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The effect of conative and affective traits on the development of occupational expertise of civilian Department of Defense scientists and engineers

ProQuest Dissertations and Theses, 2011
Dissertation
Author: Eric C Sholes
Abstract:
One of the roles of an engineering manager is to manage and develop expertise within the workforce. To this end, effective knowledge worker management requires insight into psychology and how it relates to the development of expertise. Modern psychology theory identifies three modes of mental function: cognition, affect, and conation. This research examines the role of affect and conation in the development of expertise. Expert theorists have assembled a strong body of evidence which suggests that superior achievement depends on adaptation resulting from sustained purposeful engagement. A substantial amount of research is devoted to the role of cognition in enabling expert performance. However, conation and affect are also hypothesized to be influential factors, as they determine the motivation and approach of the individual towards continuous development. A survey instrument was compiled, consisting of a set of conative and affective traits hypothesized to influence expertise development and a construct representing expertise. The survey was distributed within a large, federally-funded research and development laboratory which operates in the aviation and aerospace industry, producing a total of 541 responses. The structural equation modeling (SEM) statistical method was utilized to model and analyze the relationship between conative and affective traits and the development of occupational expertise. The findings of this research support the hypothesis that conative and affective traits are influential during expertise development. The dissertation results indicate that positive achievement orientation holds a strong, positive influence on expertise development. The mastery goal type coupled with the approach goal posture is the only goal orientation which positively influences expertise development. Work engagement holds a positive influence on expertise development. Expertise theorists hypothesize that expert-level technical performance is achievable for any individual with normal cognitive ability. Unfortunately, the reality is that only a small segment of knowledge workers currently approach this performance threshold. If engineering managers can access even a fraction of the remaining untapped potential, the implications for society are tremendous. By understanding the role of conative and affective traits in expertise development, managers can enhance professional development infrastructure and training methods in order to better support expertise development.

TABLE OF CONTENTS

List of Figures

................................ ................................ ................................ ................

xiii

List of Tables

................................ ................................ ................................ ...............

xiv

List of Acronyms

................................ ................................ ................................ ........

xvii

Chapter

I. INTRODUCTION

................................ ................................ ................................ ....... 1

A. Background

................................ ................................ ................................ ...

3

B. Research Objectives

................................ ................................ ......................

4

C. Significance/Import ance of Research ................................ ............................

7

D. Summary

................................ ................................ ................................ .......

8

II. LITERATURE REVIEW

................................ ................................ ........................

10

A. Introduction

................................ ................................ ................................ .

10

a. Historical View of Human Performance

................................ ..........

10

b. Empirical Studies of Human Performance

................................ ......

13

c. History of Expertise Research

................................ ..........................

18

d. The Expertise and Expert Performance

Framework

........................

19

e. Mental Modes ................................ ................................ ...................

20

B. Expertise and Expert Performance in Professional Domains

......................

22

a. Characteristics of Expertise ................................ ..............................

24

b. Adaptation to Task Constraints

................................ ........................

25

c. Deliberative Practice

................................ ................................ ........

27

d. Professional Development Paths ................................ ......................

29

C. M ental Modes

................................ ................................ ..............................

30

x

D. Model Construct Selection

................................ ................................ ..........

34

a. Needs Theory

................................ ................................ ...................

36

b. Goal Theory

................................ ................................ .....................

40

c. Burnout and Work Engagement

................................ .......................

44

E. Summary ................................ ................................ ................................ ......

46

III. RESEARCH QUESTIONS AND HYPOTHESES

................................ ...............

48

A.

Introduction

................................ ................................ ................................ .

48

B.

Research Question

................................ ................................ ......................

48

C.

Conceptual Research Model

................................ ................................ .......

49

D.

Re search Hypotheses

................................ ................................ ..................

52

E.

Summary

................................ ................................ ................................ .....

61

IV. RESEARCH METHODOLOGY

................................ ................................ ..........

62

A.

