Date

5-1-2025

Department

School of Education

Degree

Doctor of Philosophy in Higher Education Administration (PhD)

Chair

Eric Lovik

Keywords

artificial intelligence, higher education, generative artificial intelligence, faculty perceptions, community college faculty, attitudes, benefits, threats, artificial intelligence in higher education, teaching and learning with artificial intelligence, ChatGPT, gender, age, two-way MANOVA, large language models

Disciplines

Education | Higher Education

Abstract

The purpose of this quantitative causal-comparative study was to determine the differences in attitudes, benefits, and threats of using artificial intelligence tools in teaching and learning among community college faculty in Tennessee. The findings of this study are important because faculty acceptance or rejection of emerging technology determines educational innovation. The sample was composed of 211 full-time faculty employed at twelve community colleges in Tennessee. Data were collected using the Attitudes, Benefits, and Threats instrument which was administered by electronic survey. The results of the two-way MANOVA did not find a significant difference among attitudes, benefits, and threats associated with the use of artificial intelligence as a teaching and learning tool among community college faculty based on intrinsic characteristics of gender and age. The rejection of the null hypothesis indicates that the independent variables of gender and age do not interact regarding overall perceptions of AIED. However, the post hoc test findings of this study revealed the means for threats scores in males were lower than in females, which indicates that males do not perceive artificial intelligence in teaching and learning as highly threatening as females do among the participants surveyed. The findings of this study revealed means for attitude scores were statistically significant between age groups 27-42 and 43-58 as determined by Post Hoc Tukey tests, with the younger age group of 27-42 scoring more negative attitudes than the older age group of 43-58. This research has limitations due to the quantitative design and the anonymity of participants. Future research is needed to determine if faculty discipline and rank affect perceptions of AIED. Additionally, a more in-depth understanding of perceptions of AI tools use and adoption could be enhanced by conducting a qualitative research study.

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