Pilot Study on Student Public Opinion Regarding GAI
William Franz Lamberti, Sunbin Kim, Samantha Rose Lawrence
TL;DR
This study investigates university students' attitudes toward generative AI in higher education, addressing a gap in classroom-based public opinion data. Using a pre/post survey design within GMU CDS 130 courses, it analyzes attitude shifts after a brief instructional video via a $Binomial(n,p)$ framework and exact Clopper–Pearson $CI$s. The findings reveal a very low participation rate (≈$0.044$; $95\\%$ CI $(0.009,0.124)$) and limited evidence of systematic opinion change, with some questions showing shifts while others remain stable. The work underscores the need for larger class samples and multiple iterations to achieve statistically robust insights, and it provides groundwork for incorporating GAI discussions into course design to foster informed, critical engagement.
Abstract
The emergence of generative AI (GAI) has sparked diverse opinions regarding its appropriate use across various domains, including education. This pilot study investigates university students' perceptions of GAI in higher education classrooms, aiming to lay the groundwork for understanding these attitudes. With a participation rate of approximately 4.4%, the study highlights the challenges of engaging students in GAI-related research and underscores the need for larger sample sizes in future studies. By gaining insights into student perspectives, instructors can better prepare to integrate discussions of GAI into their classrooms, fostering informed and critical engagement with this transformative technology.
