FACTORS AFFECTING ADOPTION AND DIFFUSION OF DISTANCE .
FACTORS AFFECTING ADOPTION AND DIFFUSION OF DISTANCEEDUCATION AMONG HEALTH EDUCATION FACULTYByJames W. BallB.S., University of Wisconsin-La Crosse, 2002M.S., University of Wisconsin-La Crosse, 2007A DissertationSubmitted in Partial Fulfillment of the Requirements for theDoctor of Philosophy in Education degree with a concentration in Health EducationDepartment of Health Education and Recreationin the Graduate SchoolSouthern Illinois University, CarbondaleMay 2013
FACTORS AFFECTING DISTANCE EDUCATIONiiAN ABSTRACT FOR THE DISSERTATION OFJAMES W. BALL, for the Doctor of Philosophy degree in HEALTH EDUCATION,presented on March 19th, 2013 at Southern Illinois University Carbondale.TITLE: FACTORS AFFECTING ADOPTION AND DIFFUSION OF DISTANCEEDUCATION AMONG HEALTH EDUCATION FACULTYMAJOR PROFESSOR: Dr. Joyce Fetro and Dr. Roberta OgletreeBackground: In the past decade, distance education enrollment has become more common incolleges and universities, increasing from 1.6 million students in 1998 to an estimated 6.7million in 2012. The purpose of this study was to identify which constructs in Rogers’ (2003)diffusion of innovation theory are more likely to contribute to adoption and diffusion of distanceeducation in health education. Hopefully, health education instructors and faculty will use theinformation obtained from the results of this study to implement distance education.Methods: A quantitative, cross-sectional, descriptive, and correlational survey design was usedin this study. An instrument designed to measure constructs and factors affecting the adoptionand diffusion of distance education in health education was developed for the study. Healtheducators employed by health education departments listed in the AAHE (2011) Directory(n 498) were contacted by email and asked to participate in this study. The survey wasdistributed through SurveyMonkey survey software that was activated December 2012 January 2012.Results: A total of 245 health education faculty completed the instrument, but 21 participantswere omitted because they did not complete at least 95% of the survey instrument. A total of224 survey instruments were retained and included in the analysis, providing a 44.9% responserate. Overall, the likelihood of distance education adoption by health education faculty is highlydependent on the communication channels and characteristics of the innovation (distance
FACTORS AFFECTING DISTANCE EDUCATIONiiieducation) constructs of the diffusion of innovation theory. There was a large majority ofparticipants in the early majority adopter category and this is because of two reasons.Participants have not decided whether to accept or reject distance education. Distance educationis a relatively new innovation and it has not fully diffused through the health educationprofession. Experience with distance education was not shown to increase the likelihood ofdistance education adoption because the majority of participants have not yet decided whether toaccept or reject distance education. The social system construct was the least predictive ofdistance education adoption. If distance education has not yet fully diffused through the healtheducation profession then it is hard for the social system to impact the likelihood of distanceeducation adoption.
FACTORS AFFECTING DISTANCE EDUCATIONivTABLE OF CONTENTSCHAPTERPAGEABSTRACT . iiList of Tables . viList of Figures . viiiChapter 1 INTRODUCTION . 1Introduction . 1Background of the Problem. 1Theoretical Framework . 3Need of the Study . 5Purpose of the Study . 6Significance to Health Education . 7Research Questions . 8Research Design . 9Study Participants . 9Data Collection . 9Data Analyses . 10Assumptions . 11Limitations . 11Delimitations . 12Definition of Terms . 12Summary . 15Chapter 2 LITERATURE REVIEW . 17Introduction . 17The Evolution of Distance Education . 17The Current State of Distance Education . 20Advantages of Distance Education in Education and Health . 24Disadvantages of Distance Education in Education and Health . 35Effective Implementation Practices in Distance Education . 39Diffusion of Innovation . 40Diffusion of Innovation in Education and Health . 48Summary . 50CHAPTER 3 METHODS . 51Introduction . 51Purpose of the Study . 51Research Questions . 52
