Analysis of Professors’ Experiences with Generative AI and the Concerns of Classroom Use : Application of the Concerns-Based Adoption Model (CBAM)

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Abstract

The rise of generative AI, such as ChatGPT, poses challenges for the education sector. To explore strategies for addressing generative AI issues and identifying educational applications, it is essential for us to understand the concerns and attitudes of educators, who are the key implementers in education. In this context, this study investigated the experiences and concerns of university professors regarding the educational use of generative AI by utilizing the Concerns-Based Adoption Model (CBAM). Data was collected from 100 professors representing various disciplines at University A in Gyeonggi-do. The majority of respondents had some experience with generative AI, but its educational utilization was limited. Concerns included the provision of incorrect or biased information, ethical issues, and users' lack of ability to use generative AI. However, 61% of respondents expressed their intention to apply generative AI in their courses in the upcoming semester. Concern levels aligned with the non-user profile, with lower concerns in the consequence stage. There were no significant differences in concern levels based on the professors' disciplines, but differences were observed based on their experience and intention to use generative AI in their classes. Professors who had already used generative AI in their classes showed higher concerns regarding the consequence, collaboration, and refocusing stages. Based on these findings, implications for the educational use of generative AI in higher education were discussed.

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