Generative Artificial Intelligence in Academic Help Seeking

University Of North Carolina At Chapel Hill, Chapel Hill NC

Investigators

Abstract

This three-year mixed-methods project investigates how college students in science, technology, engineering, and mathematics (STEM) disciplines engage with generative artificial intelligence (AI) tools for academic help-seeking. As AI technologies become increasingly embedded in higher education, students encounter growing uncertainty about how to use these tools. Through surveys, interviews, and case studies, the project will generate empirical data to better understand how students use AI tools, the challenges they face in doing so, and the kinds of guidance or support they find most helpful. These findings will inform the development of institutional strategies for the use of AI. Project goals include supporting student learning, strengthening AI literacy, and upholding academic integrity. The central research questions guiding this project are: how do STEM students use generative AI for academic support, and how can institutions apply this knowledge to develop policies and support services? The project addresses a critical knowledge gap regarding how students are incorporating AI into their academic routines and how universities can respond with policy. The study integrates qualitative and quantitative methods, combining grounded theory analysis of interview and focus group transcripts with descriptive and inferential statistical analysis of survey data. The findings will inform the creation of policy briefs, a comprehensive policy recommendation, and a series of librarian-led workshops aimed at strengthening institutional guidance and support for generative AI use. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.