Computer Anxiety, Communication Preferences, & Personality Type in the North Carolina Cooperative Extension Service

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ABSTRACT

Emmons, Bruce Allen. Computer Anxiety, Communication Preferences, & Personality Type in the North Carolina Cooperative Extension Service. (Under the direction of Dr. R. David Mustian and Dr. Richard T. Liles.)

The purpose of this exploratory study was an examination of the personal attributes and other factors that may contribute to computer anxiety, thoughts about computers, and the expression of communication preferences of the personnel of North Carolina Cooperative Extension. Specifically, this study investigated the relationship of personal attributes, such as gender, age, level of formal education, work experience (tenure), ethnic background, and personality type; other factors, such as job responsibility; degree of computer experience, amount of time spent using the computer to computer anxiety, computer thoughts and communication preferences by county-based personnel of North Carolina Cooperative Extension.

The specific questions guiding this study were derived from a study of computer anxiety and communications. The following questions guided this investigation: Does a relationship exist between computer anxiety and communication preferences? Does a relationship exist between computer anxiety and personality type, gender, age, level of formal education, work experience, ethnic background, degree of computer experience, amount of time spent using a computer, job responsibility?

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staff of the North Carolina Cooperative Extension Service. Eleven hundred and twenty-six (1126) surveys were distributed. Nine hundred thirty-nine (939) instruments were returned, representing a response rate of eighty-three point four (83.4%) percent; six participants returned incomplete instruments which could not be used in this study.

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Computer Anxiety, Communication Preferences, & Personality Type in the North Carolina Cooperative Extension Service

by

BRUCE ALLEN EMMONS

A dissertation submitted to the Graduate Faculty of North Carolina State University

In partial fulfillment of the Requirements for the Degree

of Doctor of Education

DEPARTMENT OF ADULT AND COMMUNITY COLLEGE EDUCATION Raleigh

2003

APPROVED BY:

______________________________ ________________________________ Dr. R. David Mustian, Co-chair Dr. Richard T. Liles, Co-chair

of Advisory Committee of Advisory Committee

______________________________ _____________________________

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DEDICATION

This dissertation is respectfully dedicated to the people that had the most to do with its completion. To my family:

To my wife, Frances and my son, Nathan who endured countless hours without me. Hours that would have frequently been quality family time that can never be regained. To my parents, Cecil Hall Emmons and Eunice Christine Francis Emmons Goodrich, who established a love of reading and an expectation of education.

To my paternal grandparents, Jesse Emmons, a teacher who aided a respect for education even though he died three years before my birth and Allic Merilda “Rilda” Hall Emmons McAnespie, an adventurer and antique dealer who inspired a love of travel and things that are old.

To my paternal aunt, Helen Emmons Doyle, another adventurer and antique collector who fed the love of travel and old things. An attorney when few women were. Her gifts at Christmas and birthdays helped make undergraduate school possible.

To my maternal grandparents, Robert Lee Francis and Effie Irene Cole Francis, a farm couple that inspired a love of animals, agriculture and a respect for education. They opened their home and hearts to a “city” boy and gave him a chance to grow up just a little bit “country”.

To my maternal aunts, uncles, and cousins, businessmen and women, educators, doctors, contractors, civil servants, all of whom gave definition to the phrase, “family”. They inspired a love of learning and a sense of belonging and satisfaction in being a part of a wonderful group.

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BIOGRAPHY

Bruce Allen Emmons was born on July 8, 1949, in Memphis, Tennessee, the second and youngest son of the late Cecil Hall Emmons and Eunice “Christine” Francis Emmons Goodrich. He attended Mallory Heights Elementary, Longview Junior High School and Southside High School, graduating in 1967. In 1971, he received a Bachelor of Science in Agriculture with a major in Animal Husbandry and a minor in pre-veterinary medicine from the University of Tennessee at Knoxville. He worked two years in

contractor sales for Owen Lumber and Millwork in Memphis. He worked for John Morrell Meatpackers in Memphis for five years, buying over 250,000 hogs on the hoof and grading over a million carcasses on the rail, as well as working in quality control for two years.

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Bruce has received several honors including: Honorary State FFA Degree, The North Carolina Future Farmers of America Association, 2001; Professional Improvement Scholarship, Xi Chapter of Epsilon Sigma Phi, 1995; Distinguished Service Award, National Association of County Agricultural Agents, 1994; Distinguished Service Award, North Carolina Association of County Agricultural Agents, 1994; the Chester D. Black Professional Improvement Scholarship from the North Carolina Association of Extension 4-H Agents, 1993: elected District Vice-Director and District Director of the North Carolina Association of County Agricultural Agents, voting delegate to National Meeting, 1987; Extension Executive Development Institute, 1990; received the Ray H. Woodard Scholarship for Extension agents with swine responsibilities, 1983; elected District Vice-Director and District Director of the North Carolina Association of Extension 4-H Agents, voting delegate to National Meeting, 1980.

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ACKNOWLEDGMENTS

Many people have contributed to this voyage of discovery. My family as

mentioned in the dedication. My first County Extension Director, Mrs. Frances S. Voliva, the first woman extension director in the state of North Carolina, who signed me up for my first graduate course and then told me about it. “Miz Frances” always supported my involvement in graduate study and encouraged me in every way. My coworkers over the years that have covered the gaps while I was involved in class and/or travel time

associated with classes.

Thanks to Dr. Edgar Boone and Dr. Richard Liles, who planted the seeds of a doctorate at the Extension Executive Development Institute of 1990. A further thanks to Dr. Richard Liles for serving as co-chair of my committee along with Dr. R. David Mustian. Dr. Liles and Dr. Mustian served as rudders, pilots, and captains of my ship of Graduate Study. Dr. Mustian charted the course through many shoals of statistics and crossing the t’s and dotting the i’s of the manuscript. Thanks to Dr. Ken Esbenshade, who remembered from whence he came and served on my doctoral committee as he had chaired my Masters’ committee, even though his professional duties had greatly expanded. Thanks to Dr. Judy Groff, who always had insightful comments and a voice of cheer and encouragement when I needed it most.

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Dr. Kevin Gamble, Dr. Ron Heiniger, Ray Kimsey, and Rhonda Conlon.

John Dorner aided access to the Extension Personnel Database to secure the names and locations for distribution of the surveys. Carolyn Langley, Benjie Forrest and Shelia Ange provided much needed proofreading of many parts of the manuscript.

I would like to express appreciation to my coworkers at the Vernon G. James Research & Extension Center for their encouragement and tolerance of this endeavor. Thanks to Dr. Ron Heiniger and Dr. Richard Lichtenwalner for providing sounding boards and advice on statistical procedures. Their areas of study were Crop and Animal Science, but each had contributions to share that made this study possible.

