketball

setting was undertaken during the 2004-2005 collegiate basketball season. Becker

and Wrisberg (2008) observed winningest basketball coach in NCAA Division 1

history, coach Pat Head Summit. Coach Summit was observed in six practices

whilst coaching the women’s basketball team at the University of Tennessee. The

Arizona State University Observation Instrument (ASUOI; Lacy & Darst, 1984)

was used to asses coach Summit’s teaching behaviors. The ASUOI was

specifically designed to asses teaching behaviors in the practice setting and

compromises 13 behavioral categories. A total of 3,296 verbal and non-verbal

behaviors were observed using the ASUOI. Results from the systematic

observation indicated that 48% of coach Summit’s behaviors were instructional.

Praise was the second most observed behavior, representing 14.5 % of coach

Summit’s total behaviors. Concurrent instruction, a teaching behavior delivered to

14 14

athletes whilst engaged in a skilled activity, was frequently exhibited by coach

Summit. Coach Summit felt that concurrent instruction provided the athletes with

the necessary information required to successfully execute technical and tactical

moves in training. Praise, specifically positive feedback was often given to

reinforce correct executions of skills. Coach Summit felt this was important as it

served to promote the behaviors she expected to see from her team.

Instruction, hustle and praise were clearly important components of

behavioral effectiveness for coach Wooden, coach Tarakanian and coach Summit.

These behaviors ensured that practice sessions were intense, challenging and

rewarding experiences for their athletes. Although all three coaches were found to

score most frequently in the ‘instructional’ category (Wooden 50%; Summit

48.1%; Tarkanian 22.9 %) and had similar behavioral scores for ‘scold’ (Wooden

6.6 %; Summit 7 %; Taraknian 12.9 %), variance was also found in all three

coaches’ behaviors. For example coach Summit used praise almost twice as much

as coach Wooden (Summit 14.5 %; Wooden 6.9 %). Such variances in coach

behavior indicate that there is no stereotypical coaching personality or set of

behaviors which lead to coaching success (Cushion, 2010), but rather indicate that

behavioral effectiveness is dependent upon the coaches’ personal characteristics,

knowledge of their athletes, and are in direct response to situations arising within

the particular coaching episode (Erikson & Gilbert, in press).

Despite the contribution Tharp and Gallimore (1976) Bloom et al (1999)

Becker and Wrisberg (2008) have made in enhancing our understandings of coach

behavior in the performance sport setting there appears to be several gaps in the

literature in regards to behavioral knowledge. Specifically, there is a lack of data

that provides insight into coach behavior across different points of a season. With

this in mind Lyle (2010) urged future behavioral research directives to focus on

15 15

the totality of the process, stating that an examination of restricted practices would

appear to exclude the realities of coaching. Lyle (2010) has also suggested that

point of the season is likely to have a considerable impact on coach behavior, but

despite these suggestions and to our knowledge nothing has yet been done to

address these recommendations.

Impact of Coach Behavior on Athlete Outcomes

Coaches exert influence on their athletes by the behaviors they display

(Erikson & Gilbert, in press). These influences impact the ability to master skills,

psychosocial development, motivation, attitudes toward sport and the self-

perceptions of athletes (Horn, 2008). One of the first studies to stimulate thought

on the impact of coach behavior on athletic performance was Smith, Smoll and

Hunt (1977) study of youth baseball coaches. Smith and colleagues measured

athlete perceptions of coach behavior during games. Analysis of the athlete

questionnaire package, intended to examine athlete perceptions (Smith, Smoll, &

Curtis, 1978) revealed considerable variance between athlete perceptions of actual

coaching behavior during competitive situations. Results from the Smith and

colleagues 1977 study demonstrated a low correspondence between actual

coaching behavior and athlete perceptions. This implies that a low correspondence

between actual behavior and perceptions of behavior may impact the coaches’

ability to meet specific athlete outcomes.

Two years later Rejeski et al. (1979) observed 14 youth basketball coaches

in one game and one practice situation. Following their observations, the coaches

were asked to rank order their top three ‘high’ expectancy athletes and their

bottom three ‘low’ expectancy athletes. When these athletes were established,

coaching behaviors were analyzed in correspondence with the ‘high’ expectancy

16 16

and ‘low’ expectancy athletes. Results indicated that the high expectancy athletes

received more of the coaches’ attention. Specifically the high expectancy athletes

received more reinforcement both during practices and games. Unfortunately this

study did not examine the athlete’s perceptions of coach behaviour, but did

demonstrate differential treatment of athletes based on the coaches’ evaluation of

individual athlete competencies.

Building on this work, Fisher, Mancini, Hirsch, Proulx, and Staurowsky

(1982) established a direct relationship between coach behavior and influence on

team climate in their study of 50 youth basketball coaches. Using Cheffers’

Adaptation of the Flanders Interaction Analysis System (CAFAIS; Cheffers &

Mancini, 1989) to analyze coach–athlete interactions Fisher and colleagues

discovered variances within more satisfied and less satisfied teams. Specifically,

coaches with more satisfied teams were found to provide frequent praise and

delivered mostly concurrent instruction. In less satisfied teams coaches offered

less praise and often interrupted practice for extended periods of time to deliver

initiated instructions. Fisher and colleagues’ study indicated that coaches are at

large responsible for shaping the team climate. Specifically, positive team climates

emerge when coaches promote engagement in active learning, within an

autonomy-supportive environment (Mageau & Vallerand, 2003).

In sum coaching behavior directly influences athlete perceptions and

performance. However coaching behavior is also influenced by athlete behavior

and discrepancies seem to exist between actual coaching behavior and perceived

coaching behavior. Findings from coach-athlete behavioral interaction research

suggest that coaching behavior is frequently misinterpreted. Perhaps then, the key

to behavioral effectiveness lies with the coach and their ability to display coaching

behaviors that run congruent with the adopted style of leadership. Chellandurai’s

17 17

extensive research on effective leadership styles (1978; 1980; 1988; 1990; 1998)

supports this notion, and has established that athlete outcomes are optimized when

coaching behavior is congruent with leadership style.

Antecedents of Coach Behavior

Coaches’ personal values, beliefs, goals and expectancies have a significant

impact on how they interact with athletes (Horn, 2008). Coaches’ beliefs,

especially stereotypical ones are therefore likely to affect their interactions with

athletes. These beliefs include thoughts on gender, age, race and ethnicity (Horn,

Lox, & Labrador, 2006), and can result in stereotypical expectations and

differential treatment amongst athletes.

Messner (2000) uncovered differential treatment of athletes based on

gender, with youth sport coaches reinforcing gender stereotypes through their

behavior in early youth sport participants. Such differential treatment between

male and female participants is likely to affect athletic progress and the

psychological growth of youth athletes. Race and ethnicity is another dimension of

coaches’ stereotypical beliefs that has received attention. Brooks and Althouse

(2000) suggested that coaches who hold stereotypical race related beliefs (e.g.,

African American individuals are naturally gifted basketball players), may result

in differential treatment amongst athletes (e.g., opportunities for inclusion and

exclusion between African American and European American basketball athletes).

In turn, differential treatment can have a detrimental effect on motivation and the

emotional well-being of athletes.

Practitioners have drawn on achievement goal orientation theory (Ames,

1992a; 1992b) to predict the goal orientation of coaches. For example, coaches

who provide feedback concerned with individual skill mastery and emphasize the

18 18

importance of team success over individual achievement are considered to be ‘task

orientated’ coaches. Conversely ‘ego orientated’ coaches typically measure their

athletes against one another, and through their behaviors send a message that

certain athletes are of more value than others.

‘Mindset’ is another interesting perspective in identifying antecedents of

coach behavior (e.g., Dweck, Chiu, & Hong, 1995). Dweck and her colleagues

believe that ‘fixed mindset’ individuals view such traits as intelligence and the

ability to achieve in performance domains to be predetermined. In contrast those

who believe that such individual differences can be changed, developed and

improved are considered to possess a ‘growth mindset’. Therefore coaches who

adhere to a fixed perspective would be more likely to exhibit expectancy–biased

behaviors toward athletes (Horn et al., 2006). Conversely coaches who adopt a

growth mindset will be more open to the potential development opportunities of

their athletes.

Based on the four step self-fulfilling prophecy model employed in

educational research (e.g., Brophy, 1983) it is hypothesized that (1) coaches

develop expectations of their athletes at the beginning of a season, predicting the

athlete’s capabilities and level of performance over the course of the season; (2)

these expectations then affect how the coach interacts with each athlete, (3) having

a direct impact on athletic performance and (4) self-perceptions that conform with

the coaches predetermined expectations. Practitioners have focused their

investigations within individual steps of the self-fulfilling prophecy (e.g., Solomon

et al., 1996; Vealey, Armstrong, Comar, & Greenleaf, 1998), with results

providing support for the self-fulfilling prophecy phenomenon in the sport

domain. Particularly relevant to the performance sport setting is Solomon and her

colleagues’ (e.g., Becker & Solomon, 2005; Solomon 2001, 2002) work on

19 19

judgment, evaluations and expectations of collegiate coaches. This research

indicated that coaches draw upon individual player perceptions at the start of a

season to form their expectations of athletic ability, providing support for step one

of the self-fulfilling prophecy in sport.

However, constraints of the work place and the competitive level and age of

athletes will also determine how coaches behave (Gilbert & Trudel, 2004). A

number of studies have been undertaken to identify how coaching behavior differs

due to the competitive level and age of athletes (e.g., Chaumeton & Duda, 1988;

Halliburton & Weiss, 2002). General consensus indicates that coaches working

with athletes in the performance sport setting adopt a more autocratic style than

coaches working with youth sport participants. These findings indicate that

coaches working within the performance sport context perceive a greater pressure

to win and therefore revert to a more controlling style of coaching (Mageau &

Vallerand, 2003).

The link between personal characteristics and coach behavior has also been

examined. However the purpose of these investigations were not to demonstrate

how coaches’ perceptions affect their interactions with athletes but rather to

determine how coach decision making serves to predict coach behavior. For

example Abraham and Collins (1998) found that individual differences, such as

coaching experience and the ability to self-reflect play an important role in

predicting coaching action. From a sport psychology perspective research

consensus indicates that factors such as the coaches’ perceptions of coaching

efficacy (Sullivan & Kent, 2003) and motivational orientation toward coaching

(Losier, Gaudette, & Vallerand, 1997) also influence how coaches are likely to

behave in the sport setting.

CHAPTER 3: METHODOLOGY

An interpretative case study approach (Thomas, Nelson, & Silverman,

2005) with multiple methods of data collection and analysis was employed in

present study to develop a teaching behavior profile of coaching effectiveness in a

performance sport practice setting. An interpretative case study approach draws

on multiple sources of information in attempts to interpret, classify and

conceptualize data.

Participant

Standard ethics procedures indicate that the coach’s identity be concealed.

However during the present study the coach provided consent for his identity to be

revealed (see Appendix A for Coach’s Consent Form). The participant in the

present study is California State University, Fresno Head Women’s Basketball

Coach, Adrian Wiggins. Coach Wiggins was selected for the study as his profile is

consistent with how coaching effectiveness is currently defined. In 2009 Côté and

Gilbert proposed the Integrated Definition of Coaching Effectiveness, grounded in

coaching, teaching, positive psychology and athlete development. The Integrated

Definition of Coaching Effectiveness has three main components (a) coach

knowledge (b) athlete outcomes and (c) coaching context. Coaching effectiveness

is defined as the consistent application of knowledge intended to continually

improve well defined athlete outcomes within specific coaching contexts (Côté &

Gilbert, 2009). The participant in the present study works within the collegiate

basketball setting, in which the primary outcomes are (1) winning games and (2)

graduating student-athletes. The participant is required to prepare student-athletes

to compete in regular season Western Athletic Conference (WAC) play,

conference championship games and national championship basketball (NCCA).

21

Also, as a collegiate basketball coach the participant is responsible for graduating

student-athletes and in turn preparing student-athletes for life after basketball.

Adrian Wiggins became the head coach of the women’s basketball team at

California State University, Fresno during the 2005–2006 collegiate basketball

season. During the Wiggins’ tenure the women’s basketball team has accumulated

the most wins in the WAC, capturing four WAC Championships and appearing at

four NCAA Championships. Coach Wiggins holds the record for the highest

winning percentage amongst the current crop of WAC coaches (65-15), averaging

23 wins per season (CBS Interactive, 2011). Coach Wiggins was named WAC

coach of the year in the 2007–2008 and 2009–2010 collegiate basketball seasons.

