Development of a predictive model for faculty integration of technology in higher education

The purpose of this research project was to develop a predictive model for faculty integration of technology in higher education, specifically among faculty who are members of the Commission of Professors of Adult Education. The variables included both those that the educational institution could affect, such as technical support, release time, tenure and promotion opportunities, and personal variables of faculty, such as computer self-efficacy, attitudes towards computers and perceived institutional support. Three hundred and eighty-nine (389) surveys were mailed to the sample participants. One hundred and twenty-four (124) were returned completed, thirty-six were returned undeliverable and seven were deemed unusable, for a return rate of 33.14%. The survey used in this study, the "Instructional Technology Integration Assessment" was adapted from the Computer Self Efficacy Scale (CSE), developed by Murphey and others (1988) and the Middle Tennessee State University Survey developed by Lea, Brace and Roberts (1998). Multiple regression was performed, using the Statistical Package for the Social Sciences (SPSS) to determine which of the variables showed a stronger influence on the dependent variable. Integration of technology significantly correlated with five of the variables: Job Satisfaction (.403, p < .001); Quality of My Instruction (.422, p < .001); Tenure and Promotion Opportunities (.240, p < .05); and the Impact of Technology on the Depth and Breadth of Content and Student Participation (.347, p < .001). Years Teaching in Higher Education was negatively correlated with Integration (-.185, p < .05). With a multiple regression correlation coefficient (R) of .550, the squared multiple correlation coefficient (R2) resulted in .303. Thirty percent (30%) of the variance in integration could be accounted for by the predictor variables. Analysis of responses to open-ended questions revealed three main themes in regards to barriers and incentives for technology integration: psycho/social barriers, student readiness barriers and institutional barriers. Suggestions for future research included adding variables such as learning style, teaching style and fear of change to the overall survey.