University Students’ Attitudes Toward and Intentions to Use Generative AI in the Classroom: Findings from Pre- and Post-GenAI Teaching Initiative Surveys

This study aimed to examine and compare factors associated with support for integrating GenAI into classroom settings and the intention to use GenAI tools in future education among students in pre- and post-GenAI teaching initiative surveys in an R1 university in the United States. Online surveys via Qualtrics were administered at the start and end of the Fall 2024 semester. Descriptive and bivariate analyses and ordered logistic regression models were conducted. In the pre-GenAI teaching initiative survey, significant predictors associated with students’ support for GenAI tools were students’ interest in GenAI and perceived usefulness. Significant predictors associated with their intention to use GenAI in future education included being non-White, interest in GenAI, perceived usefulness, and supportive attitudes toward GenAI. In the post-GenAI teaching initiative survey, students showed increased support for and intention to use GenAI. Significant predictors of students’ support for GenAI included being a STEM major, interest in GenAI, perceived importance of GenAI in internships and future jobs, and perceived usefulness. Significant predictors associated with their intention to use GenAI tools were being an international student, perceived usefulness, and supportive attitudes toward GenAI. Results suggest that integrating GenAI into higher education is feasible, but it needs to emphasize the importance and usefulness of students’ current studies and future careers. We recommend that faculty and students get trained on how to use and implement GenAI in the classroom settings under academic integrity. It also calls for higher education institutions to develop clear policies around transparent, responsible, and ethical use of GenAI in educational settings.