Following the 2009–2010 season coach Wiggins was also named the Women’s

Basketball Coaches Association Region Seven coach of the year and was one of

eight nominated finalists for National Coach of the Year honors (CBS Interactive,

2011). Since taking the head coaching position of the women’s basketball team at

California State University Fresno, coach Wiggins has taught 20 student-athletes

who have earned academic All-WAC honors. The 2008–2009 season saw the

women’s basketball team post a 3.3 team GPA, the highest in seven years (CBS

Interactive, 2011) and a season later the all-time program record was tied for

academic All-WAC honors (6). This demonstrates that over the past six years

coach Wiggins has consistently produced championship winning teams and

successfully graduated high achieving student-athletes.

Data Collection and Analysis

Data collection and analysis was completed in three phases (see Table 1).

22

Table 1

Overview of Data Collection and Analysis Procedures

Phase Procedures Timeline

1 Preliminary Data Collection

2010 – 2011 Women’s Collegiate Basketball

season

Ten practices observed as part of the multi-

year study on coaching effectiveness

Creation of practice scripts for all 10 practices

10/15/10–

3/15/11

2 Creation of Teaching Behavior Profile

Training with systematic observation instrument

(TESCS)

Systematic observation of seven intact

practices

Proposition matrix and data report prepared

for the coach

9/1/11–

11/31/11

3 Validation of Teaching Behavior Profile

Exit interview with the coach to test teaching

behavior propositions

Review of exit interview

Revision of Proposition matrix / Creation of

Conclusion table

Exit interview transcribed

12/1/11-

1/15/12

Phase 1 – Preliminary Data Collection

The present study is part of a multi-year study on effective coaching in

action. The multi-year study intends to document effective coaching in action over

the course of two collegiate basketball seasons. Informed by a grounded theory

case study approach, year 1 of the study has drawn upon a range of techniques to

collect data and test emerging hypothesise in regard to coaching effectiveness. The

researcher in the present study has participated in all aspects of the data collection

process, videotaping the coach during practices and games, conducting interviews

23

with coaching and playing staff, transcribing coach and student-athlete interview

data and participating in bi-weekly research meetings intended to discuss

emerging hypotheses. The present study draws upon data collected from year 1 of

the multi-year study to examine teaching behavior in the practice setting.

In phase 1 of the multi-year study 10 practices during the 2010-2011

collegiate basketball season were selected for observation (see Table 2).

Table 2

Overview of Preliminary Data Collection Date of

Practice

Duration of

Practice

Practice Status (Partial or Intact)

10/15/10 20 minutes Partial: Pilot testing

10/29/10 60 minutes Partial: Observers left practice due to other

commitments

12/10/10 60 minutes Intact


1/26/11 25 minutes Partial: Coach left practice to attend meeting






Prior to the 2010–2011 collegiate basketball season the research team (two

faculty members and two graduate students) reviewed the WAC season schedule.

A review of the WAC season schedule enabled specific practices to be selected for

observation. It was hypothesized that specifically selected practices for

observation would provide the opportunity to observe the coach’s teaching

behavior in different situations across the duration of the collegiate basketball

season. For example practice 3/9/11 (see Table 2: Overview of Preliminary Data

Collection) was selected because this practice was the final practice before the

24

women’s basketball team headed to the WAC Tournament Final in Las Vergas.

Therefore the 3/9/11 practice provided the research team with the opportunity to

see if the coach’s behavior would differ due to the significance of this point in the

season.

To determine an appropriate number of practice observations the research

team reviewed the three previous observational studies conducted on collegiate

basketball coaches (Becker & Wrisberg, 2008; Bloom et al., 1999; Tharp &

Gallimore, 1976). A review of the three studies indicated that the number of

observations ranged from six practices (Becker & Wrisberg, 2008) to 15 practices

(Tharp & Gallimore, 1976). Therefore, observation of 10 practices appeared

appropriate for creating a valid teaching behavior profile.

Two members of the research team initially performed a pilot observation.

The pilot observation allowed the researchers to practice with the video recording

equipment and also enabled the coach to become familiar with the observational

procedures. Practice sessions were conducted at two different settings; on campus

in the north gymnasium and at the university’s main event centre (Savemart

Centre). The coach was consulted prior to observation and members of the

research team ensured they arrived 10 minutes prior to the start of each practice.

Video recording equipment was stationed in an unobtrusive position at the side of

the court. Prior to filming, the coach was informed that recording could be stopped

at any time and that he was free to turn off the wireless microphone. The purpose

of each observation was to specifically record the coach and therefore the

videotaped events tracked only the coach’s actions. During the observation period

recording was never requested to be stopped, nor did the coach choose to turn off

the wireless microphone.

25

Following the observational period two members of the research team–

including the author of this research study-reviewed the 10 practice films.

Employing an anecdotal recording approach (Van Der Mars, 1989) the two

observers created practice scripts for each of the 10 practices (see Appendix B for

Practice Script example). These scripts contain information on the practice

context, notes on predominantly observed teaching behaviors and general notes on

the coach’s style. Results of this informal analysis were used to prepare for phase

2 and phase 3 procedures.

Phase 2 – Creation of Teaching Behaviour Profile

During phase 2 of the study no new data were collected. The purpose of

phase 2 was to formally analyse the practice videotapes. Prior to systematic

observation the research team reviewed the 10 practice recordings to identify an

intact practice from a partial practice. Following a review of the 10 practices the

criterion for an intact practice recording was defined as; a practice recorded in its

complete duration, and a partial practice was defined as; an incomplete recording.

This criterion allowed the researcher to identify three partially recorded practices.

The three partial recordings were due to constraints within the collegiate

basketball context; on one occasion the coach had to leave the practice early to

attend a meeting, and on two occasions the observers had leave practice early to

attend to other commitments. Therefore, although 10 practice sessions were

recorded only seven intact practices were formally analysed as part of the present

study.

The Teaching Effectiveness in Sport Coding System (TESCS: Riddle &

Gilbert, 2011) (see Appendix C) was employed to systematically analyze the

seven intact recorded basketball practices. The TESCS is an adaptation of the

26

Coaching Behavior Recording Form (Tharp & Gallimore, 1976) and was selected

because the instrument provides frequency data on 15 instructional and non-

instructional teaching behaviors consistent with those observed in the studies of

coach Wooden (Tharp & Gallimore, 1976), coach Tarkanian (Bloom et al., 1999)

and coach Summit (Becker & Wrisberg, 2008).

Much like the CBRF, the TESCS enables the observer to code the

frequency of 15 instructional and non-instructional teaching behaviors. However

the TESCS was has two additional components. The two additional components

are; (1) Drill complexity and (2) Drill details. Drill complexity includes; (1) drill

familiarity, (2) drill conditions, (3) drill configuration, (4) drill intensity and (5)

drill focus. The second component; drill details enables the observer to reference

drill description including; (1) start and finish time of the drill and (2) cumulative

time and transition time between drills. As part of the multi-year study the coach

had already been asked to indicate drill complexity scores for each drill within the

seven intact practices. For each drill the coach assigned a complexity rating, with a

rating of ‘1’ indicating a low complexity drill and a complexity rating of the ‘3’

indicating a high complexity drill. Having these scores at hand enabled the

observer to document the drill complexity structures for each of the seven intact

practice sessions prior to staring the systematic observation analysis.

During the systematic observation of the seven intact practises each time a

specific behavior was observed it was coded on the coding sheet. The observer

took note of the start and finish time for each drill along with the cumulative time

and transitional time between drills. For each of the 15 instructional and non-

instructional teaching behaviors the rate per minute was calculated by dividing the

total frequency of each behavior by the specific drill length. This allowed a series

27

of teaching behavior comparisons to be made across drill complexities and

practice situations.

Following the systematic observation of the seven intact practices a data

report was prepared for the coach. The data report included a quantitative

summary of teaching behavior and a teaching behavior proposition matrix. The

teaching behavior proposition matrix was based on qualitative notes derived from

each of the seven practice scripts and also drew upon the researcher’s experiences

as part of the multi-year study. The quantitative data were derived from the

systematic observation of the seven intact practices. During the analysis the

researcher looked to identify connections between the quantitative data sets

presented in the teaching behavior profile and the teaching behaviors noted in the

practice scripts. Upon review of the data concurrent instruction was the most

frequently coded behavior (coded 1,173 times in total). Following this the practice

scripts were reviewed to see if concurrent instruction had been noted as a

prominent behavior. For example during the 3/15/11 practice the researcher noted

that “instruction was frequently directed, with coach often using cues such as

“move your feet”, “block out”, “get to the rim”, whilst the players were active in

the practice session”. Establishing number of propositions can be seen as

contextualizing step in the data analysis process (Dey, 1993; Maxwell, 1996) and

enabled the researcher to develop a theory of ‘what was going on’. For example

the theory proposition for the frequent use of concurrent instruction stated

“Concurrent instruction frequently exhibited by the coach to meet the perceived

duties of coaching. Less pre and post instruction offered to student-athletes during

practice. This can be attributed to the team’s experience. A senior laden team who

have reached a competent level of technical skill and tactical understanding.” In

28

phase 3 of the present study the teaching behavior profile and the propositions for

understanding teaching behavior were tested with the coach.

Phase 3 – Validation of Teaching Behavior Profile

In phase 3 of the study a 60-minute exit interview was conducted with the

coach. The exit interview took place in the basketball offices at California State

University, Fresno. The purpose of the exit interview was to see if the perceptions

of the coach matched the results of the proposition matrix. Given that the time

period between the final practice recording (3/15/11) and the actual exit interview

(1/1712) was almost nine months it was deemed that the coach had been given

adequate time to reflect upon his experiences before sharing his thoughts with the

researcher.

First, the researcher explained the systematic observation process, including

a definition for each of the 15 instructional and non-instructional teaching

behaviors. The coach was then presented with a data package. This package

included a behavioral profile containing the 15 instructional and non-instructional

teaching behaviors. Next to the 15 instructional and non-instructional teaching

behaviors were the actual percentage numbers for the coach’s exhibited behaviors

across the seven intact practices. However the percentages were randomly

assigned and the coach was asked to match the percentage numbers to the

behaviors he felt they most accurately represented. Following this the researcher

presented the coach with the actual study scores. Comparing the coach’s scores

with the actual study scores allowed the researcher to facilitate a discussion,

touching on and testing the behavioral propositions with the coach. Following this

the researcher explained the drill complexity scoring system to the coach. Using

this as a guide the researcher asked the coach to graph what he felt most accurately

29

represented the complexity of a typical basketball practice. After charting this, the

coach was presented with the actual drill complexity scores across the seven intact

practices. Again, revealing the results to the coach enabled the researcher to

facilitate a discussion and test theory derived from the proposition matrix. Finally

the coach was invited to make suggestions for further data analysis and the on-

going data collection process as part of the multi-year study.

The coach’s feedback helped to establish if the propositions were

representative of the coach’s actual–and current– teaching behavior. This helped

to contextualize the data and offered the opportunity to test the validity of the

findings. The exit interview was then transcribed and reviewed. The purpose of the

transcript review was to identify any points of discrepancy between the coach’s

explanation for behaving in the way that he did and the proposed teaching

behavior propositions. All points of discrepancy with the teaching behavior

proportion matrix were noted. Using the coach’s feedback a conclusion table was

created, and includes the coach’s rationale for the teaching behavior profile.

Therefore the conclusions drawn from the final teaching behavior data report

provide insight into the antecedents of teaching behavior (box 2, 3 & 4 of Horn’s

2008 working model of coaching effectiveness) within the collegiate basketball

practice setting.

Validity

Validity is the correctness or credibility of a description, conclusion,

explanation or interpretation of a given account (Maxwell, 1996). Validity is a key

component of research design and therefore in the present study numerous steps

were taken to address the validity of methods and interpretation of data (see Table

3).

30

Table 3

Overview of Validity Strategies Strategy Procedures

Context Familiarity Over one year of active participation in the multi-year

study within the collegiate basketball context.

Peer debriefing Participation in bi-weekly research meetings to review

ongoing data analysis.

Triangulation of

Methods

Information collected from a number of different

sources using a variety of methods (videotaped events,

coach interviews and field notes).

Systematic Observation

Training

Pilot film coding using the TESCS prior to formal

coding of the seven intact practice tapes.

Inter-Rater Reliability

Intra-Rater Reliability

Comparing coding scores with original coding scores

from pilot tape enabled the researcher to identify the

degree of agreement between raters (Guba & Lincoln,

1989).

Enabled the researcher to identify the degree of

agreement amongst multiple repetitions of testing.

Formal coding began when a score of at least 80 %

reliability was obtained.

Member Checking

Exit interview to test the teaching behavior

propositions with the coach.

Over 1 year of active participation in the multi-year study enabled the

researcher to become familiar with the collegiate basketball context and establish

rapport with the coach. Participation in the multi-year study has included

videotaping games and practices, conducting interviews with coaching and playing

staff, transcribing coach and athlete interview data and participating in bi-weekly

research meetings.

During the multi-year study teaching behavior data were collected from a

number of sources using multiple methods. Prior to observation two members of

31

the research team performed a 20-minute pilot test. The pilot test allowed the

researchers to practice with the video recording equipment and enabled the coach

to become familiar with the recording procedures prior to formal observation.