Appreciation also goes to Dr. Jon Ort, Associate Dean & Director of North Carolina Cooperative Extension, North Carolina State University; Dr. M. Ray McKinnie, Administrator & Associate Dean, North Carolina Cooperative Extension, North Carolina A & T State University; Dr. Joe Zublena, Associate Director & Director of County Operations, North Carolina Cooperative Extension Service for their support in participating in this research study. In addition, appreciation goes to the district and county directors for their assistance in supporting this study. Thanks to my extension coworkers that completed the survey. They were essential to this study.

A special thanks to Dr. Larry D. Rosen and Dr. Henry Thompson for allowing the use of their instruments in this study. Dr. Rosen and his coworkers developed the

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Table of Contents

List of Figures . . . ix

List of Tables . . . xi

Chapter 1 . . . Introduction The Cooperative Extension System . . . 1

Computer Anxiety . . . 2

Communication and Communication Preferences . . . 4

Objectives and Purposes of this Research Study . . . 5

Significance of this Study . . . 10

Limitations of this Study . . . 10

Definition of Terms . . . 11

Chapter 2 Conceptual Framework . . . 12

Review of the Literature . . . 14

Computer Anxiety . . . 14

Computer Anxiety Measures . . . 35

Computer Anxiety and Personality Type . . . 47

Communication . . . 52

Communication and Personality Type . . . 58

Communication Preference Questionnaire (CPQ®) . . . 62

The Myers-Briggs Personality Type Indicator . . . 63

Research Questions . . . 93

Hypotheses . . . 97

Chapter 3 . . . Methodology Research Design . . . 102

Population and Sample . . . 102

Instrumentation . . . 103

Reliability and Validity . . . 106

Data Collection . . . 108

Data Analysis . . . 110

Chapter 4 Findings (Analysis and Evaluation) . . . 111

Profile of Respondents . . . 112

Dependent Variables . . . 114

Hypotheses Testing . . . 115

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Table of Contents, (continued)

Chapter 5 . . . Summary, Conclusions, and Recommendations

Summary . . . 175

Conclusions . . . 176

General Implications . . . 210

Recommendations for Further Study . . . 213

References . . . 214

Appendices . . . 222

Cover Letter . . . 223

Demographics Survey . . . 224

Computer Anxiety Rating Scale . . . 226

Computer Thoughts Survey . . . 227

Permission to use CARS and CTS . . . 228

Technology Anxiety Rating Scale . . . 229

Permission to develop TARS based on CARS . . . 230

Communication Preferences Questionnaire . . . 231

Permission to use CPQ® . . . 232

Permission to Use MBTI type . . . 233

Tables . . . 234

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List of Figures Literature Review

Factors Influencing Attitudes Towards Computers . . . 28

Chapter Four-Findings CARS and Age . . . 117

CARS and Years Using A Computer . . . 119

CARS and Computer Use . . . 121

CTS and Age . . . 123

CTS and Years Using A Computer . . . 125

CTS and Job Responsibility . . . 126

CTS and Computer Use . . . 127

CPQ® Primary and E or I . . . 129

CPQ® Dialects and E or I . . . 130

CPQ® Primary and S or N . . . 131

CPQ® Secondary and S© or N . . . 132

CPQ® Dialects and S or N . . . 133

CPQ® Primary and T or F . . . 134

CPQ® Dialects and T or F . . . 135

CPQ® Primary and J or P . . . 136

CPQ® Dialects and J or P . . . 137

CPQ® Primary and Temperament . . . 138

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List of Figures (continued)

CPQ® Dialects and Temperament . . . 140

CPQ® Secondary and Gender . . . 142

CPQ® Primary and Age . . . 143

CPQ® Dialects and Age . . . 144

CPQ® Secondary and Educational Level . . . 146

CPQ® Primary and Years in . . . 147

CPQ® Dialects and Years in NCCES . . . 148

CPQ® Primary and Ethnic Background . . . 149

CPQ® Secondary and Ethnic Background . . . 150

CPQ® Dialects and Ethnic Background . . . 151

CPQ® Secondary and Job Responsibility . . . 154

TARS and CARS . . . 156

TARS and CTS . . . 157

TARS and Gender . . . 159

TARS and Age . . . 160

TARS and Educational Level . . . 161

TARS and Years Using A Computer . . . 164

TARS and Job Responsibility . . . 165

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List of Tables

Literature Review Page

Table 2.1 COMPAS Scores for Extension Agents . . . 31

Table 2.2 COMPAS Scores for Virginia Cooperative Extension Personnel . . . 32

Table 2.3 Communication Style Preferences of the 16 Psychological Types . . . 60

Table 2.4 Overview of the Four Preferences (MBTI)® . . . 67

Table 2.5 Choices of the four preferences (MBTI)® . . . 71

Table 2.6 Item-test correlations for Form F and Form G (MBTI)® . . . 75

Table 2.7 Correlation Matrix of the Six Measures of Overall Marital Difficulty . . . 82

Table 2.8: Results of Studies Reflecting the Percentage of Couples Having Varying Numbers of Common MBTI® Preferences . . . 83

Table 2.9: Internal consistency derived from product-moment correlations of X and Y continuous scores with Spearman-Brown prophecy formula correction . . . 87

Table 2.10: Percent of Test-Retest Agreement in Each Category Control Group . . . 88

Appendices Table 4.1 Distribution of Respondents by Socio-demographic Factors (Gender, Age, Level of Formal Education) . . . 234

Table 4.2 Distribution of Respondents by Socio-demographic Factors (Ethnic Background, Area of Job Responsibility) . . . 235

Table 4.3 Distribution of Respondents by Socio-demographic Factors (Tenure & Computer Experience) . . . 236

Table 4.4 Distribution of Respondents by Computer Use . . . 237

Table 4.5 Distribution of Respondents by Temperament as derived by MBTI® . . . 238

Table 4.6 Distribution of Respondents by Psychological Personality Preferences . . . 239

Table 4.7 Distribution of Respondents by Psychological Personality . . . 240

Table 4.8 Distribution of Respondents by Communication Preference (Primary Language) . . . 241

Table 4.9 Distribution of Respondents by Communication Preference (Secondary Language) . . . 241

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List of Tables (continued)

Table 4.11a Distribution of Respondents' Overall Computer Anxiety

(CARS) scores by Overall Communication Preferences

(CPQ®) primary language scores . . . 243 Table 4.11b Distribution of Respondents' Overall Computer Anxiety

(CARS) scores by Overall Communication Preferences

(CPQ®) secondary language scores . . . 243 Table 4.11c Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Overall Communication Preferences (CPQ®) dialect language scores . . . 244 Table 4.12a Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Overall Myers-Briggs Type Indicator (MBTI®)

psychological personality preferences . . . 245 Table 4.12b Distribution of Respondents' Overall Computer Anxiety

(CARS) scores by Myers-Briggs Type Indicator (MBTI®) psychological personality preferences,

(E) Extraversion vs. (I) Introversion . . . 246 Table 4.12c Distribution of Respondents' Overall Computer Anxiety

