In this research, it was proposed that self-efficacy is the missing underlying psychological factor in innovation diffusion models of higher education. This is based upon research conducted in the fields of innovation-diffusion in higher education, technology adoption, self-efficacy, health and behavioral change. It was theorized that if self-efficacy is related to adoption, it could provide a quick-scoring method for adoption efficiency and effectiveness that would be easy to administer. The innovation-diffusion model used in this study was Hall and Hord\'s (1987) Concerns Based Adoption Model (CBAM) and it\'s Seven Stages of Concern (SoC) About an Innovation. The SoC measures a user\'s perception of"and concerns about"an innovation over time. The self-efficacies under study were general, teaching, and technology. The scales used in this research instrument were Chen\'s New General Self-Efficacy (NGSE), Prieto\'s College Teaching Self-Efficacy Scale (CTSES), and Lichty\'s Teaching with Technology Self-efficacy scale (MUTEBI), respectively. This research hoped to uncover a relationship between self-efficacies and a Stage of Concern in the adoption of an instructional technology innovation, Google Apps for Education, at a large university institution. Over 150 quantitative responses were collected from a pool of 1,713 instructional faculty between late Fall 2012 and early Spring 2013 semesters. The response group was not representative of the larger population. Forty-six percent represented non-tenure track faculty compared to the expected 19 percent. Analysis using nominal logistic regression between self-efficacy and Stages of Concern revealed that no statistically significant relationship was found. Of note is that nearly all participants could be classified as being in the early-stages of an innovation adoption, possibly skewing the overall results. / Ph. D.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/19340 |
Date | 23 April 2013 |
Creators | Marcu, Amber Diane |
Contributors | Teaching and Learning, Cennamo, Katherine S., Evans, Michael A., Doolittle, Peter E., Moore, David M. |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Dissertation |
Format | ETD, application/pdf, application/pdf, application/pdf, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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