Prior to coding the seven intact practice films the researcher underwent a

period of systematic observation training using the TESCS. Systematic

observation training with the TESCS was crucial as it enabled the researcher to

reach a basic level of competence with the instrument (Van Der Mars, 1989). The

systematic observation training period included becoming familiar with coding

instrument and learning how to record behavioral data simultaneously. For

training purposes the researcher systematically analyzed a 120 minute practice

tape from a previous study conducted with a high school basketball coach (Riddle

& Gilbert, 2011).

Following coding the practice tape the researcher compared coding results

with original data from the study of the high school basketball coach. To check for

observer agreement the researcher conducted an inter-rater reliability test. This

enabled the researcher to identify the degree of agreement between the two raters.

The researcher calculated reliability scores for (1) drill complexity and (2) for each

of the 15 teaching behavior categories. Results of the inter-rater reliability test

revealed a reliability score of 90.07%. With a score of 80% or above indicating

reliability (Sidentop, 1976) the researcher then proceeded to code the seven intact

practices.

During the systematic observation of the seven intact practices, three

practices were selected for intra–rater reliability testing. Intra-rater reliability

testing enabled the researcher to identify the degree of agreement among multiple

repetitions of testing. When deciding which three practices to select for intra-rater

reliability testing the following variables were taken into consideration; (1)

32

practice duration (2) number of drills, (3) practice complexity and (4) frequency of

exhibited teaching behaviors. Across the seven intact practices, practice sessions

lasted between 60 minutes (practice 3) and 120 minutes (practice 4), with number

of drills ranging from 12 (practice 1) to 29 (practice 5). Practice complexity across

the seven intact practices ranged from 7 (practice 2) to 15 (practice 3), and the

total frequency of exhibited teaching behavior ranged from 214 (practice 3) and

1,438 (practice 2). With these variables in mind the researcher set about

identifying three practices for intra–rater reliability testing (the practices selected

for intra–rater reliability testing are shown in Table 4). After initial coding, each of

the three practices were re-coded. Re-coding the three practices enabled the

researcher to identify the agreement consistency, indicating scores for (1) drill

complexity and (2) teaching behavior. Results of the 3 intra-rater reliability tests

showed reliability scores of 97.78% (practice 1), 98.63% (practice 4), and 96.74

(practice 6). With a score of 80% or above indicating reliability (Sidentop, 1976)

the coding was deemed reliable.

In phase 2 of the study three practices were selected for reliability testing

(Table 4).

Table 4

Overview of Reliability Testing Date of

Practice

Practice Number

Overall r score

1/28/10 Pilot Testing 90.07%

12/10/10 1 97.78 %

2/15/11 4 98.63%

3/9/11 6 96.74%

Practice scripts from the larger study were drawn upon to create the

teaching behavior proportion matrix. The researchers’ attendance at the bi-weekly

33

research meetings continued to provide the opportunity for feedback and

debriefing on the creation of the teaching behavior propositions.

In the final stage of the study an exit interview was conducted with the

coach. The purpose of the interview was to test the teaching behavior propositions.

Testing the propositions with the coach improved the quality of the interpretations

and reduced the possibility of misinterpreting the teaching behavior data (Guba &

Lincoln, 1989).

CHAPTER 4: RESULTS

Introduction

A total of 10,878 teaching behaviors were coded across seven intact

practices observed during the 2010–2011 collegiate basketball season. The results

of the study are presented in four sections. These sections are; (1) Across Practice

Results (2) Within Practice Results (3) Coach Perceptions and (4) Final

Conclusions.

Across Practice Results

Across Practice Drill Complexity Score Profile

Drill complexity scores are calculated by coding and then multiplying the

five components of drill complexity. These are; (1) drill familiarity, (2) drill

conditions, (3) drill configuration, (4) drill intensity and (5) drill focus. The sum

total of these rating scores for each drill ranged from 7 (lowest complexity score)

to 10.7 (highest complexity score).

Table 5 provides an overview of the drill complexity data results across the

seven intact practices.

Table 5

Overview of Summary Drill Complexity Results Total Practice time

573 Minutes and 31 Seconds

Total Number of Drills

132

Mean Drill Complexity Score

9.1

Range of Drill Complexity Scores 7.2 – 11.3

35

Figure 2 shows the mean drill complexity score across the seven intact

practices. The mean drill complexity score across the seven intact practices was

9.1

Figure 2. Mean drill complexity score across the seven intact practices

Table 6 shows the occurrence of drills across the seven intact practices.

Although drill numbers range from 1 – 29, drills 1- 12 only appeared across the

seven intact practices. A drill frequency of seven indicates that the specific

number of drills (drills 1-12) was present in all seven practices and therefore

explains the flat lining effect in figure 2. (Please note that throughout the results

section drill number e.g., “Drill 1” represents the first drill of the practice and does

not relate to a specific drill).

Figure 3 shows the average drill complexity score for all drills across the

seven intact practices. Drill complexity scores ranged from 11.3 (drills #14) to 7.2

(drills #15).

36

Table 6

Frequency of Drill Occurrence Across the Seven Intact Practice

Drill # Drill Frequency DCS Mean DCS Range

1st 7 9.7 6-12

2nd 7 9.8 6-13

3rd 7 6.8 5-8

4th 7 8.1 7-10

5th 7 9 6-13

6th 7 9.7 7-13

7th 7 10.1 7-13

8th 7 10.4 7-13

9th 7 8.1 6-13

10th 7 9.2 7-14

11th 7 9.5 6-14

12th 7 10 7-14

13th 6 8.2 6-15

14th 6 9.7 7-14

15th 5 9.7 7-14

16th 5 7.5 6-9

17th 4 6 7-8

18th 3 10.4 7-13

19th 2 6 7-8

20th 2 6 7-8

21st 2 6 7-8

22nd 2 6 7-8

23rd 2 6 7-8

24th 2 6 7-8

25th 2 6 7-8

26th 2 6 7-8

27th 1 7 -

28th 1 8 -

29th 1 7 -

37

Figure 3. Across drills drill complexity average score

Across Practice Teaching Behavior Profile

Table 7 shows the definitions for the 15 teaching instructional and non

instructional behaviors coded using the Teaching Effectiveness in Sport Coding

System (TESCS).

Table 8 shows the behavioral rank for the 15 instructional and non-

instructional teaching behaviors across the seven intact practices.

Figure 4 shows the total frequency of observed teaching behavior across the

seven intact practices. The most frequently observed teaching behavior was

concurrent instruction (1,137) and the least exhibited behavior was Physical

Assistance (6).

Figure 5 shows the total percentage of teaching behavior observed across

the seven intact practices. Concurrent Instruction (21.6%) accounted for the

greatest percentage of teaching behaviors and Physical Assistance (0.1%)

accounted for the lowest percentage of teaching behaviors.

38

Table 7

TECSC Teaching Behavior Definitions

Code Description

PRIN Initial information given to player preceding the desired action to be

executed. It explains how to execute a skill, play, strategy, and so forth

associated with the sport.

CIN Cues or reminders given during the actual execution of the skill or play.

PIN Correction, re-explanation, or instructional feedback given after the

execution of a skill or play.

Q Any question to the player concerning strategies, techniques,

assignments, and so forth.

PASS Physically moving the player’s body to the proper position or through the

correct range of motion.

PMOD Demonstration of a correct skill or technique.

NMOD Demonstration of incorrect performance of a skill or technique.

H Verbal statements that are intended to intensify the efforts of the player.

PG Verbal or nonverbal compliments, statements, or signs of acceptance

without any direct emphasis on what is being complimented on.

PS Verbal or nonverbal compliments, statements, or signs of acceptance

with a direct emphasis on what or who is being complimented on.

S Verbal or nonverbal behaviors of displeasure.

CMG Verbal statements related to organizational details of practice while

player is physically active in the drill that does not refer to any skill or

strategy.

MG Verbal statements related to organizational details of practice while

player is physically inactive in the drill that does not refer to any skill or

strategy.

UNC Behavior cannot be seen or heard or does not fit into the above

categories.

FN Using the name of a player when speaking directly to the player.

39

Table 8

Teaching Behavior Rank Across the Seven Intact Practices Behavior Rank P#1 P#2 P#3 P#4 P#5 P#6 P#7

PRIN 4 8 10 8 11 10 10

CIN 2 1 3 1 1 1 1

PIN 5 5 7 5 7 7 8

Q 7 7 8 10 10 8 6

PASS 12 15 11 15 14 15 15

PMOD 12 13 11 13 13 12 13

NMOD 12 14 11 14 13 13 14

H 4 4 5 6 4 5 7

PG 6 3 9 4 3 2 3

PS 11 11 10 11 8 9 9

S 9 10 10 12 12 14 12

CMG 10 9 4 9 6 11 11

MG 3 6 1 3 5 4 4

UNC 8 12 6 7 9 6 5

FN 1 2 2 2 2 3 2

40

Figure 4. Total frequency of teaching behavior across the seven intact practices

Figure 5. Total percentage of teaching behavior across the seven intact practices

41

Figure 6 shows the total rate per minute score for observed teaching

behavior across the seven intact practices. The total number of teaching behaviors

observed across the seven intact practices was10, 878. The total practice time

observed across the seven practices was 573 minutes. The highest rate per minute

score was Concurrent Instruction (1.9) and the lowest rate per minute score was

Physical Assistance (0.01).

Figure 6. Total rate per minute (RPM) of teaching behavior across the seven intact

practices

Within Practice Results

Practice #1 Drill Complexity

The average drill complexity score for practice 1 was 10.8. The drill

complexity values across the 12 drills ranged from 7.0 (drill #l 4) to 14.0 (drill #8).

The flow of drill complexity across practice 1 is displayed in Figure 7.

Practice #1 Overview

An overview of Practice 1 results is provided in Tables 9 and 10.

42

Figure 7. Drill complexity flow score for practice 1

Table 9

Overview of Practice 1 Date 12/10/10

Duration 90:34

Number of Drills 12

Drill complexity Mean Score 10.8

Drill Complexity Range 7 - 14

Table 10

Overview of Teaching Behavior Profile for Practice 1 Teaching Behavior Frequency % RPM

PRIN 87 8.8 0.9

CIN 189 19.1 2.1

PIN 86 8.7 0.9

Q 48 4.9 0.5

PASS 0 0.0 0.0

PMOD 0 0.0 0.0

NMOD 0 0.0 0.0

H 87 8.8 0.9

PG 84 8.5 0.9

PS 20 2.0 0.2

S 24 2.4 0.4

CMG 22 2.2 0.2 MG 114 11.5 0.3

UNC 28 2.8 0.3

FN 198 20.7 2.2

43

Practice #1 Teaching Behavior Profile

Figure 8 shows the total frequency of observed teaching behavior for

practice 1 was 987. The most frequently observed teaching behavior was Full

Name (198) and the least exhibited teaching behaviors were Physical Assistance,

Positive Modeling and Negative Modeling (0).

Figure 8. Total frequency of teaching behavior for practice 1

Figure 9 shows the total percentage of teaching behavior observed for

practice 1. The highest percentage teaching behavior was Full Name (20.7%) and

the lowest teaching behavior percentage were Physical Assistance, Positive

Modeling and Negative Modeling (0.0%).

Figure 10 shows the total rate per minute score of teaching behavior

observed in practice 1. The highest rate per minute score was Full Name (2.2) and

the lowest rate per minute score was Physical Assistance, Positive Modeling and

Negative Modeling (0.0).

44

Figure 9. Total percentage of teaching behavior for practice 1

Figure 10. Total rate per minute score of teaching behavior in practice 1

45

Practice # 2 Drill Complexity


complexity values across the 14 drills ranged from 15 (drill # 13) to 8 (drills # 3

and 10). The flow of drill complexity across practice 2 is displayed in Figure 11.


Practice # 2 Overview


Table 11


Duration 104.40

Number of Drills 14


Drill Complexity Range 8 – 15

46

Table 12


PRIN 78 5.4 0.8

CIN 311 21.7 2.9

PIN 143 9.9 1.3

Q 89 6.2 0.9

PASS 6 0.4 0.1

PMOD 9 0.6 0.1

NMOD 8 0.7 0.1

H 157 10.9 1.4

PG 159 11.1 1.47

PS 39 2.7 0.4

S 42 2.9 0.3

CMG 59 4.1 0.6

MG 106 7.3 0.1

UNC 20 1.3 0.1

FN 212 14.74 1.2

Practice #2 Teaching Behavior Profile


practice 2 was 1,438. The most frequently observed teaching behavior was

Concurrent Instruction (311) and the least exhibited teaching behavior was

Physical Assistance (6).


practice 2. The highest percentage teaching behavior was Concurrent Instruction

(21.7%) and the lowest teaching behavior percentage was Physical Assistance

(0.4%).


observed in practice 2. The highest rate per minute score was Concurrent

Instruction (2.9) and the lowest rate per minute score was Physical Assistance

(0.1).