FACTORS AFFECTING DISTANCE EDUCATIONInstrument Development . 52Research Design . 57Study Participants . 58Data Collection . 60Data Analysis . 61Summary . 63Chapter 4 Results . 67Introduction . 67Purpose of the Study . 67Research Questions . 67Sample Demographics. 68Analysis of Research Questions . 72Summary . 92Chapter 5 Summary, Conclusions, Discussion, and Recommendations . 94Introduction . 94Purpose of the Study . 94Research Questions . 94Conclusion. 96Discussion . 97Recommendations for Future Reference . 106Recommendations for Future of Health Education Profession . 107Summary . 110REFERENCES . 113APPENDICES . 133Appendix A - Five Pillars of Quality Distance Education . 133Appendix B - Professional Background of Expert Panel Members . 136Appendix C - Expert Panel Member Comments . 139Appendix D - Instrument for Pilot Study and Likert Scale . 156Appendix E - Instrument in Survey Monkey for Main Study . 161Appendix F - Instrument for Main Study and Constructs . 167Appendix G - Email Solcitation to Participants for Study . 173Appendix H - Cover Letter on Survey Monkey for Study . 175Appendix I – Institutional Review Board Approval for Main Study . 177Appendix J - Mean and Standard Deviations for all Items .179v
FACTORS AFFECTING DISTANCE EDUCATIONviLIST OF TABLESTABLEPAGETable 1 Reliability of the Final Instrument as Measured by Cronbach Alphas . 58Table 2 Sample Items from the Survey Instrument . 59Table 3 Data Analysis Summary . 64Table 4 Demographic Characteristics of Study Participants . 70Table 5 Example of How Experience Variable was Calculated . 71Table 6 Total Number of Participants in each Adopter Category . 71Table 7 Cronbach Alphas of Developed Instrument . 73Table 8 Frequencies and Percentages of Perception of Need Responses . 74Table 9 Frequencies and Percentages of Characteristics of Innovation Responses . 75Table 10 Frequencies and Percentages of Social System Responses . 79Table 11 Frequencies and percentages of Communication Channels Responses . 80Table 12 Frequencies and Percentages of Characteristics of Adopters Responses . 81Table 13 Independent Sample T-test Results by Gender . 83Table 14 Independent Sample T-test Results by Highest Degree (Master’s/PhD) . 83Table 15 Independent Sample T-test Results by Type of Institution (Private/Public) . 83Table 16 Independent Sample T-test Results by Experience . 83Table 17 One-way ANOVA Results by Age. 84Table 18 One-way ANOVA Results by Type of Institution (Research/Teaching/Both) . 84Table 19 One-way ANOVA Results on Perceptions of Need Construct . 86Table 20 Tukey’s HSD Results on Perceptions of Need Construct . 86Table 21 One-way ANOVA Results on Characteristics of Innovation Construct . 86Table 22 Tukey’s HSD Results on Characteristics of Innovation Construct . 87Table 23 One-way ANOVA Results on the Social System Construct . 87Table 24 Tukey’s HSD Results on the Social System Construct . 87Table 25 One-way ANOVA Results on the Communication Channels Construct . 88Table 26 Tukey’s HSD Results on the Communication Channels Construct . 88
FACTORS AFFECTING DISTANCE EDUCATIONTable 27 One-way ANOVA Results on the Characteristics of Adopters Construct. 89Table 28 Tukey’s HSD Results on the Characteristics of Adopters Construct . 89Table 29 Pearson Correlation Test Results Experience . 91Table 30 Pearson Correlation Test Results Participant’s Total Score . 91Table 31 Model Summary of Linear Regression Analysis . 93Table 32 Full Regression Model . 93Table 33 Summary of Linear Regression Individual Predictors . 93vii
FACTORS AFFECTING DISTANCE EDUCATIONviiiLIST OF FIGURESFIGUREPAGEFigure 1 Model of the Innovation-Decision Process for this Study . 44
FACTORS AFFECTING DISTANCE EDUCATION1Chapter 1IntroductionDistance education has been a part of the United States educational system since the1800’s. The United States Postal Service (USPS) provided long distance communicationcapabilities in the United States, leading to the beginning of distance education (Casey, 2008).Casey (2008) explained that the first correspondence course classified as a distance educationcourse was developed in 1852. Since this course, distance education has evolved along withadvances in technology in our society. Advances in technology that followed the USPS includeradio, television, satellite, and Internet. Distance education courses and programs have beencreated to educate people using all of these systems (Casey, 2008).Background of the ProblemDistance education is quickly becoming an alternative option for people to receive aneducation in the United States. In the Fall of 2007, 28 states offered high school distanceeducation programs (Tucker, 2007). In 2008, 97% of all public schools had a local area networkconnection for Internet access (Gary & Lewis, 2009). It was reported that 55% of public schoolshad students enrolled in distance education courses in 2009-2010 (Queen & Lewis, 2011).“Among those districts, 96% reported having students enrolled in distance education courses atthe high school level, 19% at the middle or junior high school level, and six percent at theelementary school level” (Queen & Lewis, 2011, p. 3).At the post secondary level, in 2006-2007, 66% of postsecondary institutions reportedusing some form of distance education with their students (Parsad, Lewis, & Tice, 2008). In thepast decade, distance education enrollment has become more common in colleges anduniversities, increasing from 1.6 million students in 1998 to an estimated 6.7 million in 2012
