A Survey on Student Use of Generative AI Chatbots for Academic Research - Deschenes, Amy; McMahon, Meg (Evidence Based Library and Information Practice, 2024)
Objectives – To understand how many undergraduate and graduate students use generative AI as part of their academic work, how often they use it, and for what tasks they use it. We also sought to identify how trustworthy students find generative AI and how they would feel about a locally maintained generative AI tool. Finally, we explored student interest in trainings related to using generative AI in academic work. This survey will help librarians better understand the rate at which generative AI is being adopted by university students and the need for librarians to incorporate generative AI into their work.Methods – A team of three library staff members and one student intern created, executed, and analyzed a survey of 360 undergraduate and graduate students at Harvard University. The survey was distributed via email lists and at cafes and libraries throughout campus. Data were collected and analyzed using Qualtrics.Results – We found that nearly 65% of respondents have used or plan to use generative AI chatbots for academic work, even though most respondents (65%) do not find their outputs trustworthy enough for academic work. The findings show that students actively use these tools but desire guidance around effectively using them.Conclusion – This research shows students are engaging with generative AI for academic work but do not fully trust the information that it produces. Librarians must be at the forefront of understanding the significant impact this technology will have on information-seeking behaviors and research habits. To effectively support students, librarians must know how to use these tools to advise students on how to critically evaluate AI output and effectively incorporate it into their research.