47



48




complexity values across the 16 drills ranged from 11 (drill # 6) to 6 (drills # 3, 5,

9, 11, 13 and 15). The flow of drill complexity across practice 3 is displayed in

Figure 15.


49



Table 13


Duration 37:18

Number of Drills 16



Table 14


PRIN 5 2.3 0.1

CIN 29 13.5 0.1

PIN 14 6.5 0.2

Q 9 4.2 0.4

PASS 0 0.0 0.0

PMOD 0 0.0 0.0

NMOD 0 0.0 0.0

H 20 9.4 0.5

PG 6 2.8 0.1

PS 5 2.3 0.1

S 5 2.3 0.1

CMG 25 11.7 0.1

MG 46 21.5 1.2

UNC 15 7.1 0.4

FN 35 16.3 0.9

Practice # 3 Teaching Behavior Profile


practice 3 was 214. The most frequently observed teaching behavior was

Management (46) and the least exhibited teaching behavior were Physical

Assistance, Positive Modeling and Negative Modeling (0).

50



practice 3. The highest percentage teaching behavior was Management (21.5%)

and the lowest teaching behavior percentage were Physical Assistance, Positive

Modeling and Negative Modeling (0.0%).


51


observed in practice 3. The highest rate per minute score was Management (1.2)

and the lowest rate per minute score was Physical Assistance, Positive Modeling

and Negative Modeling (0.0).



The average drill complexity score for practice 4 was 9.The drill

complexity values across the 18 drills ranged from 14 (drill # 10) to 5 (drill # 3).



An overview of Practice # 4 results is provided in Tables 15 and 16.

52


Table 15


Duration 92.14

Number of Drills 17

Drill complexity Mean Score 9


Table 16


PRIN 38 5.3 0.4

CIN 149 21.1 1.6

PIN 53 7.5 0.5

Q 27 3.8 0.2

PASS 0 0.0 0.0

PMOD 3 0.4 0.3

NMOD 2 0.3 0.2

H 52 7.3 0.6

PG 66 9.3 0.7

PS 17 2.4 0.1

S 11 1.2 0.1

CMG 29 4.1 0.3

MG 105 14.9 1.1

UNC 43 6.1 0.4

FN 112 15.1 1.2

53



practice 4 was 707.The most frequently observed teaching behavior was

Concurrent Instructions (149) and the least exhibited teaching behavior was






(0.0%).



Instruction (1.6) and the lowest rate per minute score was Physical (0.0).

54



55



complexity values across the 29 drills ranged from 14 (drill # 14) to 6 (drill # 3).





Table 17

Overview of Practice 5 Date 3/211

Duration 79:24

Number of Drills 29



56

Table 18


PRIN 13 2.0 0.1

CIN 135 21.2 1.7

PIN 42 6.1 0.1

Q 29 4.1 0.3

PASS 0 0.0 0.0

PMOD 1 0.1 0.1

NMOD 1 0.1 0.1

H 67 10.5 0.1

PG 69 10.1 0.1

PS 41 6.4 0.1

S 5 0.1 0.6

CMG 50 7.1 0.1

MG 56 8.1 0.1

UNC 34 5.0 0.4

FN 93 14.1 1.1









(0.0%)




(0.0).

57



58

Figure 26. Total rate per minute score of teaching behavior for practice 5



complexity values across the 18 drills ranged from 13 (drills # 8 and 13) to 6 (drill

# 1). The flow of drill complexity across practice 6 is displayed in Figure 27.


59



Table 19


Duration 86:47

Number of Drills 18



Table 20


PRIN 30 3.6 0.3

CIN 232 27.1 2.7

PIN 49 5.8 0.5

Q 33 3.9 0.3

PASS 0 0.0 0.0

PMOD 8 0.1 0.9

NMOD 7 0.1 0.8

H 61 7.1 0.7

PG 125 14.1 1.4

PS 32 3.1 0.3

S 2 0.2 0.2

CMG 24 2.9 0.2

MG 88 10.1 1.1

UNC 56 6.5 0.6

FN 108 12.6 1.2






60





(0.0%).


61




(0.0).

Figure 30. Total rate per minute score of teaching behavior in practice



complexity values across the 26 drills ranged from 13 (drills # 8, 10, 12 and 14) to

6 (drills # 2, 9 and 11). The flow of drill complexity across practice 7 is displayed

in Figure 31.



62


Table 21


Duration 80:14

Number of Drills 26



Table 22


PRIN 18 3.0 0.2

CIN 128 21.2 1.6

PIN 36 5.1 0.4

Q 45 7.4 0.5

PASS 0 0.0 0.0

PMOD 4 0.6 0.4

NMOD 3 0.5 0.3

H 41 6.1 0.4

PG 79 13.1 0.9

PS 19 3.1 0.2

S 10 1.1 0.1

CMG 14 2.3 0.1

MG 65 10.1 0.7

UNC 58 9.1 0.7

FN 82 13.1 0.9

63










(0.0%).




(0.0).

64



65

Coach Perceptions

In this phase of the study a 60 minute exit interview was conducted with the

coach. The interview took place in the basketball offices at California State

University, Fresno. The purpose of the exit interview was to see if the perceptions

of the coach matched the results of the proposition matrix. The researcher’s

propositions were grounded in quantitative data derived from the systematic

observation of the seven intact practices, and from qualitative data taken from the

practice scripts. Drawing upon both the teaching behavior profile and the practice

scripts allowed the researcher to develop a number of propositions. This enabled

the researcher to develop a theory of ‘what was going on’ (see Appendix D for

proposition matrix and for exit interview transcript notes). Summarized below are

the coach’s thoughts in regard to the research propositions.

The Role of Instruction

It was concluded that concurrent instruction was the highest scoring

behavior due to the coach’s need to fulfil the perceived duties central to coaching.

However the coach said that he saw concurrent instruction as a form of modeling.

The coach explained that he thought it was very important that he was an “active

participant” during practice time. The coach said he wanted to inspire energy and

enthusiasm within each player, and he felt the best way to cultivate this type

intensity was by leading through his own example.

Praise:Scold Ratio

It was concluded that the coach offered frequent praise to bolster team

confidence. The coach said he was glad to see that his praise frequency was higher

than his frequency for scold. The coach said he felt it was important that the

players left practice remembering the things they had done well, and that focusing

66

predominantly on positive aspects of performance during practice would help to

achieve this. In addition the coach pointed out that he did not perceive scolding to

be a negative behavior. The coach said he saw scolding as a positive aspect of his

work. To this coach scolding meant that he was correcting behaviour (opposed to

criticizing), and thus enabling the players to learn and grow.

The Role of Modeling

It was concluded that the coach rarely modeled because of his inexperience

as a basketball player. When discussing this, the coach admitted that he was never

a good basketball player and therefore lacked the physical skills to teach

effectively through modeling. Due to this the coach felt there was no value to be

gained in trying to teach through modeling. The coach went on to say that this

aspect of his coaching was of little concern to him as he felt he could draw upon

other teaching methods to get his message across to the players.

The Use of Student-Athlete First Name

It was concluded that student-athlete first name was used frequently used to

maintain a personable connection with the student-athletes and to emphasize his

instructions. The coach said that he felt addressing each player by name was an

essential component of effective teaching. The coach said that it was important

that each player knew that he cared and that he was paying specific attention to

them. The coach said this was especially important for the non- starters, as they

were not receiving recognition gained through playing time. The coach also said

that personalizing instruction helped engage the student-athletes in the teaching

and learning process.

67

Instruction vs. Management

It was concluded that the coach scored high in management due to the

composition of the team. At the time of the study the coach was leading a senior-

laden team, and therefore the researcher felt that the coach used more management

techniques (than instructional behaviors) to facilitate the existing competencies of

the team (rather than teach new skills). The coach acknowledged this to be

“partially true”, and then expanded his own view of effective teaching. The coach

felt that effectiveness depended largely on his ability to recognize and adapt to the

needs of the student-athletes. The coach said “I think this group (referring to

2011-2012 team) wants to learn more about basketball, so there will be more

opportunity for teaching. Last year’s group (senior laden 2010-2011 team) was

great but they just wanted to play, win and be done, they had no concern for

learning. This group is different, this group has a passion for learning about

basketball, which creates more opportunities to teach, so I think you have to look

at the people and the team, they should dictate where the coach goes.”

Across Practice Drill Complexity

It was concluded that across practice drill complexity scores were stable

due to the inherent demands of in-season collegiate basketball coaching. The

coach’s rationale for across practice drill stability revealed that the proposition fit

with the coach’s actual response. The coach explained that practice intensity

would follow a pattern and point of the season was an important component to

consider when structuring practice. The coach said that a practice a week prior to a

game would be planned and delivered at a low level of intensity, and that practice

intensity leading up to a game would be deliberately raised, ensuring that the

players were in the right “mode” to play.

68

Within Drills Drill Complexity

It was concluded that overall within practice drill complexity scores were

unstable as the coach structured practice to replicate the mental and physical

‘peaks’ and ‘valleys’ experienced in a basketball game. The coach explained that

he felt a basketball game did follow a predictable pattern, in which the players

would have to cope with periods of intense exertion, immediately followed by

periods of rest. With this in mind the coach said he tried to replicate these

conditions during practice. The coach felt the most effective way to prepare the

players for the mental and physical rigors of competition was to structure practice

around a “practice how we intend to play” mentality.

Average Drill Complexity Score

Average drill complexity scores across the seven intact practices were

stable. However there was fluctuation in drill complexity scores within each

practice. The coach stressed the importance of providing “practice stability” for

the players across the course of the season, but said that he never wanted the

players to become “too comfortable within the practice environment”. To ensure

this the coach said he aimed to make each practice “a little unpredictable”. The

coach referred to this as “creating unstructured conditions within a structured

practice framework” and is represented by the consistent ‘peaks’ and ‘valleys’

flow that characterizes the structure within each of the seven practices.

Coach Suggestions for Future Research

At the end of the exit interview, the coach was invited to make suggestions

for further data analysis. The coach highlighted two areas that he said he wanted to

know more about. These were; (1) uncodable teaching behaviors and (2) the

behavior of his coaching staff.

69

Uncodable Teaching Behavior

The coach was eager to learn more about the specific nature of behaviors

that were deemed to be uncodable. The coach felt that an uncodable score could

mean one of two things. The coach felt that he could be either wasting time, “like

why did I spend 5% of my day doing nothing?”, or that the uncodable moments

were actually very significant in the team building process, “I know there are

times in drills when a player will come by and I will say something that is very

specific and it’s meant just for them and it’s very motivational. Maybe that’s the

5% of time that really builds the team. Even with my assistant coaches I am

laughing, or making fun of someone, basically I am making sure we are on the

same page. So that could come out as uncodable and really I am being very

specific for a reason.” Therefore the coach was concerned to know what he was

doing during the 4.67% of time that was deemed to be uncodable.

Behavior of Coaching Staff

The coach was interested in extending the study of teaching behavior to the

entire coaching staff. The coach thought it would be beneficial to the ongoing

development of the basketball program to create teaching behavior profiles for

each of his assistant coaches. The coach envisioned a study that would enable each

coach to see how they compared to their colleagues. The coach said “I want them

to be aware of how involved, enthused and personable they are. I would like to

know how much time each coach is wasting during practice, and also what they

are doing well.” As part of the multi-year study the coach would like the research

team to film a further 10 practices and code the following behaviors for each of

the assistant coaches; Concurrent Instruction, Physical Assistance, Hustle, Praise

General, Praise Specific, Scold, Uncodable and Use of Student-Athlete First

Name. The coach felt that an analysis of these specific teaching behaviors would

70

enable him to see how effective they were performing, and would provide the

foundation for how they could improve as a coaching staff.

Summary

On the whole the coach said that the results of the study had confirmed to

him what he wanted to see, “In my mind I want to see that I am involved, that I am

enthusiastic, that I tell them (the players) three times as much that they did a good

job, that I am very specific with their names, it is not important that I am

physically doing it.” However as part of the multi-year study the coach said he

was keen for the research team to uncover the negative aspects of his practice, “In

general I want to hear more negatives than positives. The negatives are really

what help me get better.”

For the purpose of the present study the coach’s feedback helped to

establish if the propositions were representative of the coach’s actual–and current

– teaching behavior. This helped to contextualize the data and offered the

opportunity to test the validity of the findings.

The final conclusions are summarized in Table 23. Direct extracts from the

exit interview with the coach are included in the conclusions table to provide

context to the teaching behavior and drill complexity scores.

Conclusion Table

Table 23 shows the final conclusions. The conclusions are representative of

the coach rationale for exhibited teaching behaviour and the drill complexity

scores.