Introduction

................................ ................................ ................................ .

62

B.

Organization

................................ ................................ ................................

64

C.

Description of Test Instruments

................................ ................................ ..

65

a . Achievement Orientation

................................ ................................ .

66

b . Goal Orientation ................................ ................................ ...............

69

c. Work Engagement

................................ ................................ ............

72

d. Expertise

................................ ................................ ...........................

73

D.

Model Specification

................................ ................................ ....................

76

E.

Research Model

................................ ................................ ..........................

76

F. Statistical Methods –

Psychometric Reliability and Validity

......................

77

a. Internal Consistency Reliability Analysis

................................ ........

77

xi

b. Construct Validity Analysis

................................ ............................

78

G. Statistical Methods –

Structural Equation Modeling

................................ ..

78

a. Multivariate Normality ................................ ................................ .....

80

b. Systematic Missing Data ................................ ................................ ..

81

c. Sample Size

................................ ................................ ......................

82

d. Model Specification

................................ ................................ .........

85

e. Model Fit

................................ ................................ ..........................

85

f. Data Analysis

................................ ................................ ....................

92

H. Summary

................................ ................................ ................................ .....

93

V. ANALYSIS AND FINDINGS ................................ ................................ ................

95

A. Demographics

................................ ................................ .............................

95

B. Evaluation of Test Instruments

................................ ................................ ...

97

a . Achieve ment Orientation

................................ ................................ .

98

b . Goal Orientation ................................ ................................ .............

102

c. Work Engagement

................................ ................................ ..........

105

d. Occupational Expertise

................................ ................................ ..

107

e. Summary of Psychometric Evaluation of Selected Instruments

....

109

C. Analysis of the Expertise Development Factors Measurement Model

.....

109

D. Dis cussion of Hypotheses

................................ ................................ .........

121

E. Summary ................................ ................................ ................................ ....

135

VI. CONCLUSIONS AND RECOMMENDATIONS

................................ ..............

137

A.

Contribution to Body of Knowledge -

Theoretical Implications

..............

137

B.

Contribution to Body of Knowledge -

Managerial Implications

..............

139

xii

C.

Assumptions and Limitations

................................ ................................ ...

147

D.

Future Research

................................ ................................ ........................

149

E.

Conclusions

................................ ................................ ...............................

153

APPENDIX A: COMPREHENSIVE SURVEY INSTRUMENT

.............................

156

APPENDIX B: IMPACT AND MITIGATION OF DATA NON - NORMALITY

....

164

APPENDIX C: DEMOGRAPHICS

................................ ................................ ...........

170

APPENDIX D: THEORETICAL MODEL DEVELOPMENT

................................ .

172

APPENDIX E: CROSS LOADING

................................ ................................ ..........

181

APPENDIX F: S TATISTICAL OUTPUT: EDFM M1

................................ .............

184

APPENDIX G: STATISTICAL OUTPUT: EDFM M2

................................ .............

194

APPENDIX H: STATISTICAL OUTPUT: EDFM M3

................................ .............

205

APPENDIX I: INSTITUTIONAL REVIEW BOARD DOCUMENTATION

..........

217

APPENDIX J: COPYRIGHT APPROVAL

................................ ...............................

219

APPENDIX K: PILOT RELIABILITY AND VALIDITY DA TA

............................

222

REFERENCES

................................ ................................ ................................ ...........