(S)Sensing Perception vs. (N)iNtuitive Perception . . . 246 Table 4.12d Distribution of Respondents' Overall Computer Anxiety

(T)Thinking Judgement vs. (F)Feeling Judgement . . . 247 Table 4.12e Distribution of Respondents' Overall Computer Anxiety

(J)Judgement vs. (P)Perception . . . 247 Table 4.12f Distribution of Respondents' Overall Computer Anxiety

Temperament . . . 248 Table 4.13 Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Gender . . . 248 Table 4.14 Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Age . . . 249 Table 4.15 Distribution of Respondents' Overall Computer Anxiety (CARS)

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Table 4.17 Distribution of Respondents' Overall Computer Anxiety (CARS) scores by Years in NCCES . . . 250 Table 4.18 Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Ethnic Background . . . 251 Table 4.19 Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Years Using A Computer . . . 251 Table 4.20 Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Job Responsibility . . . 252 Table 4.21 Distribution of Respondents' Overall Computer Anxiety (CARS)

scores by Computer Use on a TYPICAL Day . . . 252 Table 4.22a Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Overall Communication Preferences (CPQ®) primary language scores . . . 253 Table 4.22b Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Overall Communication Preferences (CPQ®) secondary language scores . . . 253 Table 4.22c Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Overall Communication Preferences (CPQ®) dialect language scores . . . 254 Table 4.23a Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Overall Myers-Briggs Type Indicator (MBTI®) psychological personality preferences . . . 255 Table 4.23b Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Myers-Briggs Type Indicator (MBTI®) psychological personality preferences,

(E) Extraversion vs. (I) Introversion . . . 256 Table 4.23c Distribution of Respondents' Overall Computer Thoughts Survey

(S)Sensing Perception vs. (N)iNtuitive Perception . . . . 256 Table 4.23d Distribution of Respondents' Overall Computer Thoughts Survey

(T)Thinking Judgement vs. (F)Feeling Judgement . . . . 257 Table 4.23e Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores BY Myers-Briggs Type Indicator (MBTI®) psychological personality preferences,

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Table 4.23f Distribution of Respondents' Overall Computer Thoughts Survey (CTS) scores by Myers-Briggs Type Indicator

(MBTI®) psychological personality preferences,

Temperament . . . 258 Table 4.24 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Gender . . . 258 Table 4.25 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Age . . . 259 Table 4.26 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Educational Level . . . 259 Table 4.27 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Years in Current Position . . . 260 Table 4.28 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Years in NCCES . . . 260 Table 4.29 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Ethnic Background . . . 261 Table 4.30 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Years Using A Computer . . . 261 Table 4.31 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by area of Job Responsibility . . . 262 Table 4.32 Distribution of Respondents' Overall Computer Thoughts Survey

(CTS) scores by Computer Use on a TYPICAL Day . . 262 Table 4.33a Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by MBTI© score . . . 263 Table 4.33b Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by E or I type . . . 264 Table 4.33c Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by S or N type . . . 264 Table 4.33d Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by T or F type . . . 265 Table 4.33e Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by J or P type . . . 265 Table 4.33f Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Myers-Briggs Type Indicator (MBTI®)

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Table 4.34 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Gender . . . 266 Table 4.35 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Age . . . 267 Table 4.36 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Educational Level . . . 267 Table 4.37 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Years in Current Position . . . 268 Table 4.38 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Years in NCCES . . . 268 Table 4.39 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Ethnic Background . . . 269 Table 4.40 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Years Using A Computer . . . 269 Table 4.41 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Job Responsibility . . . 270 Table 4.42 Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Primary Language by Computer Use on a TYPICAL Day . . . 270 Table 4.43a Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Secondary Language by MBTI® score . . . 271 Table 4.43b Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Secondary Language by E or I type . . . 272 Table 4.43c Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Secondary Language by S or N type . . . 272 Table 4.43d Distribution of Respondents' Overall Communication

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Table 4.43e Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Secondary Language

by J or P type . . . 273 Table 4.43f Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Secondary Language by Myers-Briggs Type Indicator (MBTI©)

psychological personality preferences,

Temperament . . . 274 Table 4.44 Distribution of Respondents' Overall Communication

by Gender . . . 274 Table 4.45 Distribution of Respondents' Overall Communication

by Age . . . 275 Table 4.46 Distribution of Respondents' Overall Communication

by Educational Level . . . 275 Table 4.47 Distribution of Respondents' Overall Communication

by Years in Current Position . . . 276 Table 4.48 Distribution of Respondents' Overall Communication

by Years in NCCES . . . 276 Table 4.49 Distribution of Respondents' Overall Communication

by Ethnic Background . . . 277 Table 4.50 Distribution of Respondents' Overall Communication

by Years Using A Computer . . . 277 Table 4.51 Distribution of Respondents' Overall Communication

by Job Responsibility . . . 278 Table 4.52 Distribution of Respondents' Overall Communication

by Computer Use on a TYPICAL Day . . . 278 Table 4.53a Distribution of Respondents' Overall Communication

Preference Questionnaire (CPQ®) Dialects

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Table 4.53b Distribution of Respondents' Myers-Briggs Type Indicator (MBTI®) psychological personality preferences, (E) Extraversion vs. (I) Introversion

by Overall Communication Preferences (CPQ®)

Dialect Language scores . . . 281 Table 4.53c Distribution of Respondents' Myers-Briggs Type Indicator

(MBTI®) psychological personality preferences, (S) Sensing Perception vs. (N) iNtuitive Perception by Overall Communication Preferences (CPQ®)

Dialect Language score . . . 282 Table 4.53d Distribution of Respondents' Myers-Briggs Type Indicator

(T) Thinking Judgement vs. (F) Feeling . . . 283 Table 4.53e Distribution of Respondents' Overall Communication

Preferences (CPQ®) dialect language scores by Myers-Briggs Type Indicator (MBTI®) psychological personality preferences,

(J) Judgement vs. (P) Perception . . . 284 Table 4.53f Distribution of Respondents' Overall Communication

Preferences (CPQ®) Dialect Language scores by Myers-Briggs Type Indicator (MBTI®) psychological personality preferences,

Temperament . . . 285 Table 4.54 Distribution of Respondents' Gender by Overall

Communication Preferences (CPQ®)

Dialect Language scores . . . 286 Table 4.55 Distribution of Respondents' Overall Communication

Preferences (CPQ®) dialect language scores

by Age . . . 287 Table 4.56 Distribution of Respondents' Educational Level by

Overall Communication Preferences (CPQ®)

Dialect Language score . . . 288 Table 4.57 Distribution of Respondents' Years in Current Position

Dialect Language score . . . 289 Table 4.58 Distribution of Respondents' Years in NCCES

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Table 4.59 Distribution of Respondents' Ethnic Background

Dialect Language scores . . . 291 Table 4.60 Distribution of Respondents' Years Using A Computer

(Computer Experience) by Overall Communication Preferences (CPQ®)

Dialect Language scores . . . 292 Table 4.61 Distribution of Respondents' Job Responsibility