71

Table 23

Conclusions Table

Behaviour Conclusion Supporting Evidence The Role of Instruction

Concurrent instruction is the most frequently

occurring behavior. The coach viewed concurrent

instruction as a form of practice intensity

modeling.

Concurrent instruction the most frequently

recorded teaching behavior across the seven

intact practices (1,137).

“My thing is why would I ask them to do

something that I can’t do? So like I want them

to be talkative, energetic, enthused, in to it, so

I have to be. Active, that’s really it, everything

stems from that.”

Praise : Scold Ratio The coach exhibits a high praise and a low scold

ratio in order to bolster the confidence of his

players.

The praise to scold ratio was 7:1. Praise was

coded a total of 761 times during systematic

observation of the seven intact practices.

Scold recorded a total 99 times during

practice.

“I want to make sure that for every time I yell

at you, that three of four times I told you that

you did good. And I will remind them, that

hey listen, I know I said this one bad thing

and I know you will hold on to it, but I hope

you also hold on to the three or four good

things I said too.”


Due the coach’s inexperience as a basketball

player he seldom models techniques or tactics.

Modeling accounted for only 0.9% of all

behaviours across the 7 intact practices.

“I don’t actively do that a lot (modeling),

because I am not that good at it. I will do a lot

more modeling on defence than I do on

offence. Because physically I can mimic the

movement. Offensively I can’t mimic what I

am trying to teach them, I don’t have the skill.

And so why butcher it?”

72

Table 23. (Cont.)

Behaviour Conclusion Supporting Evidence The use of Student- Athlete Name

Frequent use of first name in order to emphasize

instruction and maintain a personable connection

with the student–athletes.

First name was the second most recorded

behavior and accounted for 15.4% of the

coach’s total behaviors.

“You are teaching them, I want them to

understand that I am talking to you. I want

them to know that I am paying attention to

you. Especially with the players that don’t

always play. I want them to know that I pay

attention to you too.”


Due to the team’s experience (senior laden team)

management is a central feature of the coach’s

practice behaviors. The coach draws upon

management to facilitate the existing

competencies of the student – athletes.

Management accounted for 14.8% of the

coach’s total behaviors and was the third

highest coded behavior.

“Last year’s group, they were great but they

just wanted to play, win and be done, they had

no concern for learning. This group has a

passion for learning about basketball which

creates more opportunities to teach.”

Across Practice Drill Complexity

Practice intensity and point of the season are

important components when considering

structuring practice intensity.

Drill complexity scores ranged from 10.7

(practice 2) to 7.0 (practice 3).

“If you came and observed on a Tuesday and

we didn’t play until the Saturday then it is

going to be low intensity, but if it is a day or

two before a game then hopefully it’s more

intense.”

73

Table 23. (Cont.)

Behaviour Conclusion Supporting Evidence Within Drills Drill Complexity Practices are structured to replicate the mental and

physical ‘peaks’ and ‘valleys’ experienced in

competition.

Drill complexity scores ranged from 11.3

(drill 14) to 7.2 (drill 15) and the within drills

drill complexity graphs depict a series of

‘peaks’ and ‘valleys.’

“Basketball has no pattern, it has no rhythm.

So I want them to go-stop, go-stop, go-stop,

so it’s important to me that they are operating

in that mode. There is no comfort zone in

basketball, So that’s how I try and practice

them.”

Across Practice Average Drill Complexity Score

Average drill complexity scores across the seven

intact practices were stable. However there was

fluctuation in drill complexity scores within each

practice. This is represented by the consistent

‘peaks’ and ‘valleys’ flow that characterizes the

structure within each of the seven intact practices.

The mean drill complexity score across the

seven intact practices was 9.1 and the mean

drill complexity score across all drills was 8.5

The coach stressed the importance of

providing “practice stability” for the players

across the course of the season, but said that

he never wanted the players to become “too

comfortable within the practice

environment”. To ensure this the coach said

he aimed to make each practice “a little

unpredictable”. The coach referred to this as

“creating unstructured conditions within a

structured practice.”

CHAPTER 5: DISCUSSION

Introduction

This chapter is divided into three sections. First, the theoretical implications

will be discussed. Specifically, how the results of the present study compare and

contrast with current research on effective coaching is considered. Second,

limitations of the present study are discussed and recommendations for future

research directives are offered. Finally, suggestions are made for coaching practice

and coach education.

Theoretical Implications


Results from the present study reveal that instruction was the most

frequently observed teaching behavior (34.3%). This finding concurs with

previous research on teaching behavior effectiveness in the performance sport

setting (e.g., Becker & Wrisberg, 2008; Bloom et al., 1999; Tharp & Gallimore,

1976). Results from the study of legendary UCLA basketball coach John Wooden

evidenced instruction as the most frequently occurring behavior (50.3%). Results

of the systematic observation of coach Tarkanian’s in practice teaching behaviors

revealed that instruction was also the most frequently occurring behavior (54.9%),

and results from the systematic observation of Coach Summit indicated that

instruction was her most predominant teaching behavior (48.1%). This implies that

instruction is an essential component of effective teaching, with the timing,

delivery and quality of instruction being of paramount importance (Potrac, 2000).

However in the studies of coach Wooden and coach Summit, instruction was

observed as one overall behavioral category and in the study of coach Tarkanian,

75

instruction was analyzed in regards to whether it was technical or tactical in

nature. In the present study instruction was delimited to three specific categories;

Pre Instruction, Concurrent Instruction and Post Instruction. In the present study

concurrent instruction, a teaching behavior delivered to athletes whilst engaged in

a skilled activity, was the most frequently observed instructional behavior (21.57

%). Although instructional behavior across the studies of coach Wooden, coach

Trakanian, coach Summit and coach Wiggins cannot be directly compared, it is

possible to draw comparisons based on the rationale’s offered by each coach for

why instruction was an essential component of teaching effectiveness. Coach

Wooden believed that delivering instruction to his players was the best way to

communicate ‘what to do’ and ‘how to do it’, and both coach Summit and coach

Tarkanian felt that instruction was the most effective way to provide student-

athletes with the necessary information required to successfully execute technical

and tactical skills . Results from the present study reveal that Coach Wiggins

foresees concurrent instruction as a form of intensity modelling. Specifically,

delivering a continuous stream of instruction was an opportunity for coach

Wiggins to demonstrate desired team behaviors to the players. Coach Wiggins

explained that he felt it was very important that he was an “active participant”

during practice. Coach Wiggins said he wanted to inspire energy and enthusiasm

within each player, and he felt the best way to cultivate this was by “leading

through his own example”. This finding indicates that similarities exist between

the predominant behaviors of effective coaches. However the differing rationales

offered by coach Wooden, coach Tarkanian, coach Summit and coach Wiggins

would indicate there is no stereotypical coaching personality which leads to

coaching success (Cushion, 2010), rather, this finding indicates that behavioral

76

effectiveness is dependent upon the coaches’ personal characteristics, values and

knowledge of their athlete needs.

Praise:Scold Ratio

In the present study praise accounted for 13.9 % of the coach’s teaching

behaviors, and scold for only 1.82% of exhibited teaching behavior across the

seven practices. Coach Wiggins said that the imbalance between the delivery of

praise and scold was intentional. Coach Wiggins believed that offering high

frequencies of praise during practice was critical in bolstering the confidence of

his players. Results from the present study are similar to Becker and Wrisberg’s

(2008) research on coach Pat Summit. Becker and Wrisberg’s observations

revealed praise as the second most observed behavior, representing 14.5 % of

coach Summit’s total behaviors. Coach Summit not only believed in praising to

reinforce correct executions of skills, but also believed praise would ensure

practice was a rewarding experience for her players. These finding indicate that

effective coaches understand the influence their behaviors have on athletes, and

therefore effective coaches take responsibility for, and behave in ways that serve

to increase athlete confidence, motivation, and perceptions of autonomy (Mageau

& Vallerand, 2003). Creating conditions in which confidence, motivation and

perceptions of autonomy are elevated has been described as an optimal climate for

learning (Ames, 1992). Conceptually an optimal learning climate focuses attention

on the mastery of performance, opposed to an outcome based focus adopted in

many traditional coaching climates. Through their behaviors coaches can shape

and nurture a climate focused on performance mastery. For instance coaches have

the power to define the meaning of “success” in the practice setting (e.g. coaches

can choose to reward athletes for demonstrating persistence and effort and refrain

77

from making judgements based on winning or losing.), these behaviors can help to

ensure that athletes feel component, play without a fear of failure and enjoy the

sport experience (Chelladurai, 1993; Horn, 2002; Jones, Armour, & Potrac, 2004;

Mageau & Vallerand, 2003; Smith & Smoll, 2002). Athletes who feel competent,

play free of worry and generally enjoy the sport experience are more likely to

experience intrinsic motivation and self determination (Mageau & Vallerand,

2003), Therefore there is a positive correlation between the learning climate

created by the coach and the athlete’s motivational orientation. In sum effective

coaches adopt a positive coaching approach, with predominantly positive

behaviors serving to increase athlete confidence, intrinsic motivation and

perceptions of autonomy (Mageau & Vallerand, 2003).


Results from the present study demonstrate that modeling was the least

frequently exhibited teaching behavior, accounting for only 0.84 % of the coach’s

total behaviors across the seven practices. The coach’s use of modeling in the

present study was considerably less than modeling evidenced in previous studies

on collegiate basketball coaches (Becker & Wrisberg, 2008; Bloom et al., 1999;

Tharp & Gallimore, 1976). This can be attributed to the coach’s lack of experience

as a basketball player. The coach in the present study has no experience as a

basketball player and by his own admission lacks the physical skills to teach

effectively through modeling. This finding refutes current thinking within coach

development literature, in which playing experience is thought to be an essential

component in the development of coaching expertise (Erickson, Côté, & Fraser-

Thomas, 2007; Nash, Sproule, Callan, McDonald, & Cassidy, 2009; Schinke,

Bloom, & Salmela, 1995; Werthner & Trudel, 2009). The coach in the present

78

study believed that playing experience was not essential, and that he could

overcome his lack of playing experience by being creative in his teaching

methods, drawing upon the knowledge of his assistants and senior players where

necessary. However results for modeling in the present study are similar to

findings from previous research in the collegiate basketball setting (e.g., Becker &

Wrisberg, 2008; Bloom et al., 1999; Tharp & Gallimore, 1976). In three previous

collegiate basketball studies modeling represented a score of below 5% for all

recorded teaching behaviors; coach Wooden (4.4%), Coach Tarkanian (2.2%) and

coach Summit (2.67%), demonstrating that modeling is not an common feature of

coaching effectiveness in the collegiate basketball practice setting. This can be

attributed to the performance sport setting, in which athletes are already highly

skilled and therefore desired skills can be verbally reinforced by coaches.

Furthermore the collegiate basketball setting practice is seen by coaches’ as the

opportunity to prepare teams for competition (Bloom et al., 1999), and therefore,

in order to be effective performance coaches must be efficient managers of their

time (Jones et al., 2004).

The Use of Student-Athlete First Name

To our knowledge the present study was the first study to document the

frequency with which an effective performance coach addressed the players by

first name. Results from the present study reveal the use of first name as the

second most recorded behavior, accounting for 15.4% of the coach’s total teaching

behaviors. Although there appears to be a lack of data in regard to the use of first

name in the study of coach behavior, links can be made to literature focused on the

coach–athlete relationship. Research on successful coach-athlete relationships

reveals that effective coaches look to establish a personable connection with their

79

athletes. Establishing a personable connection allows effective coaches to tailor

their coaching strategies to meet the specific needs of their athletes. During the

present study the coach emphasized his role as a teacher first, and felt the use of

first name prior to instruction allowed him engage each player in the teaching-

learning process. In the present study the coach felt frequent use of first name also

enabled him to demonstrate the deep care and focused attention he wants each

player to feel. The coach’s comments concur with the work of Jowett and Lavallee

(2006) and there research for understanding successful coach–athlete

relationships. Jowett and Lavallee’s research indicates that successful coach-

athlete relationships are mutually grounded in closeness and commitment and are

complementary and co–orientated (3 + 1 C’s in the Coach–Athlete Relationship).

Effective coaches therefore understand that initiating successful relationships first

requires a person-centred connection to be made (Jones et al., 2004). The

frequently consistent use of first name in the present study demonstrates that the

coach is continually striving to initiate and maintain the interpersonal connection

that binds coach and athlete together. Effective coaches therefore understand that

successful coach-athlete relationships stem from thoughtful and meaningful

communication, and are underlined by stability and dependability of

communication strategies (Jowett, Paull, & Pensgaard, 2005). Sincere and

personable communications allows athletes to know why, what, when and how to

perform (Jowett & Timson-Katchis, 2005), and therefore effective coaches who

possess a strong interpersonal connection with their athletes are more likely to

obtain their goals.