226

xiii

LIST OF FIGURES

Figure

Page

2.1 Professional Development Paths (Ericsson 2004)

................................ ................... 30

2.2 Tripartite Mental Modes Model

................................ ................................ ............... 32

3.1 Endogenous - Exogenous Structural Relationships

................................ ................... 50

3.2 Endogenous Structural Relationships

................................ ................................ ...... 51

3.3 Complete Structural Model

................................ ................................ ...................... 51

3.4 Causal Relationships in Expertise Development Factors Model

............................. 53

4.1 Research Methodology

................................ ................................ ............................ 62

4.2 Expertise Development Factors Model

................................ ................................ .... 77

5.1 Goal Orientation Scree Plot

................................ ................................ ................... 105

5.2 EDFM

M1

................................ ................................ ................................ .............. 110

5.3 EDFM M2

................................ ................................ ................................ .............. 117

5.4 EDFM M3

................................ ................................ ................................ .............. 119

D.1 EDFM T1

................................ ................................ ................................ .............. 174

D.2 EDFM T2

................................ ................................ ................................ .............. 177

D.3 EDFM T3

................................ ................................ ................................ .............. 179

D.4 EDFM M1

................................ ................................ ................................ ............. 180

xiv

LIST OF TABLES

Table

Page

3.1

Hypothesize Relationship of Exogenous Variables to Expertise

........................... 53

4.1

Achievement O rientation Construct Candidates

................................ .................... 67

4.2

Goal Orientation Construct Candidates

................................ ................................ . 71

4.3

Engagement Construct Candidates

................................ ................................ ........ 72

4.4

Expertise Construct Candidates

................................ ................................ ............. 74

4.5

Recommended Sample Size

................................ ................................ ................... 84

4.6

Goodness - of - Fit Measures

................................ ................................ ..................... 92

5.1

Sample Demographics -

Experience

................................ ................................ ...... 96

5.2

Sample Demographics -

Education

................................ ................................ ........ 96

5.3

Sample Demographics -

Job Category

................................ ................................ ... 96

5.4

Sample Demographics -

Project Type

................................ ................................ ... 96

5.5

Population and Sample Experience Distributions ................................ .................. 97

5.6

Achievement Orientation Reliability Analysis

................................ ...................... 99

5.7

Achievement Orienta tion (Faver) Factor Analysis

................................ .............. 100

5.8

Achievement Orientation (Ray) Factor Analysis

................................ ................. 101

5.9

Achievement Orientation (Ray) Rotated Factor Analysis

................................ ... 101

5.10

Goal Orientation Reliability Analysis

................................ ................................ .. 102

5.11

Goal Orientation Validity Analysis (w/ Varimax Rotation )

................................ 103

xv

5.12

Goal Orientation Validity Analysis w/ Four Factors

................................ ........... 104

5.13

Work Engagement Reliability Analysis ................................ ............................... 106

5.14

Work Engagement Factor Analysis

................................ ................................ ..... 107

5.15

Occupational Expertise Reliability Analysis

................................ ....................... 107

5.16

Occupational Expertise Factor Analysis

................................ .............................. 108

5. 17

Goodness - of - Fit Indices and Interpretation Criteria

................................ ............ 110

5.18

Goodness - of - Fit Statistics –

EDFM M1

................................ .............................. 111

5.19

Large Error Term Cross - Loadings

................................ ................................ ....... 116

5.20

Goodness - of - Fit Statistics –

EDFM M2

................................ .............................. 117

5.21

Correlated Error Terms

................................ ................................ ........................ 118

5.22

Goodness - of - Fit Statistics –

EDFM M3

................................ .............................. 119

5.23

Hoelter‟s N Index Values for EDF Models

................................ ......................... 120

5.24

Statistical Power of EDF Models

................................ ................................ ......... 120

5.25

Unstandardized Structural Model Regression Weights

................................ ....... 123

5.26

Model Covariances

................................ ................................ .............................. 123

5.27

Standardized Structural Model Regression Weights

................................ ........... 124

5.28

Model Correlations

................................ ................................ .............................. 124

5.29

Hypotheses and Conclusions for Endogenous - Exogenous Relationships

.......... 132

5.30

Hypotheses and Conclusions for Endogenous Relationships

.............................. 134

B.1

Assessment of Normality

................................ ................................ ..................... 167

xvi

D.1

EDFM T1 Causal Path Regression Weights

................................ ........................ 176

D.2

EDFM T1 E xogenous Covariances

................................ ................................ ..... 176

D.3

EDFM T2 Causal Path Regression Weights

................................ ........................ 177

D.4

EDFM T2 Exogenous Variable Cross - Loadings

................................ ................. 177

D.5

EDFM T3 Regression Weights

................................ ................................ ............ 179

