Exploring University Educators’ Perceived Competence, Acceptance, and Use of Generative AI: A Mixed-Methods Study Using TAM and TPACK Frameworks

Author

• Sanju Gharti Chhetri G.C., University of South AlabamaFollow

Date of Award

8-2026

Document Type

Dissertation

Degree Name

Ph.D.

Department

Instructional Design and Development

Committee Chair

James P. Van Haneghan, Ph. D.

Abstract

As Generative AI (GenAI) technology becomes increasingly embedded in education, its effective use and integration hinges on the competence, attitudes, and experience that shape educators’ acceptance and behavioral intention to adopt it. Drawing on the TAM and TPACK frameworks, this study examined the relationship between university teachers’ perceived competence and self-efficacy (SE) in GenAI, measured via the Teacher AI Competence Self-Efficacy (TAICS) scale, and their acceptance and behavioral intention (BI) to adopt GenAI technology in teaching. This mixed-methods study used path analysis to test hypothesized predictive relationships and thematic analysis of open-ended responses to develop a comprehensive understanding of faculty competence, experience, and attitudes toward GenAI. Data were collected through validated survey instruments and open-ended questions from 119 faculty members at three universities across the southern United States. The study used purposive sampling where university educators teaching baccalaureate and/or graduate level courses were the sample demographic. The results confirmed statistically significant predictive relationships between teachers’ AI competence/self-efficacy (TAICS) and both behavioral intention (BI) to adopt GenAI as well as perceived usefulness (PU) of GenAI. Contrary to the assumptions of TAM, perceived ease of use (PEU) however did not significantly predict faculty members’ perceived usefulness (PU) or attitude towards GenAI technology (ATT). Notably, human-centered education (HCE), one dimension of the AI competence scale capturing critical and ethical awareness of AI, negatively predicted perceived usefulness (PU) and behavioral intention (BI) suggesting that faculty who were critically aware about GenAI were less likely to perceive it as useful and adopt it. The qualitative responses clarified this finding as it revealed faculty members who were knowledgeable about GenAI and reported high self-efficacy were also critical of GenAI technology. Furthermore, ethically grounded awareness of AI played a role in dissuading their inclination to adopt GenAI. While a majority of faculty (66%) reported using GenAI, many voiced concerns about student overreliance, the erosion of critical thinking, academic integrity, privacy, and environmental impact of GenAI. The findings further revealed limited AI readiness among faculty and a widespread institutional policy vacuum surrounding GenAI use in education. The study concludes that AI literacy does not necessarily translate into adoption. For many faculty, GenAI integration represented a matter of ethics and moral principle rather than preference. The findings carry significant theoretical implication as it extends TAM and TPACK frameworks by situating it within the emerging context of GenAI as well as practical implications for policy, faculty development, and effective and ethical integration of GenAI in higher education.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Chhetri G.C., Sanju Gharti, "Exploring University Educators’ Perceived Competence, Acceptance, and Use of Generative AI: A Mixed-Methods Study Using TAM and TPACK Frameworks" (2026). Graduate Theses and Dissertations (2019 - present). 260.
https://jagworks.southalabama.edu/theses_diss/260