80


Results from the present study demonstrate that management accounted for

14.8% of the coach’s total behaviors and was the third highest coded teaching

behavior. Besides Becker and Wrisberg’s 2008 study of coach Summit, to our

knowledge the present study is the only other study to address management

behaviors in the performance sport setting. Becker and Wrisberg’s study revealed

that management compromised 9.34 % of all coach Summit’s teaching behaviors,

and was her fourth most frequently occurring teaching behavior. However, apart

from management being considered as a way to facilitate the organization of

practice, analysis of coach Summit’s teaching behavior offered no further insight

on the significance of management as part of the quest to understand coaching

effectiveness. At the time of the present study the coach acknowledged that

management was a central feature of his coaching role. The coach attributed this to

the experience level of his team; a senior laden team, boasting an array of

experience at the collegiate level of competition, had in the coach’s eye’s

“reached their potential.” With this in mind the coach felt his job was to simply

“steer the ship” before introducing and teaching a new wave of players in the

following season. The insight provided here concurs with current research on

coaching effectiveness, in which effective coaches recognize the inherent demands

of their coaching context and adapt to the needs of the athletes (Côté & Gilbert,

2009). Therefore effective coaches recognize that they must be flexible, and the

coach in the present study summarized this approach, “I think you have to look at

the people and the team, they should dictate where the coach goes.” The insight

provided by the coach supports what has been labelled an athlete–centred

coaching approach (Kidman, 2005). Athlete–centred coaches focus on athletes

needs first, and therefore the teaching profile adopted by the coach caters to the

81

needs of the athletes. However this does not mean power in the coach-athlete

relationship is ‘equal’ but rather shared, with athletes having a say in shaping and

defining their own direction (Arai, 1997). The coach in the present study can best

be described as a ‘facilitator of performance’, acting to guide his team toward their

goal (WAC Championship and NCAA Tournament Appearance). Underpinning

this is the concept of team culture. Team culture is a major philosophical

underpinning in athlete–centred coaching. Successful team cultures initially

depend on the coach’s ability to bring a group of individuals together, and unite

them in the pursuit of a common goal (Kidman, 2001). For an athlete-centred

approach to ‘work’ coaches must not only trust athletes to be serious about their

goals but athletes must trust the coach to make decisions and to ensure athlete

responsibility is the best thing for the team (Kidman, 2005). The present study

demonstrates that establishing a team culture, grounded in mutual trust and respect

between coach and athlete takes time. The coach in the present study has over the

course of four seasons established a group of senior leaders. The seniors acted as a

mediation group between coach and athletes, serving to communicate, uphold and

live out the values of the program. In essence the coach in the present study built

‘a team full of leaders’, demonstrating that people with power (coach) can act in a

manner that enhances rather than appropriates the power of others (Kidman,

2005). An athlete–centred coaching approach has been evidenced to have many

advantages for athletes including increased motivation, development of mental

toughness and a stronger interpersonal connection with the coach (Hadfield,

2002). Finally empowering athletes can help facilitate intrinsic desire, develop

self-efficacy, foster self-belief and create a willingness to engage totally in team

values (Kidman & Davis, in press).

82

Stability of Behavioral Profile

Behavioral signature is a concept that considers the influence of differing

situations on coach behavior (Erickson and Gilbert, in press). Despite observation

being conducted at different points of the season the teaching behavior profile

across the seven practices evidenced consistency of behavior. Specifically,

concurrent instruction was the most frequently observed teaching behavior within

five of the seven practices and the use of athlete first name was the second most

frequently observed behavior within five of the seven practices. This pattern can

be considered as part of the coach’s behavioral signature, with concurrent

instruction and use of athlete first name remaining consistent across the differing

practice situations (Smith, Shoda, Cumming & Smoll, 2009). However the

coach’s perceptions of his actual behavior were inaccurate. Although the coach

was close to matching actual teaching behavior scores with his own perceptions

for three of the 15 behavioral categories (e.g., Pre Instruction; 4.95% (actual)

4.10% (coach perception), Questioning; 5.15% (actual) 4.67%, (coach perception)

Hustle; 8.92% (actual) 7.78% (coach perception), he was unable to accurately

match any of the 15 teaching behavior scores (see Appendix D for coach’s

perceptions in full). Despite the behavioral miss-match the present study has

evidenced cross practice behavioral consistency, with the coach stressing

consistency as an essential component of effective coaching, “You always need to

be the face they (the athletes) need to see.” Although more research is needed in

the area of behavioral signatures, the present study indicates that behavioral

stability, namely the coherence of behaviors across practice situations is a

component of effective coaching in the performance coaching context.

83

Future Research Design

The multiple methods in present study allowed an in-depth analysis of

coach Wiggins’s teaching behaviors to be conducted. However if the present study

were to be carried out again three additional dimensions would be added to the

research design. These are (1) Coach-Centred Research Approach, (2) Interviews

with Playing and Coaching Staff and (3) Instrument Design. The three research

dimensions are outlined below.

Coach–Centred Research Approach

Discussing the results with the coach enabled the researcher to develop a

greater understanding of effective teaching behavior in action. The coach’s

feedback not only helped to validate the results of the present study but also

provided a rationale for why, in the practice setting, certain teaching behaviors are

more effective than others. Coach-researcher collaboration is essential not only in

advancing understandings of coaching effectiveness but also aiding coaches in

their quest to become more effective. Reflecting upon the results sharing process

with the coach it is suggested that future research endeavors should place the

coach at the heart of the research process. Therefore if the present study were to be

repeated, the coach would be encouraged to guide the research process. To achieve

this, the coach would first be consulted to find out what he wanted to learn more

about. The researcher would then use the coach’s feedback to design and

implement a study that addressed the coach’s current development needs.

Adopting a collaborative action research approach (Kemmis & McTaggart, 2000)

would enable the goals of research and the coach’s development needs to be met.

Through a coach–centred research approach, coaching science would gain unique

insight into coaching effectiveness (from the coach’s point of view) and coaches

84

would also be learning more about specific aspects of their coaching that they

consider key to becoming more effective.

Interviews with Playing and Coaching Staff

As part of the multiple-year study on coaching effectiveness in action two

additional research methodologies were employed, these included two focus group

interviews conducted with the student-athletes and individual interviews with the

assistant coaching staff. The interviews conducted with the playing and coaching

staff provide multiple perspectives on coaching effectiveness, and upon reflection

allow for a more holistic portrayal of coaching effectiveness to emerge.

Specifically, establishing if the perceptions of the coach (how he thinks he

behaves) concur with the perceptions of the players and the coaching staff (how

they perceive the coach behaves). Gaining student-athlete and coaching staff

insight would enable a more complete analysis of teaching behavior in the practice

setting to emerge. If the present study were to be conducted again, following the

observational period, interviews with playing and coaching staff would be

conducted. This approach would not only offer further insight into coaching

effectiveness, but would also provide the coach with additional feedback that

could aid in his quest for effectiveness.

Instrument Design

In the present study it emerged that the Teaching Effectiveness in Sport

Coding System (Riddle & Gilbert, 2011) was limited in its capacity to capture the

specific nature of teaching behaviors. This became apparent when the coach

learned that 4.67% of his time in practice was judged to be uncodable. The coach

was eager to learn more about the specific nature of this behavior, specifically the

85

coach felt that an uncodable behavior could be attributed to one of two things,

either that he was “simply wasting time” or that the instrument may not be able to

account for the behaviors he was exhibiting. The coach said, “Maybe the

uncodable moments were actually very significant to the team building process. I

know there are times in drills when a player will come by and I will say something

that is very specific and it’s meant just for them and it’s very motivational. So that

could come out as uncodable.” With coach’s thoughts in mind, it is recommended

that the development of future systematic observation instruments focus on the

specific content of teaching behavior (e.g., dimensions of feedback, dimensions of

praise, dimensions of scold, etc). This would enable a more specific and accurate

portrayal of behavioral effectiveness to emerge. It is recommended that future

research directives continue to incorporate measures specific to the sport, the

coaching context and the coach when considering the design of observational

instruments. For example within the present study the coach said it was important

that “each player knew that he cared”, and highlighted that paying specific

attention to the non-starters was especially important in practice. The coach felt

that the non-starters needed this type of “attention”, as they were not receiving the

recognition gained from playing time. For this coach it seems that who teaching

behaviors are directed at are equally as important as why certain behaviors are

exhibited. Therefore observational instruments that measure who coaches’ direct

their behaviors at can potentially shed light on coach-athlete relationship building

and effective coach–athlete communication strategies (see Erickson & Gilbert, in

press for overview of observational instruments.)

86

Practical Implications

A summary of the practical implications for coaches is provided in Table

24.

Table 24

Practical Implications for Coaches Coaching Behavior Guideline

The Role of Instruction Plan for the delivery of instruction

Tailor instruction to the specific learning needs of each

athlete

Deliver instruction in a clear and concise manner

Reflect upon the delivery of instruction

The Role of Praise and

Scold

Be positive

Exhibit behaviors that demonstrate support and

encouragement

Scold constructively

The Role of Modeling Provide quality demonstrations

Demonstrations should be brief, clear and simple

Demonstrations should provide information that helps

athletes to perform skills correctly

The Use of Student-

Athlete First Name Communicate with athletes in a personable way

Build a meaningful connection with athletes

Use of first name prior to delivering instruction can help

engage athletes in the teaching–learning process


and Management Understand the inherent demands of the coaching

context

Be flexible; adapt a coaching approach that is focused

on meeting athlete needs

87


Results of the present study demonstrate that instruction is an essential

component of effective teaching within the performance coaching context (Becker

& Wrisberg, 2008; Bloom et al., 1999; Tharp & Gallimore, 1976). Therefore

coach educators should endeavour to improve the instructional strategies of

coaches. Specifically coach educators should focus on how coaches can become

more effective in planning for the delivery of instruction. Planning for the delivery

of instruction was an essential component of effective teaching for legendary

UCLA basketball coach John Wooden. Coach Wooden spent almost as much time

planning for a practice as he did conducting it. Coach Wooden saw the value in

planning as it allowed him to create a lesson plan of important instructions to be

delivered as “teachable moments” during practice (Gallimore & Tharp, 2004).

These instructions focused on the specific learning needs of each player. This

enabled coach Wooden to deliver concise, improvement orientated instruction to

each player. Coaches should plan for the delivery of instruction, and these

instructions should be grounded in the specific learning needs of each athlete.

Delivering instruction that is grounded in the needs of each learner requires

coaches to know their athletes. Therefore coaches are encouraged to take the time

to get to know their athletes. This will not only help improve instructional

effectiveness but will also help coaches to establish successful relationships with

their athletes. Finally the importance of coach reflection cannot be underestimated

in the quest for coaching effectiveness. To again draw upon the exemplary

coaching practice of coach Wooden, who following each practice would set aside

the time to reflect upon how the learners had progressed. Reflecting upon each

practice enabled coach Wooden to set goals that addressed the learning needs of

each player in the following practice (Gallimore & Tharp, 2004).

88

Praise:Scold Ratio

Insight provided by the coach in the present study revealed that the

imbalance between praise and scold behaviors (Praise; 13.9% - Scold; 1.82%) was

intentional. Praise was deliberately offered in practice to bolster student-athlete

confidence. This finding indicates that effective coaches are not only aware of

their behaviors but also understand the impact their behaviors have on athlete

behavior. Specifically, praise can serve to increase athlete confidence, motivation,

and perceptions of autonomy (Mageau & Vallerand, 2003). Therefore coaches at

all levels should be aware that their behaviors can directly influence the

perceptions and performances of athletes. Therefore coach educators should

advice coaches to generally exhibit behaviors that demonstrate support and

encouragement for athletes.


Results from the present study are consistent with findings on behavioral

effectiveness in performance sport settings (Becker & Wrisberg, 2008; Bloom et

al., 1999; Tharp & Gallimore, 1976). Although modeling is not a common feature

of teaching effectiveness in the performance coaching context, it remains a

valuable component of effective teaching at all levels of coaching. Modelling can

be an effective teaching tool as it provides learners with a visual account of the

skill to be performed, and therefore the foundation of effective modeling is based

on the quality of the demonstration offered by the coach. Although various

recommendations for effective modeling exist, here legendary UCLA basketball

coach John Wooden is drawn upon to provide coaches with an example of

effective modeling in action. Coach Wooden’s modeling has been described as a

form of “artistry, serving to leave his players with an image in their memory much

like a text book sketch” (Gallimore & Tharp, 2004). Coach Wooden’s

89

demonstrations typically lasted no longer than three seconds, and followed a three

step ‘sandwich’ approach. In the first step a demonstration of how to correctly

perform the desired skill was given. This was followed by a demonstration of how

the skill had been incorrectly performed, and in the final phase the correct way to

perform the skill was remodeled. In sum, regardless of the modeling approach,

coaches should keep their demonstrations brief and aim to provide athletes with

quality information on how to perform skills correctly.