D.6

EDFM T3 Covariances

................................ ................................ ........................ 179

E.1

Occupational Expertise Correlated Errors

................................ ........................... 182

E.2

Work Engagement Co rrelated Errors

................................ ................................ ... 183

E.3

Goal Orientation Correlated Errors

................................ ................................ ...... 183

K.1

EDFM Construct Reliability -

Pilot

................................ ................................ ..... 223

K.2

EDFM Construct Eigenvalues -

Pilot

................................ ................................ .. 223

K.3

Faver Achievement Orientation Factor Analysis -

Pilot

................................ ...... 223

K.4

Ray Achievement Orientation Factor Analys is -

Pilot

................................ ........ 224

K.5

Goal Orientation Factor Analysis -

Pilot

................................ ............................. 224

K.6

Work Engagement Factor Analysis -

Pilot

................................ .......................... 225

K.7

Work Engagement Factor Analysis –

(Forced to Three Factors) -

Pilot

............. 225

K.8

Occupational Expertise Factor Analysis -

Pilot

................................ ................... 225

xvii

LIST OF ACRO NYMS

ADF

Asymptotically Distribution - Free

AGFI

Adjusted Goodness of Fit Index

AO

Achievement Orientation

ASTD

American Society of Training and Development

AMOS

Analysis of Moment Structures

AMRDEC

Aviation and Missile Research, Development, and Engineering Center

CFI

Comparative Fit Index

CI

Confidence Interval

CMIN

χ 2

Function, As Reported in Statistical Software Package

CR

Critical Ratio

DoD

Department of Defense

DF

Degrees of Freedom

EDF

Expertise Development Factors

EDFM

Expertise Development Factors Model

FMIN

Minimum Fit Function

GEM

Generalized Expertise Measure

GFI

Goodness of Fit Index

GO

Goal Orientation

HI

Upper Boundary of Confidence Interval

IFI

Incremental Index of Fit

IQ

Intelligence Quotient

LO

Lower Boundary of Confidence Interval

M

Model

MI

Modification Index

MAP

Mastery Approach

MAV

Mastery Avoid

NFI

Normed Fit Index

NO

Need Orientation

OE

Occupational Expertise

P

Probability Value

PAP

Performance Approach

PAV

Performance Avoid

PE

Professional Expertise

R&D

Research & Development

RDT&E

Research, Development, Test & Engineering

RMR

Root Mean Square Residual

RMSEA

Root Mean Square Error of Approximation

SE

Standard Error

SEM

Structural Equation Modeling

SPSS

Statistical Software Package

SRMR

Standardized Root Mean Square Residual

TLI

Tucker Lewis Index

UWES

Utrecht Work Engagement Scale

WE

Work Engagement

1

CHAPTER I

INTRODUCTION

Tremendous resources are dedicated to employee training and development, particularly for knowledge workers. The American Society for Training and Development (ASTD) 2009 State of the Industry Report (Paradise and Patel 2009) estimates that, despite difficult economic conditions, in 2008 U.S. organizations invested $134.07 billion, or an a verage of $1,068 per employee on training and development. Training and development expenditures as a percentage of payroll averaged 2.24 percent (Paradise and Patel 2009). However, there are indications that despite this staggering level of investment, training activities do not always produce the expected outcome in terms of increased employee knowledge and productivity or expanded organizational core competencies.

In a letter to P. Senge on the topic of learning organizations, W. E. Deming (per sonal communication, 1990) stated that “the prevailing system of management has destroyed our people. People are born with intrinsic motivation, self respect, dignity, curiosity to learn, joy in learning … The job in management should be the optimization of the system” (Senge 2006). These comments emphasize the importance of enabling continuous development of employees or channel learning activities towards the strategic objectives of the firm. Echoing the value of developing core competencies which supp ort strategic objectives, Torraco and Swanson (1995, 11) state that “business success increasingly hinges on an organization‟s ability to use its employees‟ expertise as a factor in the shaping of its business strategy.”

