A study of reactive behavior patterns and online technological self-efficacy DISSERTATION
Thomas Eugene Bayston, University of Central Florida, United States
University of Central Florida . Awarded
The purpose of this study is to look for relationships between Dr. William Long's Reactive Behavior Types and Traits and online technology self-efficacy as measured by Miltiadou and Yu's Online Technology Self-Efficacy Scale. To determine if the survey was truly measuring technological task-specific “state” efficacy or a more generalized “trait” of self-efficacy, general self-efficacy and academic self-efficacy scales were included. The self-efficacy items were all converted to a forced-choice 4-point Likert type scale. The survey instrument was administered during class time to 261 students in the education college of a major Florida state university. Internal reliability tests yielded Cronbach's alpha of .95, .94, and .86 for the OTSES, general, and academic scales respectively. Validity was confirmed by factor analysis using SPSS's Promax oblique rotation. ANOVA tests at alpha value .05 for OTSES scores across Long's Types and Traits resulted in no statistically significant effects. Although positive Pearson's correlation coefficients between OTSES and general and OTSES and academic self-efficacies were statistically significant, the coefficient sizes (r <= .21) were too small to conclude a generalized self-efficacy trait over task-specific state. Although Long's Types do not appear to be a factor, low self-efficacy did occur among 16.7% of the responses. Since self-efficacy can be vicariously modeled, education of future teachers should be designed to alleviate low technological self-efficacy.
Bayston, T.E. A study of reactive behavior patterns and online technological self-efficacy. Ph.D. thesis, University of Central Florida. Retrieved June 19, 2018 from https://www.learntechlib.org/p/123537/.
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