The Use of Student–Athlete First Name

Results from the present study revealed the use of first name as the second

most recorded teaching behavior, accounting for 15.4% of the coach’s total

teaching behaviors. During the present study the coach felt the use of first name

had two main benefits. These benefits included; (1) allowed a personal connection

to be made with each athlete and (2) the use of first name prior to instruction

enabled the coach to engage each player in the teaching-learning process.

Although there is a lack of research to support the use of first name in coaching

effectiveness, coaches at all levels are advised to develop quality relationships

with their athletes. Quality coach–athlete relationships are built upon trust, respect

and mutual understanding. Coaches are advised to communicate, behave and lead

in consistent manner. Coaches who lead through this example demonstrate that

they are dependable, credible and worthy of following. Communicating with

athletes on a personable level can facilitate meaningful connections, and in turn

enhance the quality of the coach–athlete relationship. Coaches are advised to be

active participants in the lives of their athletes. Achieving this could be a simple as

coaches scheduling time during practice to get to know their athletes.

90


The coach in the present study acknowledged that management was a

central feature of his coaching role. The coach attributed this to the experience

level of his team. Therefore coach educators can work with coaches to help them

identify the demands of their work place. Establishing work place demands will

enable coaches to identify the primary learning needs of their athletes. Once these

learning needs have been established coaches can then map out a plan of how to

best meet the needs of their athletes. Although each coaching context will present

its own unique challenges, it is important to emphasize that effective coaches,

regardless of the context are essentially athlete–centred. Coach educators should

therefore emphasize the importance of adaptability and encourage coaches to be

flexible in their approach.

Summary

Findings from the present study reveal that instruction was the most

frequently observed teaching behavior (34.3%). This finding concurs with

previous research on teaching behavior effectiveness in performance coaching

contexts (e.g., Becker & Wrisberg, 2008; Bloom et al., 1999; Tharp & Gallimore,

1976). This demonstrates that effective coaches play an active role in the

teaching–learning process. The second most frequently observed teaching

behavior was use of athlete first name (20.7%). Despite a lack of research on the

use of first name in effective coaching this finding concurs with the work of

Jowett and Lavllee (2006) and there research for understanding successful coach–

athlete relationships. Effective coaches understand that successful relationships

stem from thoughtful and meaningful communication, and the frequent use of first

name in the present study demonstrates that the coach is continually striving to

initiate the interpersonal connection that binds coach and athlete together. The

91

third most frequently observed teaching behavior was praise (14%). This findings

support the promotion of an autonomy supportive learning climate (Mageau &

Vallerand, 2003). Effective coaches understand that their behaviors can nurture

and shape a desired coaching climate, and therefore effective coaches exhibit

positive behaviors that serve to increase athlete confidence, intrinsic motivation

and perceptions of autonomy (Mageau & Vallerand, 2003).

Finally, becoming a more effective coach is built upon the concept of

possessing a growth mindset (Dweck et al., 1995). Like the coach in the present

study, coaches who possess a growth mindset are on a constant quest for

effectiveness. Effective coaches experience success because they are totally

committed to the process of continuous learning. However, ‘openness’ is the

foundation that underpins the concept of a growth mindset. Coaches who possess a

growth mindset are essentially open to new ideas and change. The coach in the

present study is a living, breathing example of ‘coaching openness’. Coach

Wiggins has experienced great success and could therefore have perceived little

value participating in this study. By participating in the present study coach

Wiggins has demonstrated his commitment to ongoing learning. To conclude

coaches are strongly advised to adopt a mindset of ‘openness’ and coach educators

can help facilitate this by encouraging coaches to engage in self study and critical

self reflection (Gilbert & Trudel, 2006).

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APPENDICES

APPENDIX A: CONSENT FORM – COACHES

103 103

CONSENT FORM – COACHES

The Project: The purpose of the proposed study is to document effective coaching in

action over the course of one full season of competition. Sport coaching has recently

emerged as a formal worldwide profession. Many developed countries are now investing

tens of millions of dollars into long-term coach development plans. As a result, there is a

growing demand for scientific research on effective coaching. To date the few studies on

effective coaching have relied on retrospective interviews or video analysis of a few

games or practices. The current study will be the first to combine multiple methods of

data collection over a full season with a coach in the midst of action. The methods of data

collection include interviews, document analysis, and video taping of games and training

sessions.

Analyzing and Reporting Results: All data will be analyzed by members of the research

team (Dr. Wade Gilbert, Mr. Tim Hamel, Mr. Matt Emmett, Mr. Nate Ferrante). All data

will be stored in the sport and exercise psychology laboratory at California State

University, Fresno. Only members of this research team will have access to the data. Any

information that is obtained in connection with this study and that can be identified with

you will remain confidential and will be disclosed only with your permission or as

required by law. If you give us your permission by signing this document, we plan to

disclose the outcome of the study in order to help other coaches and sport programs

improve their effectiveness.

Benefits and Risks: There are no anticipated risks to you as a participant in this study.

Potential benefits include increasing coaching effectiveness, networking and developing

positive connections with sport scientists and other coaches, developing an awareness of

the influence you have on athlete development in sport and life, and developing methods

for measuring and assessing personal coaching techniques and athlete outcomes. Upon

completion of the study you will be provided with a copy of the results if so desired.

Participation is Voluntary: Your decision whether or not to participate will not prejudice

your future relations with California State University, Fresno. If you decide to participate,

you are free to withdraw your consent and to discontinue participation at any time

without penalty.

Contact Information: For more information, feel free to contact Mr. Tim Hamel (278-

6049) or Dr. Wade Gilbert (278-5170). You will be given a copy of this form to keep.

YOU ARE MAKING A DECISION WHETHER OR NOT TO PARTICIPATE. YOUR

SIGNATURE INDICATES THAT YOU HAVE DECIDED TO PARTICIPATE,

HAVING READ THE INFORMATION PROVIDED ABOVE.

_______________________________ ____________________________________

Print Name Signature

APPENDIX B: PRACTICE SCRIPT EXAMPLE

105 105

PRACTICE SCRIPT EXAMPLE

Coach Wiggins Project: Practice Script

Date: 03/15/11

Location: North Gym Practice Court

Time: 10:15am – 12:30pm

Point in Season: In Season (approaching the NCAA Tournament)

Previous Result: Won vs. LA Tech 78 – 76 (WAC Tournament Final, Las Vegas)

Background Information:

All coaching staff present at practice

One of the last practices before leaving for the NCAA Tournament

General Notes:

Prior to practice discussing match ups with Coach Frank ahead of the North

Carolina game

Potential recruits in attendance at practice

Coaching Style:

Coach Wiggins is very relaxed, almost laid back - not a ‘normal’ “Wiggins

performance”

Coaching Behaviours:

Frequent Instruction – Directive cues “move your feet”, “block out”, “get to the

rim” whilst players active in practice drills

Positive Feedback / reinforcement “Good job”, “Nice”

APPENDIX C: TEACHING EFFECTIVENESS IN SPORT CODING SYSTEM

107 107

TEACHING EFFECTIVENESS IN SPORT CODING SYSTEM

Teaching Effectiveness in Sport Coding System

Wade Gilbert & Brian Riddle, California State University – Fresno, USA

Ron Gallimore, University of Los Angeles – California, USA

Introduction

The Teaching Effectiveness in Sport Coding System was developed to measure two

components of the teaching-learning environment in sport settings: (a) drill complexity

and (b) coach behaviors. Drill complexity refers to the organization and intent of the

drills that comprise a lesson. Coach behaviors refers to instructional and non-

instructional behaviors exhibited by the coach during the lesson that are intended to

direct and facilitate athlete learning. This coding system was created to assess specific

behavioral changes targeted by an experienced high school basketball coach. No existing

coding system adequately captured all of the setting and behavioral features identified by

the case study coach. Therefore, the current system was created based on a

comprehensive review of the systematic observation literature in physical education

teaching and sport coaching (Darst, Zakrajsek, & Mancini, 1989; More, 2008; van der

Mars, 1989). This coding system could not have been developed without the expert

feedback provided by Ronald Gallimore, Brad Ermeling, and Genevieve Ermeling on

multiple drafts of the coding system. The teaching behaviors component of this system is

an adaptation of the Arizona University Observation Instrument (ASUOI; Lacy & Darst,

1989; Solomon & Reece,1995), that is based on the coding system first developed by

Gallimore and Tharp (1976) in their pioneering observation study of legendary college

basketball coach John Wooden.

DRILL DETAILS

Drill # - identification number assigned to drill in chronological sequence

Description – brief statement about drill activity (What are they doing?)

Drill Duration

Start time – video counter time at which drill begins

Stop time – video counter time at which drill ends

Cumulative time (CT) – total time of drill in minutes and seconds

Transition time (TT) – time observed in between drills, from end of one drill to

player active participation in subsequent drill (athlete movement to next drill

location, equipment retrieval, listening to drill set-up / instructions, etc.)

DRILL COMPLEXITY

*Always record to the highest code within each category (i.e., if drill starts out 2v1, but

eventually works up to 5v5, would be recorded as Large Group and Exact Game

Requirement)

*Complexity scores in brackets at end of code description\

A. Drill Familiarity

108 108

1. Familiar to most players (FM) – drill so familiar to players that they can perform

automatically, or with minimal reminders and instructions [1]

2. Recently introduced (RI) – drill introduced within the past few practices; players

know the drill, but not fully, requiring "touch-up" instruction on how to perform it

[2]

3. New (NW) – first time introduced to players this season [3]

B. Drill Conditions

1. Non-game requirement (NGR) – conditions that would not be encountered in a

game situation (e.g., 10 free-throws, multiple undefended jump shots, jumping

rope) [1]

2. Simplified game requirement (SGR) – limiting game conditions under which a

skill must be executed (e.g., full court dribbling in lanes without defender, 3 v. 3

half-court) [2]

3. Exact game requirement (GR) – exact replication of game conditions under which

skill must be executed (e.g., pick and roll, man to man defense, 5 v. 5 full court,

etc.) [3]

4. Extreme game requirement (EXR) – conditions that are somewhat exaggerated

beyond normal game situation (e.g., 5 on 6 to elevate defensive difficulty) [4]

C. Drill Configuration

5. Individual (I) – simple drill performed by player alone (e.g., full court dribbling

undefended in lanes) [1]

6. Small group (SG) – drill that requires coordinated participation of 2 or more

players simultaneously, but less than actual requirements in a true game like

situation (e.g., 3 v. 3, 1 on 1 defending) [2]

7. Large group (LG) – drill that requires coordinated participation of five offensive

and/or five defensive players simultaneously [3]

D. Drill Intensity

8. Low intensity (LI) – drill requires minimum physical exertion (walking through

plays or offensive sets, free-throw shooting) [1]

9. Normal intensity (NI) – drill requires normal game-like exertion [2]

10. Maximum intensity (MI) – drill requires sustained maximum physical exertion

(sprinting full speed, racing to a loose ball, practice with taking charges, etc) [3]

E. Drill Focus

11. Individual techniques (IT) – fundamental skills (e.g., shooting, quickness) [1]

12. Individual tactics (ITA) – strategic skills required by a player to defeat an

opponent in a one-on-one situation. [2]

13. Team tactics - offense (TTO) – strategic skills requiring collective execution by

more than one player simultaneously while on offense [3]

14. Team tactics – defense (TTD) – strategic skills requiring collective execution by

more than one player simultaneously while on defense [3]

109 109

15. Combined (COM) – drill in which focus is on techniques and tactics, or offensive

and defensive tactics, simultaneously [4]

*Drill Complexity Score (DCS) = sum total of component complexity scores

COACH BEHAVIORS

The following codes are used to record all discrete teaching behaviors exhibited by the

coach during the session (game or practice). A discrete teaching behavior is defined as

“behavior exhibited by an instructor that has a clearly distinguishable beginning and

end” (van der Mars, 1989, p. 15). Furthermore “the beginning and end of a verbal

statement are, of course, characterized by the first and last word of that statement” (van

der Mars, 1989, p. 20). For example, if coach says in rapid succession ‘That’s it’ ‘That’s

it’ ‘Way to go’ ‘Head up’ ‘That’s it’, each one of these utterances should be coded as a

discrete teaching behavior because each one constitutes the beginning and ending of one

complete verbal statement.

A. Instructional Behavior

Instructional behavior is defined as the coach giving instruction to the athlete that is

directed at teaching a skill or team strategy.

1. Pre-Instruction (PRIN) – Initial information given to player preceding the desired

action to be executed. It explains how to execute a skill, play, strategy, and so forth

associated with the sport.

2. Concurrent Instruction (CIN) - Cues or reminders given during the actual execution

of the skill or play.

3. Post-Instruction (PIN) - Correction, re-explanation, or instructional feedback given

after the execution of a skill or play.