2

Emerging research suggests t hat a possible explanation for the ineffectiveness of prominent contemporary methods for training knowledge workers is widespread misunderstanding of how knowledge workers develop and what training methods aid or support this development process. Over the

past several decades, the field of cognitive psychology has made a concentrated effort to improve understanding of what developmental activities enable expert level performance (Chi, Glaser, and Farr 1988; Ericsson and Smith 1991; Sternberg and Grigorenko , 2003). The culmination of that research is the Cambridge Handbook of Expertise and Expert Performance, which examines the developmental patterns which support superior performance in a wide variety of fields (Ericsson, Charness, Feltovitch, and Hoffman 2006). This body of knowledge is referred to as the Expertise and Expert Performance Framework.

The Expertise and Expert Performance Framework indicates that superior performance in cognitive disciplines depends on the development of cognitiv e tools and strategies which are developed over an extended period of continuous improvement and are enabled through sustained purposeful engagement (Ericsson 2006). This research effort investigates what factors influence the development of occupational expertise in interdisciplinary technical domains which require mastery of dynamic, varied, and complex c ognitive skills and abilities.

The central focus of this dissertation is to investigate the nature of expert performance and explore potential application of the Expertise and Expert Performance Framework to address the critical need to improve management and training of knowledge

workers in the field of engineering. In order to improve training and development of knowledge workers, managers must better understand the factors which promote high performance.

3

Pursuit of this objective requires considering whether high performance is

a product of innate characteristics, environmental fa ctors, or a combination of both.

If innate characteristics play a role, then what innate characteristics are associated with high performance?

If environmental factors play a role, why do some individ uals continue to progress while the development of others within the same environment reaches a plateau? If the factors which explain differential achievement can be identified, is it possible to proactively facilitate increased mastery of expertise?

I mproved understand ing

of these issues may yield insight into what specific support infrastructure or conditions could help promote improved training and development programs for knowledge workers.

A.

Background

For the purposes of academic study, expe rtise is defined as the ability to consistently reproduce superior performance in either absolute or normative terms. The focus of expertise research is twofold: 1) to expand insight into what cognitive elements are required to enable consistently superio r performance and 2) to improve understanding of how those required cognitive elements develop. Research to date establishes that expertise develops over an extended period of sustained purposeful engagement (Ericsson, Krampe and Tesch - Romer 1993; Ericsso n and Charness 1994). During this period, individuals who are successful in building expertise exhibit a pattern of incremental progress by systematically addressing their perceived weaknesses. Over time this process results in development of a set of ne urological and/or physiological adaptations, enabling circumvention or mitigation of constraints which limit performance

4

and enable the individual to improve domain specific performance (Ericsson and Lehmann1996).

Building on this foundation,

current research in the domain of expertise seeks to expand understanding of domain structure, integrated knowledge, domain specific pattern recognition, and methods of defining and solving both well - structured and ill - structured problems (Ericsson, Charn ess, Feltovitch, and Hoffman 2006; Ericsson 2009). Meanwhile, a critical need remains to improve understanding of how expertise is attained, what teaching and training methods are best suited to foster expertise, and how development opportunities and lear ning experiences should be structured to promote expertise development.

B.

Research Objectives

Technology - driven disciplines, such as engineering, depend on the development and sustainment of technical competencies in interdisciplinary technical domains.

To achieve this objective in a field where the required knowledge base is expanding rapidly requires engineering professionals to continuously learn and refine their skills throughout their career s .

While this critical professional development t ask can be daunting, emerging research presents insight that can be used to improve the management of development and training activitie s, potentially enabling

continuous development and refinement of individual skills and knowledge and, in turn,

raising t he cor e competencies of the collec tive organization substantially in the process (Ericsson 2009).