Dialect Language scores . . . 293 Table 4.62 Distribution of Respondents' Computer Use on a TYPICAL Day

Dialect Language scores . . . 295 Table 4.63 Distribution of Respondents' Overall Technology Anxiety

(TARS) scores by Overall Computer Anxiety Rating Scale

(CARS) scores . . . 297 Table 4.64 Distribution of Respondents' Overall Technology Anxiety Rating

Scale (TARS) scores by Overall Computer

Thoughts Survey (CTS) scores . . . 297 Table 4.65 Distribution of Respondents' Overall Computer Anxiety Rating Scale

(CARS) scores by Overall Computer Thoughts Survey

(CTS) scores . . . 298 Table 4.66a Distribution of Respondents' Overall Technology Anxiety Rating

Scale (TARS) scores by Overall Communication Preferences

(CPQ®) Primary Language scores . . . 298 Table 4.66b Distribution of Respondents' Overall Technology Anxiety Rating

Scale (TARS) scores by Overall Communication Preferences (CPQ®) Secondary Language scores . . . 299 Table 4.66c Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Overall Communication Preferences

(CPQ®) Dialect Language scores . . . 300 Table 4.67a Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Overall Myers-Briggs Type Indicator

(MBTI®) psychological personality preferences . . . 301 Table 4.67b Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Myers-Briggs Type Indicator (MBTI®) psychological personaity preferences,

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Table 4.67c Distribution of Respondents' Overall Technology Anxiety Rating Scale (TARS) scores by Myers-Briggs Type Indicator

(S)Sensing Perception vs. (N)iNtuitive Perception . . . 302 Table 4.67d Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Myers-Briggs Type Indicator (MBTI®) psychological personality preferences,

(T) Thinking Judgement vs. (F) Feeling Judgement . . . 303 Table 4.67e Distribution of Respondents' Overall Technology Anxiety Rating Scale

(J)Judgement vs. (P)Perception . . . 303 Table 4.67f Distribution of Respondents' Overall Technology Anxiety Rating Scale

Temperament . . . 304 Table 4.68 Distribution of Respondents' Overall Technology Anxiety Rating

Scale (TARS) scores by Gender . . . 304 Table 4.69 Distribution of Respondents' Overall Technology Anxiety Rating

Scale (TARS) scores by Age . . . 305 Table 4.70 Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Educational Level . . . 305 Table 4.71 Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Years in Current Position . . . 306 Table 4.72 Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Years in NCCES . . . 306 Table 4.73 Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Ethnic Background . . . 307 Table 4.74 Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Years Using A Computer . . . 307 Table 4.75 Distribution of Respondents' Overall Technology Anxiety Rating Scale

(TARS) scores by Job Responsibility . . . 308 Table 4.76 Distribution of Respondents' Overall Technology Anxiety Rating Scale

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Table 4.78 Summary of Forty-one Hypotheses . . . 170 Table 4.79 Summary of Twenty-two Rejected Null Hypotheses . . . 172 *********************************************************************** Chapter Five

Table 5.1 Summary of Conclusions . . . 177 Table 5.2 Computer Anxiety and Computer Experience (both Years Using

A Computer and Hours Using A Computer on a TYPICAL

Day) . . . 191 Table 5.3 Communication Preference Questionnaire (CPQ®) scores and

the Myers-Briggs Type Indicator (MBTI®) . . . 196 Table 5.4 Communication Preference Questionnaire (CPQ®) scores and

Selected Variables . . . 202 Table 5.5 Communication Preference Questionnaire (CPQ®) scores and

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Chapter One - Introduction

The Cooperative Extension System

Rogers (1995) refers to the agricultural extension system as, "... the government agency that has been by far the most successful in securing users' adoption of its research results...". He describes the three components of the system as: a research component, consisting of professors of agriculture supported by the fifty state agricultural experiment stations and the United States Department of Agriculture; county extension agents, working as change agents with clientele at the local level; and state extension specialists who link agricultural researchers to the county agents

(p. 157).

The component established first was the agricultural university teaching

component by the Morrill Act of 1862. The Morrill Act established land-grant universities with one in each state. These institutions usually had the phrase, "of agricultural and mechanical arts" in their title, such as the Iowa State College of Agriculture and

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subjects relating to agriculture and home economics, and to encourage application of the same" (p. 158). The agricultural extension service has a long history as one of the oldest and most successful diffusion systems in the United States. The budget for the extension services comes from federal, state, and county governments. The term, "Cooperative Extension Service" indicates the collaboration of these three levels of government and is frequently the title of the organization, such as, North Carolina Cooperative Extension (p. 159).

Computer Anxiety

Rosen and Weil (1990) observe that the spread of computers on the university campus is generally viewed as a positive sign that American education is keeping pace with the "emerging technological revolution". However, they note there is a segment of the population that is being left out of the revolution. They describe several labels for these people, including, but not limited to, cyberphobes, technophobes, or more

commonly, computerphobics. How much of a problem is this computer anxiety? They report that a 1993 national poll by the Dell Computer corporation found that 55% of the American public feel technophobic (Weil & Rosen, 1997, p. 3).

A study of southern region cooperative extension agents estimates computer anxiety levels of 55% (Smith & Kotrlik, 1990). Using a computer anxiety scale developed by Oetting in 1983, Smith and Kotrlik found that a representative sample of 522 agents in eleven of the thirteen southern region states (North Carolina and Kentucky did not

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Martin, Stewart, and Hillison (2001) report that in Martin's doctoral research of 1997, a modified version of the Oetting computer anxiety scale was used. In her research, Martin found that more than 44% of Virginia Cooperative Extension personnel responding felt very anxious, anxious/tense, or mildly anxious. In the Journal of

Extension article, the authors summarized the research as follows:

This study found that, of the Virginia Cooperative Extension personnel, secretaries had the lowest anxiety level, with only 10.8% total for the anxious and very anxious categories. On the other hand, technicians had the highest anxiety levels, with 33.4% total in the same two categories. The personnel in the over 40 age group

expressed the highest anxiety levels. The 40- to 49-year-old subjects had 22.4% total for the anxious and very anxious categories; the 50- to 59-year-old subjects had 26.8% in the same categories; while 30- to 39-year-old subjects had only 9.9%.

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communications and information retrieval combined with Extension's reputation as a long-time, unbiased source of useful information could make the coming years some of

Extension's best.

"By becoming more advanced in information communications, we can be an educational force in the 21st century".

Communication and Communication Preferences

Thompson (2000) defines communication as "...a dynamic process of listening, processing, and expressing information and meaning". King and Rockwell (1998) report that information can be so complex or chaotic that individuals can give up, become fatigued, or be simply overloaded. Information must be designed to be received so that clients can understand the meaning and be able to apply it to their situations.

By becoming more knowledgeable about how individuals prefer to transmit and receive information, extensionists can be better providers of information for their clientele. The Communication Preference Questionnaire® developed by Thompson (2001), is a quick and powerful self assessment tool to determine the preferred communication language and dialect that a person prefers when conversing with another person.