4. Questioning (Q) - Any question to the player concerning strategies, techniques,

assignments, and so forth.

5. Physical Assistance (PASS) - Physically moving the player’s body to the proper

position or through the correct range of motion.

6. Positive Modeling (PMOD) - Demonstration of a correct skill or technique.

7. Negative Modeling (NMOD) - Demonstration of incorrect performance of a skill or

technique

B. Non-Instructional Behavior

Although this is still instructional these behaviors are not intended to provide players

with specific instruction towards learning a skill or team strategy.

8. Hustle (H) - Verbal statements that are intended to intensify the efforts of the player.

9. Praise General (PG) - Verbal or nonverbal compliments, statements, or signs of

acceptance without any direct emphasis on what is being complimented on.

10. Praise Specific (PS) - Verbal or nonverbal compliments, statements, or signs of

acceptance with a direct emphasis on what or who is being complimented on.

11. Scold (S) - Verbal or nonverbal behaviors of displeasure

110 110

12. Concurrent Management (CMG) - Verbal statements related to organizational details

of practice while player is physically active in the drill that does not refer to any skill

or strategy.

13. Management (MG) – Verbal statements related to organizational details of practice

while player is physically inactive in the drill that does not refer to any skill or

strategy.

14. Uncodable (UNC) - Behavior cannot be seen or heard or does not fit into the above

categories.

15. C. Dual Codes

When a coaches speaks specifically to a player by calling the players name followed by

any of the above behaviors.

16. First Name - Using the name of a player when speaking directly to the player.

References

Darst, P. W., Zakrajsek, D. B., & Mancini, V. H. (Eds.). (1989). Analyzing physical


ed.). Champaign, IL: Human Kinetics.

Lacy, A. C., & Darst, P. W. (1989). The Arizona State University Observation Instrument

(ASUOI). In P. W. Darst, D. B. Zakrajsek, & V. H. Mancini (eds.), Analyzing physical


ed., pp. 369- 377). Champaign, IL: Human Kinetics.

More, K. (2008). Notational analysis of coaching behavior. In M. Hughes & I. M. Franks

(eds.), The Essentials of Performance Analysis (pp. 264-276). London: Routledge.

Solomon, G. B., & Reece, S. D. (1995). Training manual for the Arizona State University

Observation Instrument. Charlottesville, VA: University of Virginia.

Tharp, R. G., & Gallimore, R. (1976). What a coach can teach a teacher. Psychology

Today, 9(8), 75-78.

van der Mars, H. (1989). Systematic observation: An introduction. In P. W. Darst, D. B.

Zakrajsek, & V. H. Mancini (eds.), Analyzing physical education and sport instruction

(2nd

ed., pp. 3-17). Champaign, IL: Human Kinetics.

111 111

APPENDIX D: PROPOSITION MATRIX AND EXIT INTERVIEW TRANSCRIPT

113 113

PROPOSITION MATRIX AND INTERVIEW TRANSCRIPT NOTES

Thesis Results Meeting Summary

Coach Wiggins

Date: 1/17/12

Time: 9:30 – 10:30am

(59:12)

Coach Behavior Score Review

Coach Behavior Actual Percentage of

Behavior

Coach Wiggins

Behavior Score

Pre Instruction 4.95% 4.10%

Concurrent Instruction 21.57 % 4.95%

Post Instruction 7.78% 0/.11 %

Questioning 5.15% 4.67%

Physical Assistance 0.11% 1.82%

Positive Modeling 0.46% 3.18%

Negative Modeling 0.39% 8.92%

Hustle 8.92% 7.78%

Praise General 10.81% 15.44 %

Praise Specific 3.18% 10.81%

Scold 1.82% 21.57%

Concurrent Management 4.10% 0.46%

Management 10.66% 0.39%

Un - codeable 4.67% 1.82%

Full Name 15.44% 10.66%

114 114

Proposition Matrix

Behaviors Proposition Coach Wiggins Response

The Role of

Instruction

Concurrent instruction frequently

exhibited to meet the perceived duties

of coaching. Less pre and post

instruction offered to student -

athletes during practice. This can be

attributed to the team’s experience. A

senior laden team who have reached a

competent level of technical skill and

tactical understanding.

Although coach Wiggins scored

concurrent instruction low, upon

review he “could see why” it

was such a high scoring

behavior. He said he aims to be

“active” in practice.

“My thing is why would I ask

them to do something that I can’t

do? So like I want them to be

talkative, energetic, enthused, in

to it, so then I have to be. That’s

really it, everything stems from

that, so that’s really good, to me

that’s a good number because

that means I am actually

involved.”

Therefore Coach Wiggins see’s

concurrent instruction as a form

of modeling. An opportunity to

model the desired behaviors to

his players.

Praise / Scold

Ratio

Praise offered to bolster the team’s

confidence. Scold delivered when

deemed appropriate. Scold is directed

at specific members of the team and

is intended to ‘make an example of a

particular individual’. Scold is a

motivational tool used to unite the

group (‘prove the coach wrong’) and

teach the student - athletes how to

deal with adverse situations both on

and off the court.

Perceived scold to be a higher

scoring behavior than it actually

was. However “scolding” to

coach Wiggin’s means that “I

am correcting you, rather than a

negative tone, yelling or cussing

you out. That is why my scoring

of scolding is a little bit

skewed.”

The role of

Praise

General praise offered to bolster the

team’s overall confidence. Less

specific praise offered as the coach

“I’m glad that my praise is high.

I want to make sure that for

every time I yell at you (scold)

115 115

doesn’t want certain team member to

believe that they are more important

to the team than any other player.

that three of four times I told you

that you did good. And I will

remind them, that hey listen, I

know I said this one bad thing

and I know you will hold on to

that but I hope you hold on to the

three or four good things I said

too. That’s important to me, so I

like that a lot and it’s intentional,

so it’s nice to be reminded of

that.”

The role of

Modeling

Due the coach’s inexperience as a

basketball player he seldom models.

Therefore the coach often draws on

the student - athletes to demonstrate

sound techniques and tactical aspects

of play. A ‘bad’ demonstration given

by the coach could potentially

damage his credibility.

“I don’t actively do that a lot,

because I am not that good at it.

I will do a lot more modeling on

defense than I do on offence.

Because physically I can mimic

the movement. Offensively I

can’t mimic what I am trying to

teach them, I don’t have the

skill. And so why butcher it? I

can’t mimic the correct form on

shooting because I don’t shoot

very well. And it takes a lot of

energy, like I’m out of shape,

when I was younger I would

play with them a lot more but

now I can’t.”

The use of

student –athlete

name

To maintain a personable connection

with the student – athletes. Full name

is also drawn upon to emphasize the

instruction by the coach.

“Because I think you are

teaching them, I want them to

understand that I am taking to

you. I want them to know that I

am paying attention to you.

Especially with the players that

don’t always play. I want them

to know that I pay attention to

you too, so I do make a point of

hey I am talking to you right

now. I think that I am specific

about their behavior and to that

person as they relate to the

team.”

116 116

Instruction vs.

Management

Due to the teams experience (senior

laden team) management is a central

feature of the coach’s practice. The

coach draws upon management to

facilitate the existing competencies of

the student – athletes rather than

‘teach’ new skills.

“I think you are right partially

but I think this group (referring

to this season’s team) wants to

learn more about basketball, so

there will be more time to talk

more about it (teaching), like

they are capable of learning. Last

year’s group they were great but

they just wanted to play, win and

be done, they had no concern for

learning. They were going to do

what they were going to do, they

didn’t want to get too far beyond

that, and there skills sets

wouldn’t take them too far

beyond that. This group is

different they have more skills

sets, like they like playing

basketball more, they are very

intelligent kids, there GPA’s are

really high. So yes because they

are new but also yes because

they are capable. This group has

a passion for learning about

basketball and the newness,

which creates more opportunities

to teach, so I think you have to

look at the people and the team,

they should dictate where the

coach goes.”

The role of

Hustle

Hustle statements employed by the

coach to raise intensity within the

practice environment.

No specific data / feedback

The use of

Questioning

Questioning seldom drawn upon as a

teaching tool by the coach. This can

be attributed to the experience level

of the team. When questioning is

used it is generally to check for

student – athlete understanding.

No specific data / feedback

117 117

Variation in

drill complexity

scores across

the 7 intact

practices

Unstable structure of practice

complexity across the 7 intact

practices. This reflects the complex

nature of collegiate coaching, in

which results dictate the structure of

the next practice session. For

example a practice leading in to a

game may warrant the coach to

design a low intensity practice (low

complexity) and a practice following

a loss may require the coach to

deliver high intensity practice (high

complexity).

When asked to create a DCS line

score that represented what he

perceived to be a typical practice

structure coach Wiggins was

accurate in his recollection.

“If you came (and observed) on

a Tuesday and we didn’t play

until the Saturday then it is going

to look like this, kind of easy

(low intensity) but if it is a day

or two before a game then

hopefully it’s more intense.”

Variation in

drill complexity

scores within

drills

Drill complexity is depicted as a

series of ‘peaks’ and ‘valleys’. This

can be attributed to the coach

repeatedly emphasizing isolated skill

practices (‘valleys’; low intensity)

followed immediately by bouts of

conditioning (‘peaks’; high intensity

training).

“To be different. I think you

have to mix it up, I don’t want

them to be able to predict me. I

mean I am predictable but I want

to be unpredictable within that

structure. We always tell them

you have to be ready to play

anytime, anyone, anyplace, there

are no excuses, and you have to

be ready to go. It doesn’t matter

if the balls are flat, the gym is

cold, the rims are a different

size, the fans are mean, the refs

are bad, it doesn’t matter, and

you have to be ready to go.”

“Basketball has no pattern, it has

no rhythm. So I want them to go-

stop, go-stop, go-stop, so it’s

important to me that they are

operating in that mode, there is

no comfort zone in basketball.

So that’s how I try and practice

them, its peak and then shut it

down, lets relax them and then

lets intensify it again.”

Low - Moderate

drill complexity

score average

A low - moderate drill complexity

score across practices reflects the

team’s stage of development and the

coach’s relationship with the team.

So within that structure of

practice I like to make it

different. But with that I always

want is to intensify it, have a

118 118

The team is familiar with the plays,

drills and overall practice structure.

The coach is sticking with his “tried

and tested formula” as this

structuring has brought about

successful results over the past 4

seasons.

peak during practice, bring it

down and finish on a positive

note, with something easy which

they can feel good about. Across

the season I aim to achieve a

constant process of growth. Not

steep but progressive. Take your

time and slowly get better.”

Future Research Initiatives / Directives

- Un-codeable

“I think that you have got be careful on the Un-codebale part. It could go two ways, like I

am just wasting time, like why did I spend 5% of my day doing nothing, so I would be a

little worried about that. Or maybe that’s the 5% that really builds the team, maybe when

I walk by a Rachael Perkoda and say something, or maybe when I walk by Coach Frank

and say something, maybe those things are very intentional. I personally don’t think I

have too many times in practice where it’s not vet intentional. Even with my assistant

coaches I am laughing, or making fun of someone, basically I am making sure we are on

the same page. So I hope that un-codebale part is not wasted time, and that it is actually

very intentional. I know there are times in drills when a player will come by and I will

say something that is very specific and it’s meant just for them and it’s very motivational.

Like hey you haven’t hit a shot in three days V good job, and it’s sarcastic but I know she

is a great shooter and I know she can handle that. But say it was a Bree Farley, I would

never say that, because Bree Farley is a little more sensitive, she younger, she’s not ready

for that pressure. So with Bree I would say good job Bree, you are shooting really good,

man you are getting hot. I am making her think she is good. So that could come out as

un-codebale and really I am being very specific for a reason. So for me to have 5% that’s

a pretty high number, so I would want to know what I am doing in that time. Could you

show me those clips on the un-codebale? If you could put that on film and I could just

watch those, then I could see what I am doing.”

- Behavior of Coaching Staff

Film 10 practices and code the following behaviors of all the assistant coaches;

Concurrent Instruction, Physical Assistance, Hustle, Praise General, Praise

Specific, Scold, Un codeable and Full Name.

Develop teaching profiles for each coach. Create a book for effective teaching.

Compare each coach to one another. Show them where they stand compared to

their colleagues; how involved, enthused and personable is each coach? How

119 119

much time is each coach wasting during practice? What are they doing well?

Develop self-awareness within the entire coaching staff.

How effective are we as a coaching staff? How can we be more effective?

- Uncovering the Negative Aspects

“These numbers (the coded behaviors) validate what I do well, they confirm what I

want to see. In my mind I want to see that I am involved, that I am enthusiastic, that I

tell them three times as much that they did a good job, that I am very specific with

their names, it is not important that I am physically doing it. But in general I want to

hear more negatives than positives. The negatives are really what help me get

better.”

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Matthew Emmett

April 12, 2012

teaching behavior profile during practices of an effective ...

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