Expertise research indicates that, in

a set of individuals receiving

instruction

in the same environm ent , some will progress further towards expertise

than their peers

5

(Ericsson and Charness 1994) .

Although the long held assumption is that performance differences are the product of differential levels of innate talent, t he differentiating factor is actually empirically proven to be the q uantity, qualit y, and structure of practice

(Ericsson, Krampe, and Tesch - Romer 1993, Krampe 1994; Ericsson and Charness 1994 ) .

But, while establishing this poin t resolves one set of

questions by correctin g long held misconceptions which

underestimate the potential of th e average individua l to produce greatly improved performance , it also raises new questions. What drives one set of individuals to engage in more practice than others? What compels some

individuals to organize their practice sessions more systematically, organizing their practice into a series of incremental objectives and designing practice methods that provide immediate feedback?

What makes one set of individuals allocate their practice sessions into the short, intensive periods that produce the highest

yield while other individuals establish alternative routines?

In advancing towards the goal of fostering expertise development, these important issues remain largely unexplored.

In order to put the framework to practical use, the goal is not just to comprehend the nature of expertise but to understand how to propel individuals within the organization ,

whose development is stalled or constrained ,

towards continuous growth and how to sustain or accelerate the advancement and growth of individuals who

are already advancing. Posner

(1998 , xxxiii - xxxv ) stated, “The burden of this work on expertness is a hopeful one. Ordinary people seem to have within them a potentiality for expertise, should they be able to acquire the large technical vocabulary and ma ke the long commitment of study that such expertise requires. … The problem of producing an expert

6

may not be so much in selecting someone that has a special capability, but to create and maintain the motivation for long continued training.”

While pr ogress to date towards this objective is limited , there is a path towards improved understanding of expertise developm ent. Ackerman and Beier (2006,

15 7) note that personality traits (affect and conation) “ represent an area of great promise for prediction

of the development and expression of expertise, but this area has littl e substantive evidence to date.” A ffect deals with the experience of feeling and attitudinal orientatio n (emotion) whereas

conation deals with how those thoughts and feelings drive an

individual to act (motive) (Lavidge and Steiner

1961).

While cog nition explains what happens

during each step of maturation in performance level or skill on the path towards expertise, conation and affect

influence

what motivates individuals towar ds continued growth, how the individual views personal development, and how the individual approaches self improvement. Insight into these questions may reveal what infrastructure and methods are needed to cultivate expertise development and help managers

improve training and development within their organizations.

The objective of this study is two - fold. The first objective is to utilize the statistical structural equation modeling (SEM) technique to model the relationship between conative and affe ctive traits and the development of occupational expertise . The

second objective is to apply the model to characterize the effect of conative and affective effects on development of o ccupation expertise within the domain of engineering research and devel opment.

7

C.

Significance/Importance of Research

There is a mounting body of evidence that existing professional development systems are not equipped to establish requisite levels of professional expertise to establish and maintain

a competitive position in the complex, fast - paced contemporary business environment (Ericsson 2009). Davis (2009,

196) states that it is apparent that professional development will inevitably “move from reliance on the update models and systems that coun t only formal activities, to a more performance -

or outcome - driven model, in which feedback on objective measures of competence and performance are married to a better understanding of effective educational methods.” Performance -

or outcome - driven trainin g involves enabling continuous development and adaptation of professional knowledge and skills through a mutually self - governed cycle of performance evaluation, competency assessment, and self directed learning.

This research effort is designed to e xpand

insight into how the Expertise and Expert Performance Framework

can be harnessed to enable the needed shift towards continuous development and skill adaptation. This project will 1) build insight into the relationship between achievement orientation

and

expertise development, 2) examine

how to structure and manage goals to foster expertise by expanding insight into the relationship between goal orientation and exp ertise development, and 3) improve understanding of how the degree of work engagement inf luences expertise, which requires

steady, consistent progress over an extended period of time.