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Computer anxiety can isolate individuals within an organization that depends on E-mail communications. Ezell (1989) notes that computer, media, and communications are all converging. Communication networks are spreading concepts and ideas around the globe with astonishing speed. She states that the new information technologies are adding value to information by storing, processing, converting, and transporting it in an accessible and easy-to-use format. It will provide this information at a lower cost with wider reach, greater convenience, and with richer content. All of this interaction flows through a common vessel, the computer. Without this access, individuals will be sorely restricted in reaping the benefits of this communications age. Computer anxiety can be a major roadblock in that access.

Objectives and Purposes of this Research Study

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1. What relationship exists between computer anxiety and communication preferences of North Carolina Cooperative Extension personnel?

2. What relationship exists between computer anxiety and personality type of North Carolina Cooperative Extension personnel?

3. What relationship exists between computer anxiety and gender of North Carolina Cooperative Extension personnel?

4. What relationship exists between computer anxiety and age of North Carolina Cooperative Extension personnel?

5. What relationship exists between computer anxiety and level of formal education of North Carolina Cooperative Extension personnel?

6. What relationship exists between computer anxiety and work experience (tenure) of North Carolina Cooperative Extension personnel?

7. What relationship exists between computer anxiety and ethnic background of North Carolina Cooperative Extension personnel?

8. What relationship exists between computer anxiety and degree of computer experience of North Carolina Cooperative Extension personnel?

9. What relationship exists between computer anxiety and area of job responsibility of North Carolina Cooperative Extension personnel?

10. What relationship exists between computer anxiety and amount of time spent using the computer of North Carolina Cooperative Extension personnel?

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12. What relationship exists between computer thoughts and personality type of North Carolina Cooperative Extension personnel?

13. What relationship exists between computer thoughts and gender of North Carolina Cooperative Extension personnel?

14. What relationship exists between computer thoughts and age of North Carolina Cooperative Extension personnel?

15. What relationship exists between computer thoughts and level of formal education of North Carolina Cooperative Extension personnel?

16. What relationship exists between computer thoughts and work experience (tenure) of North Carolina Cooperative Extension personnel?

17. What relationship exists between computer thoughts and ethnic background of North Carolina Cooperative Extension personnel?

18. What relationship exists between computer thoughts and degree of computer experience of North Carolina Cooperative Extension personnel?

19. What relationship exists between computer thoughts and area of job responsibility of North Carolina Cooperative Extension personnel?

20. What relationship exists between computer thoughts and the amount of time spent using the computer of North Carolina Cooperative Extension personnel?

21. What relationship exists between communication preference and personality type of North Carolina Cooperative Extension personnel?

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23. What relationship exists between communication preference and age of North Carolina Cooperative Extension personnel?

24. What relationship exists between communication preference and level of formal education of North Carolina Cooperative Extension personnel?

25. What relationship exists between communication preference and work experience (tenure) of North Carolina Cooperative Extension personnel?

26. What relationship exists between communication preference and ethnic background of North Carolina Cooperative Extension personnel?

27. What relationship exists between communication preference and degree of computer experience of North Carolina Cooperative Extension personnel?

28. What relationship exists between communication preference and area of job responsibility of North Carolina Cooperative Extension personnel?

29. What relationship exists between communication preference and amount of time spent using the computer of North Carolina Cooperative Extension personnel?

30. What relationship exists between technology anxiety and computer anxiety of North Carolina Cooperative Extension personnel?

31. What relationship exists between technology anxiety and computer thoughts of North Carolina Cooperative Extension personnel?

32. What relationship exists between technology anxiety and communication preferences of North Carolina Cooperative Extension personnel?

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34. What relationship exists between technology anxiety and gender of North Carolina Cooperative Extension personnel?

35. What relationship exists between technology anxiety and age of North Carolina Cooperative Extension personnel?

36. What relationship exists between technology anxiety and level of formal education of North Carolina Cooperative Extension personnel?

37. What relationship exists between technology anxiety and work experience (tenure) of North Carolina Cooperative Extension personnel?

38. What relationship exists between technology anxiety and ethnic background of North Carolina Cooperative Extension personnel?

39. What relationship exists between technology anxiety and degree of computer experience of North Carolina Cooperative Extension personnel?

40. What relationship exists between technology anxiety and area of job responsibility of North Carolina Cooperative Extension personnel?

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Significance of this Study

Rosen and Weil (1990), Smith and Kotrlik (1990); and Martin (1998) have all identified computer anxiety as a major obstacle to participation in careers involving the "technological revolution". Finding an occupation that is immune from the advances of technology would be a difficult task. Rosen and Weil estimate more than 33% of university students suffer from this anxiety. Smith and Kotrlik place an estimate of 55% of cooperative extension agents in the southern region have some degree of computer anxiety (excluding Kentucky and North Carolina). Martin found that more than 44% of Virginia Cooperative Extension personnel (including agents, secretaries, and support staff) demonstrate feelings of computer anxiety.

This study will examine the degree of computer anxiety present among county-based extension personnel in North Carolina. It will also examine the possibility of relationships between computer anxiety and computer thoughts, communication preferences, personality type, and demographic factors, such as age, gender, etc.. Limitations of this Study

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Definition of Terms

Communication - "a dynamic process of listening, processing and expressing information and meaning", (Thompson, 2000).

Communication preference - Each of the 16 psychological types has a unique pattern of primary, secondary, tertiary, and least preferred communication styles. The preferences are: (E/I) Extraversion/Introversion; (S/N) Sensing Perception/iNtuitive Perception; (T/F) Thinking Judgement/Feeling Judgement; and (J/P) Judgement/Perception. "All people use all four communication styles--sensing, intuition, thinking, and feeling--but not with equal preference, skill of effectiveness." (Yeakley, 1982, p. 30-31).

Computer anxiety - a.) resistance to talking or even thinking about computer technology; b.) fear or anxiety, which may even create physiological consequences;

c.) hostile or aggressive thoughts and acts, indicative of some underlying frustrations (Jay, 1981, p. 47).

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Chapter Two

Conceptual Framework

The computer revolution around the world has not been without its casualties. Rosen and Weil (1990), Jay (1981), Maurer (1994), Lawton and Gerschner (1982), Dupagne and Krendl (1992), Smith and Kotrlik (1990), Martin, Stewart, and Hillison (2001) and many others have documented the existence of computer anxiety. This anxiety has been found by researchers to effectively block many individuals from effectively interacting with computers and other new technologies that are taken for granted by the majority in today’s society. Access to these technologies is so important because, as Harriman and Daugherty (1992) state, “The computer has transformed education as radically as the printing process once did”.