FACTORS AFFECTING DISTANCE EDUCATION2(Allen & Seaman, 2012; Doyle, 2009; Harasim, 2000; Lei & Gupta, 2010). Distance educationprovides universities an opportunity to maximize their educational resources to meet the needs ofdiverse students by reducing overcrowded classrooms and providing students with the flexibilityto complete lessons, discussions, and class work at their convenience (Gould, 2003). Allen andSeaman (2010) found that 74% of administrators at public institutions of higher educationbelieved that distance education was critical to include in their long term plans. Increases intechnology over the last century have allowed more high schools and universities to offer theirprograms over the Internet.Increases in technological capabilities are not the only reason why distance education inthe United States has evolved. “Three-quarters of institutions reported that the economicdownturn has increased demand for online courses and programs” (Allen & Seaman, 2010, p. 3).In addition, the next generation of “tech-savvy” students will be entering university systemsacross the United States. Simonson (2010) called this group of students the millennialgeneration, and explained that distance educators needed to establish a level of understandingabout millennial learners so that distance education courses and programs could capitalize on thisgeneration’s interests and abilities.With current increases in enrollment from 1.6 million students to 6.1 million students anddemand from administrators to implement distance education, it will be essential for institutionsof higher education to offer distance education courses and programs of the same quality as faceto-face courses (Allen & Seaman, 2011; Doyle, 2009; Harasim, 2000; Lei & Gupta, 2010).More importantly, it is crucial for the health education profession to increase quality distanceeducation programs, so that it can attract those individuals who are being affected by theeconomic downturn as well as the millennial generation of technologically-savvy students. To
FACTORS AFFECTING DISTANCE EDUCATION3amplify the diffusion of distance education in the health education profession, it is important toidentify characteristics of people who adopt and reject distance education, their perceptionsabout distance education, and other factors affecting adoption and diffusion of distance educationwithin the health education profession.Theoretical FrameworkThe diffusion of innovation theory explained how a new idea, product, or innovationdisperses through society (Rogers, 1962). “Diffusion is a process in which an innovation iscommunicated through certain channels over time among the members of a social system”(Rogers, 2003, p. 5). The main constructs of diffusion of innovation theory are characteristics ofthe innovation, communication channels, social system, and time (Rogers, 2003).An innovation is an idea, practice, or object that is perceived as new by individuals or asocial system (Rogers, 2003). There are five factors related to characteristics of an innovation.Relative advantage is the degree to which the innovation is better
about distance education, and other factors affecting adoption and diffusion of distance education within the health education profession. Theoretical Framework . The diffusion of innovation theory explained how a new idea, product, or innovation disperses through society (Rogers, 1962). “Diffusion is a process in which an innovation is
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Factors Affecting EV Adoption . The factors affecting EV adoption are organized as those that are internal to EVs, like battery performance and price and those that are external, such as fuel prices and charging stations, and the policy mechanisms that may influence adoption.
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Factors were identified based on extensive literature reviews and empirical findings. Three main stages of literature review were conducted: (1) factors influencing user adoption of IT, (2) factors affecting physician adoption of EHR, and (3) findings of relevant studies pertaining EHR adoption by physicians in the KSA.
Modeling carbon diffusion and its role in suppressing boron diffusion in silicon and SiGe has been studied by several groups. While boron diffusion is well-established, different modeling regimes have been developed for carbon diffusion. Each of the existing studies has focused on subsets of the available experimental data. We present a
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