Through applica tion of expertise theory to classical engineering management problem s , great strides may be possible in employee and organizational performance. Th ese insights will help managers:

8

Improve long term value creation potential of existing employees by enabling organizations to tailor professional development initiatives to fos ter traits which support development of occupational expertise

Help organizations maximize human capital by identifying and mitigating traits which are not associated with development of occupational expertise.

Assist organizations in preserving

competiti ve advantage by recognizing emerging and established expertise within the firm

D.

Summary

The body of exper tise research strongly suggest s that the level of skill, ability, and knowledge is determined by purposeful engagement rather than fixed genetic qualities.

This research will establish an incremental step towards enabling organizations to proactively manage potential, developing, and existing expertise within the organization

by build ing

insight needed to take advantage of training methods focused on expertise development . Professional development approaches focused on expanding expertise potentially offer widespread expansion of core competencies for organizations operating in interdisciplinary technical domai ns.

The subject of this research

is to investigate factors that may influence the direction and focus of organizational professional development ef forts .

The research will contribute to an improved understanding of how and why individual expe rtise develops within an organization by analyzing various factors and how these factors, singularly or in combination, influence the development of expertise or core competencies.

Likewise,

9

this research will contribute to an improved understanding of the potential outcomes of c hoosing a particular approach to professional development.

10

CHAPTER II

LITERATURE REVIEW

A.

Introduction

An extensive literature search was conducted to examine the body of research related to the Expertise and Expert Performance Framework.

This rese arch shows that over an extend ed period individuals develop and

refine domain - specific cognitive structures or processes which enable consistently and reproducibly superior performance

(Ericsson 2004) .

Research has shown that while specific activities and

experiences vary across domains, individuals who

have achieved experti se have employed a common approach which

foster s

growth and aid s development (Ericsson, Krampe, and Tesch - Romer 1993; Ericsson 1994).

The Expertise and Expert Performance Framework def ines the structure and acquisition of expert performance, identifying the habits and development al

patterns that enable expert performance

(Ericsson, Charness, Feltovitch, and Hoffman 2006) .

In the field of engineering, managers are primarily interested i n the development of knowledge workers.

Therefore, while these developmental patterns produce both

Full document contains 253 pages
Abstract: One of the roles of an engineering manager is to manage and develop expertise within the workforce. To this end, effective knowledge worker management requires insight into psychology and how it relates to the development of expertise. Modern psychology theory identifies three modes of mental function: cognition, affect, and conation. This research examines the role of affect and conation in the development of expertise. Expert theorists have assembled a strong body of evidence which suggests that superior achievement depends on adaptation resulting from sustained purposeful engagement. A substantial amount of research is devoted to the role of cognition in enabling expert performance. However, conation and affect are also hypothesized to be influential factors, as they determine the motivation and approach of the individual towards continuous development. A survey instrument was compiled, consisting of a set of conative and affective traits hypothesized to influence expertise development and a construct representing expertise. The survey was distributed within a large, federally-funded research and development laboratory which operates in the aviation and aerospace industry, producing a total of 541 responses. The structural equation modeling (SEM) statistical method was utilized to model and analyze the relationship between conative and affective traits and the development of occupational expertise. The findings of this research support the hypothesis that conative and affective traits are influential during expertise development. The dissertation results indicate that positive achievement orientation holds a strong, positive influence on expertise development. The mastery goal type coupled with the approach goal posture is the only goal orientation which positively influences expertise development. Work engagement holds a positive influence on expertise development. Expertise theorists hypothesize that expert-level technical performance is achievable for any individual with normal cognitive ability. Unfortunately, the reality is that only a small segment of knowledge workers currently approach this performance threshold. If engineering managers can access even a fraction of the remaining untapped potential, the implications for society are tremendous. By understanding the role of conative and affective traits in expertise development, managers can enhance professional development infrastructure and training methods in order to better support expertise development.