The computer that is so prevasive in today’s society has not always been so accessible. Room-sized computers consisting of huge metal cabinets filled with heat producing vacuum tubes, whirring fans, and small keyboards used to be the domain of a few white-coated, often aloof, individuals that served as “gatekeepers”. These individuals would accept stacks of cardboard cards with laboriously punched holes and inform

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Estimates by noted experts vary from 25% to 50% or more of individual members of society that possess computer anxiety.

The factors that have been examined as possibly contributing to this computer anxiety have been many and varied. Age, gender, ethnic background, educational level, socio-economic standing, profession, and many other factors have been examined in relation to computer anxiety. For every factor and for both sides of every possible question about computer anxiety, at least some studies have been conducted.

Personality and the constructs that affect personality and the interaction of our daily lives have also been the subject of much study and investigation. Myers and

McCaulley (1985) state that the purpose of the Myers-Briggs Type Indicator was to make psychologist C.G. Jung’s theory of psychological types understandable and useful in the lives of people. They state, “Almost every human experience involves either perception or judgement and is played out in the world of action or ideas” (p.4).

Studies of relationships of the interaction of personality type and computer anxiety have found both no interaction and significant relationships between the study factors.

Computers have taken on the function of communication to a large part in today’s world. Communication preferences, how we desire to communicate verbally has been examined by numerous researchers. Yeakley (1982 and 1983) studied communication patterns and personality traits. Thompson (1998) developed the Communication Preference Questionnarie (CPQ®) and the Communication Wheel® to explain the relationships of personality type and preferences in verbal communication.

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related to computer anxiety. The variables will include demographic variables, such as gender, age, level of education, work experience (tenure), ethnic background, job responsibility, personality type, degree of computer experience, amount of time spent using the computer, and communication preferences. Investigated relationships will include the following general questions:

Does a relationship exist between computer anxiety and communication preferences?

Does a relationship exist between computer anxiety and personality type, gender, age, level of formal education, work experience, ethnic background, degree of computer experience, amount of time spent using a computer, job responsibility? Can an instrument developed by the author accurately reflect the level of a

person’s anxiety related to recent changes in technology, compared to instruments developed in the late 1980s?

Review of the Literature Computer Anxiety

Computer anxiety can be interpreted as resistance to change. Resistance as found by Jorde (1985, p. 13), "...is often a symptom of something else; fear of the unknown, fear of failure, or an unwillingness to alter the status quo". She further stated, "Any attempt to understand the nature of resistance to a technological innovation such as microcomputers cannot ignore the power of emotions in regulating behavior (p.7).

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innovation or new technology. Rybczynski (1985) reports several historical examples of difficulty in accepting innovation. One such example found that in 1139, Pope Innocent II thought the crossbow was so cruel that he banned its use against Christians, although the Moors - infidels, were still fair game. Later, in 1559, Queen Elizabeth I of England would not grant a royal patent for a knitting machine because it might force some of her subjects into unemployment (p. 10).

"Engels, and ... Marx... has the distinct impression that although the main villain is the middle class, much of the blame for the social and environmental effects of

industrialization falls on technology itself" (Rybczynski, 1985, p. 14). Rogers and Shoemaker (1971) report that even in 400 B.C., Sophocles advocated practical trials of innovation when he said, "One must learn by doing the thing, for though you think you know it - you have no certainty, until you try" (p. 98).

Frankel (1990) said, "Technology is as old as the human race, and is one of the developments which set humans apart from other beings" (p. 2). He also reports that human development is a progression of technological changes or discoveries and that "Civilization and technology are intimately interwoven" (p. xvii).

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stemmed from the development of one very simple tool. Those lacking the skills to utilize the new technology more than likely experienced an anxiety about their place in the changing society.

An examination of an innovation would reveal the following characteristics: relative advantage-the degree to which an innovation is better than that which it replaces; compatibility-the degree to which an innovation is consistent with values, experiences and needs of the receivers; complexity-the degree to which an innovation is thought to be difficult to understand and/or use; trialability- the degree to which an innovation can be tried out or experimented with on a limited basis; and observability-the degree to which others perceive the results of an innovation (Rogers and Shoemaker, 1971, p. 22).

According to Rogers and Shoemaker (1971), "The innovation-decision process is the mental process through which an individual passes from first knowledge of an

innovation to a decision to adopt or reject and to confirmation of this decision". This process contains four functions: 1.) knowledge - an individual learns of an innovation's existence and some understanding of it; 2.) persuasion - the innovation generates a favorable or unfavorable attitude; 3.) decision - a choice is made to accept or reject the innovation; and 4.) confirmation - reinforcement for the decision is sought by the individual, conflicting messages may generate a reversal of the decision (Rogers and Shoemaker, 1971, p. 101).

Individuals fit into one of five adopter categories according to Rogers and

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(p. 27) . They found these five categories to describe all adopters.

Rogers (1995) reports that the first adopters of home computers in the U. S. were hobbyists that simply loved technological gadgets. These individuals did not perceive computers to be complex because to them they were not. However, the majority of those purchasing home computers in the early 1980s faced a period of six to eight weeks of extreme frustration and anxiety. This perceived complexity was an important negative force in their rate of adoption in the early 1980s. Advances in making computers more user-friendly helped increase their acceptance to about 30 percent of households in the U.S. by 1994 (p. 243).

Herzberg (1987) discusses several characteristics of innovative people. He contends that innovators have an above average intelligence quotient, but very high IQs can be detrimental because they are too highly correlated to standard educational achievement. "It is the reinforcement of standard performance that inhibits seeking satisfaction outside the standards" (p. 182). He found that innovative people have a high level of subject matter expertise, but not that of an authority. Such a status inhibits new ideas through the "BIYOB (belief in your own bullshit) syndrome"

(p. 183).

Being unable to make it conventionally is highly correlated with innovation. Innovative people push the rules of the game while conventional people strive to break "existing records" (Herzberg, 1987, p. 184).

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bound to be ineffective when faced with the unknown". Further, innovative people have a well developed sense of self. Herzberg further stated, "The innovative person is not acting, he is being" (p. 185). The innovative person is not usually a careerist (a person that agrees with the boss to get ahead) but rather someone that prefers accomplishment (Herzberg, 1987, p. 187).

Herzberg (1987) recognizes three Mega-barriers to innovation and entrepreneurship: a shift away from quality production; membership in guilds

(professional societies) which become "a clique of gatekeepers of what is acceptable"; and the capture of knowledge by sacred institutions such as government, "capturing individual conscience and patriotism" (p. 191). Educationally, Hasselbring (1991) details three major barriers to successful computer technology in our schools: first, the installed technology base which schools have sought to match new equipment to the old to save on teacher training, along with the familiarity of students with the programs and existing software; second, software limited to 64 K memory and one disk drive that have prevented

development of more powerful programs that might be capable of following a student and his or her performance throughout school; and third, teacher training, since the "...vast majority of those now teaching or planning to teach have had little or no computer education or training..." (p. 35).

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monolithic; traditional academic values resist new concepts in curriculum, teaching styles, merit rewards, research priorities, and student-teacher relationships; no tested methods for measuring success (or failure) of innovations; little time for teachers to stay abreast of both subject matter and innovations in teaching methods; and "the single most devastating resistance to change in academic programs - organizational inertia"(Redmon, 1982, p. 19). Faculty resistance "...deserves consideration since policy has emerged in the departments of learning as a concept imbued with authority for regulating academic practices"

(Redmon, 1982, p. 20).

In regards to administrative resistance: confusion about control; no continued reappraisal of decision making styles; no support for human resource development; inadequate central structures for decision making; haphazard communication; few management tools for change; academic decisions follow simplistic models of policy execution; and unclear role definition in reorganizations "have left the institution in a listing position between the dock of conservative tradition and the rough seas of

innovation and economic scarcity". Most administrators have not been trained for their job responsibilities, especially in the academic affairs arena (Redmon, 1982, p. 20).

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resistance can be the greatest block for innovation.

Schieman and Fiordo (1990) presented the following at the Australian Communications Conference:

... a major obstacle to the introduction and dissemination of instruction and communication media in higher education is the inertia of the education system itself. There are few if any incentives for college professors to change their methods. The institutions themselves seem to be organized in such a way as to resist all change, not only those concerned with improving instruction. (p. 4)

They earlier stated, "Adoption of instructional communications technology meets with resistance and even opposition in higher education" (Schieman and Fiordo, 1990, p. 1).

Gayeski (1989) felt that "People generally don't resist technical change - most people probably care little about the techniques and tools of communication. They resist the social aspects of change - the change in their human relationships" (p. 12). Along the same vein, she reports that one of the most significant factors preventing the widespread use of computers in office information systems is a lack of knowledge at top management levels about what computers are and what they can do (p. 13).

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Masie and Wolman (1989) divulge that "...diverse reactions to learning about computers are actually caused by identifiable differences in the way people think and learn...". They also found that people sometimes are resistant to learning about new innovations because they think they will not succeed (p. 21).

The Organisation for Economic Co-operation and Development (1981) found innovation to be a two-edged sword:

Scientific research and technological innovation are basic determinants of economic and social change. They are factors of enhanced performance as well as of tremendous expansion of new products and material prosperity. At the same time, they are also causes of destabilization. They make obsolete whole categories of knowledge, techniques and professional skills. They call into being new risks and challenges (p. 7).

Preparing for such changes is the responsibility of each professional, according to Rieber and Welliver (1992). They maintain that every professional must be willing to become a student and learn new techniques and information in order to serve our clients. "Not only is it the professional thing to do; it is a matter of ethics" (p. 40). In an

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Hurly and Hlynka (1982) describe computers as an instructional technology just like any other tool and dependent on the skills, values, objectives, goals and creativity of the person using that tool. When failure occurs, the failure is that of those initiating the innovation to support the user in acquisition of the necessary attitudes, skills and behaviors to be successful with the new technology (p. 5). One method for enhancing this

acquisition is to provide the teachers with advancement opportunities; increased authority; release time to learn the technologies; study leave; and special assignments, in addition to more money (p.4).

Like Redmon and also Herzberg, Hurly and Hlynka found a desire to protect the status quo strongly exists in educational entities. "The educational institution is depicted as a 'traditional' organization which is extremely conservative and which divests large

amounts of autonomy in the individual. In universities this status quo is maintained by the oldest guild system still in existence" (p. 7).

Bresler and Walker (1990) found that, "...people and the institutions they create and sustain...determine the success or failure of an innovation...it may still not succeed unless it fits the patterns by which they run their lives as students and teachers" (p. 66). The failure or success of an innovation depends on the people affected.

In an effort to review the literature to study the effects and barriers of new

technology, innovation was found to be a close companion to new technology. One of the best explorations of technology occurs in Witold Rybczynski's Taming The Tiger: The

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tiger. Part of the difficulty of taming the tiger is that we can't see the animal clearly. It is easy to identify the boldly striped beast in a cage, but in the splotchy light of the jungle its colors

become confused with background shadows. So too with technology. It is easy to discuss in isolation, but immersed in the opacity of human culture its outlines frequently become indistinguishable from its surroundings. This is all the more true because we live in such close proximity to all sorts of machines and we tend to see only a part of the whole. Occasionally, one machine will come to the fore - the computer, for instance - but in focusing on one manifestation of technology we lose sight of the overall pattern. Since we lack the historical perspective to observe the pattern of our own technological environment, we have frequently failed to see what should have been obvious: technology is not a thing (p. 213).

Jay (1981) stated that many instructors are afraid of computers, and that fear is only part of a larger "...technophobia that has been engendered by our recent period of rapid technological growth and development." He defines computerphobia as a negative attitude that takes the form of:

a.) resistance to talking or even thinking about computer technology; b.) fear or anxiety, which may even create physiological consequences; c.) hostile or aggressive thoughts and acts, indicative of some

underlying frustrations (p. 47).

Jay (1981) further stated that instructors may exhibit some of these resistances, fears, anxieties, and hostilities in:

1.) a fear of physically touching a computer;

2.) a feeling that one could break or damage the computer or somehow ruin what is inside;

3.) a failure to engage in reading or conversation about the computer, a type of denial that the computer really exists;

4.) feeling threatened, especially by students, and others who do know something about computers;

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a machine, (b) feeling dehumanized, or feeling aggressive toward computers (let's bend, fold, and mutilate these cards!). Such feelings are indicative of an underlying feeling of

insecurity and lack of control; and

6.) a type of role reversal, whereby the person assumes the role of slave to technology rather than the master of a fine tool (p. 47).

Jay (1981) theorized the reasons this "computerphobia" to be both individual and organizational: individual in the failure of the instructor to keep current in the advances in technology affecting their life; organizational in that the institution may not have taken all jobs into consideration when planning to use a new technology. Also, institutions may fail to provide incentives to educators to remain current in technology. These may include training, time for workshops and seminars, funds for courses, time for learning new technology, and incentives (recognition, money) to develop changes in courses to incorporate the use of the computer.

Rosen and Weil (1990), stated that computers are now commonplace on all college campuses and most elementary and secondary schools. They stated that, "At the close of the 1980s, computer manufacturers estimate that one in four households currently own a home computer and that this number will double by the year 2000"(p.275).

As Rosen and Weil state, the computer is part of our everyday lives: ATMs, or automatic teller machines; pay-at-the-pump gas stations; voicemail; E-mail; video cassette recorders (VCRs); on-board guidance systems for automobiles; the list is endless.

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enter these air-conditioned environments and actually touch these machines. Contact consisted of spending hours punching small holes in crisp stiff cards and then handing them over to a white-coated attendant and then waiting overnight, or even days, for the resultant printout.

Today, just over thirty years later, the computer is part of the standard university curriculum. Almost every department and school has an applied computer component as part of their field of study. The computer is no longer the exclusive domain of the

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machine for some. Others may have "...grave discomfort and impaired ability when they must use a computer, and avoidance of all computers and computer-related technology whenever possible" (p.276).

For their research, Rosen and Weil (1990) defined the computerphobic as evidencing one or more of the following:

a.) anxiety about present or future interactions with computers or computer-related technology;

b.) negative global attitudes about computers, their operation or their societal impact; or

c.) specific negative cognition or self-critical internal dialogues during actual computer interaction or when contemplating future computer interaction (p.276).

This label computerphobic can be applied to individuals who range from "...severe reactions on all dimensions to mild discomfort on a single dimension" (p. 276).

Rosen and Weil (1990) went on to detail several researchers' attempts to explain the problem. They stated that Meier proposed "computer aversion" as a negative affective state, explainable by a social learning theory expectancy model.

They also shared that Glass and Knight adapted Meichenbaum and Butler's cognitive model of test anxiety to develop a model of computer anxiety. Rosen collaborated with Deborah Sears to develop a computerphobia treatment program based on a combined cognitive-behavioral model, drawing from behavior therapy approaches and cognitive behavioral approaches.

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among groups of people in the United States. Although most

researchers have studied undergraduate and graduate university students (Bandalos & Bensen, 1990; Chu & Spires, 1991; Cohen &Waugh, 1989; Gilroy & Desai, 1986; Glass & Knight, 1987; Gressard & Loyd, 1986; Heinssen, Glass, & Knight, 1987; Hudiburg, 1989; Igbaria & Chkrabarti, 1990; Jonassen, 1986; Jones & Wall, 1985; Jordan & Stroup, 1982; Kernan & Howard, 1990; Liu, Reed & Phillips, 1990; Marcoulides, 1988, 1991; Marcoulides & Wang, 1990; Powers, Cumming, & Talbott, 1973; Raub, 1982; Rosen, Sears, & Weil, 1987; Sigurdsson, 1991; Weil, Rosen, & Wugalter, 1990), others have examined computer anxiety among school teachers (Gressard & Loyd, 1984; Honeyman & White, 1987; Issa & Lorentz, 1988, 1989; Kotlrik & Smith, 1989; Lindbeck & Dambrot, 1986; Mertens & Wang, 1988; Rosen & Weil, 1995; Simonson, Maurer, & Montag-Torandi, 1987), public school students (Koohang, 1986; Pilotte & Gable, 1990), business managers (Howard & Smith, 1986), or other people for the general population (Temple & Gavillet, 1990; Herkimer, 1985)(p. 46).

In their cross cultural comparison of university students in ten countries, Rosen & Weil (1995) measured computer anxiety in university freshmen in ten countries (Japan, Australia, Germany, Hungary, Spain, Yugoslavia, Italy, Israel, Czechoslovakia, and the United States). They found "...that computer anxiety is not a culture-free construct. It means very different things to students around the world...technological gadgets pose different problems for students in different counties." (p. 60).

Maurer (1994) developed a model of the development of computer anxiety as part of a literature review:

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influence the development of computer anxiety, but they may only influence its development in an indirect fashion. Other variables, such as demographic characteristics (e.g., socioeconomic status or gender) and life choices

(e.g., academic major or career choices) interact indirectly with computer anxiety by affecting the amount of computer experience. Personality characteristics also affect computer anxiety indirectly by affecting life

choices and computer experience. In addition, some cycles may exist between these variables (e.g., computer experience affects life choices, which in turn affects computer experience, which ultimately affects computer anxiety). The most important cycle is between computer anxiety and computer

experience. It is likely that they each affect the other (p. 374).

Lawton and Gerschner (1982) found that factors influencing attitudes toward computer literacy or computer illiteracy include:

(a.) the numerous terms used in computer instruction,

(b.) the various methodologies used to assess the effectiveness of and attitudes towards projects,

(c.) the variety of software described in the studies, and

(d.) the various aspects of implementation which contribute towards "computerphobia"(p.51).

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more planning, and being aware of the impact of the computer on people would make teachers more receptive to computers and would encourage the growth of computer literacy.

In their review of the literature concerning teachers' attitudes toward computers, Dupagne and Krendl (1992) found that in the prior two decades, teachers had ambivalent attitudes toward computer technology. They reported a study conducted in 1976 by Lichtman (1979) which found educators were less favorable toward computers than the general public. Computer technology was regarded by 55% of teachers responding as a dehumanizing tool.

Another study reported by Dupagne and Krendl, that of Stevens (1980), surveyed 657 K-12 teachers and found that although they strongly supported computer literacy instruction in secondary schools, 90% did not consider themselves qualified to teach computer literacy studies and almost 40% felt anxiety not only when around computers, but also when others were just talking about computers.

In Dupagne and Krendl's (1992) review of the literature, they reported: Overall, teachers in recent years have been enthusiastic about and have expressed positive attitudes towards the implementation of microcomputers in the classroom and curriculum (Aust, Allen, & Bichelmeyer, 1989; Austin, 1988; Bassler, Almeida, & Van Voorst, 1984; Davis, 1988; Delfrate, 1987; Grasty, 1985; Harmon, 1985; Olson, 1986; Robinson, 1984; Savenye, 1989; Toomey, 1987). The level of enthusiasm about computer use increases with the individual teacher level of computer experience (Koohang, 1987; Woolsey, 1985).

In expressing their concerns about computer use, teachers report that they do not have enough time to carry out computer activities in the classroom (Aust et al., 1989; Cox, Rhodes, & Hall, 1988; Manarino-Lettett & Cotton, 1985; Olson, 1986; Taylor, 1987;

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lack of hardware and software (Hagey, 1985; Knupfer, 1989; Olson, 1986; Taylor, 1987; Woodward & Mathinos, 1987), lack of relevant achievement tests to evaluate student performance (Woodward & Mathinos, 1987), and inadequate training (Taylor, 1987; Woodrow, 1987).

Teachers who use or own computers are more likely to exhibit favorable attitudes towards computer use in the classroom (Bassler et al., 198; Burke, 1986; Delfrate, 1987; Taylor, 1985). Educators with previous computer skills tend to show lower levels of anxiety towards computers than do other educators (Honeyman & White, 1987). In sum, the literature suggests that computer experience fosters positive attitudes toward the use of computers (p.421).

Rosen, Sears and Weil (1987), report that in 1963, Lee reported the general public held two independent beliefs about computers: "...computers are useful tools of mankind, and that computers are relatively autonomous and eventually will control society"(p.168).

Smith and Kotrlik (1990) conducted a study of eleven of the thirteen Southern states extension services (North Carolina and Kentucky did not participate). Using Oetting's COMPAS (COMPuter Anxiety Scale), 544 randomly chosen county agents

returned 522 usable surveys, they found that overall 55% of agents were computer anxious. In their conclusion, they stated Extension administrators may facilitate acceptance and use of computers if they "...show a commitment to computer technology in their organizations, organize formal computer training for agents, provide facilities and offer incentives and rewards for agents to use computers, and extend specialist support for continued practice."