While recent research has investigated how students perceive generative AI tools (Amani et al., 2023; Chan & Hu, 2023; Johnston et al., 2024) little is known about how AI use reshapes their underlying information assumptions and behaviors. Drawing on Dervin’s ten information assumptions, such as “More information is always better”, this study examines how the information behaviors of first-year students have evolved in an information landscape that includes AI generated text and images. Using a survey adapted from Cole, Napier, and Marcum and a complementary interview protocol, we will share our analysis of new 2025 data on the potential impact of generative AI through a longitudinal study with data starting from 2017. Our questions probe critical topics such as students’ evaluation of image authenticity, their use of generative AI in searches, and how they assess the reliability of AI-generated textual information. This research provides a unique perspective on first-year students’ understanding of authenticity, evaluation practices, and generative AI’s limitations.
Participants will engage with both qualitative and quantitative results to gain practical strategies for integrating these insights into library instruction and basic AI education. The session will include reflective questions and use collaborative tools like Padlet to encourage active participation and anonymous sharing of ideas.
At the end of this presentation, participants should be able to:
• Understand some of the changes in information beliefs based on AI
• Apply our findings to their own IL teaching practices
Participants are encouraged to bring their electronic devices. Presenters will need to be able to project a PowerPoint presentation on a screen and have microphones for accessibility. Target audience: Any librarian who works with students, particularly at a college or university.
References :
Amani, S., White, L., Balart, T., Arora, L., Shryock, K. J., Brumbelow, K., & Watson, K. L. (2023). Generative AI Perceptions: A Survey to Measure the Perceptions of Faculty, Staff, and Students on Generative AI Tools in Academia. arXiv preprint. doi:https://arxiv.org/abs/2304.14415
Chan, C. K., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). doi:10.1186/s41239-023-00411-8
Cole, A., Napier, T., & Marcum, B. (2015). Generation Z: Facts and Fictions. In H. Jagman, & T. Swanson, Not Just Where To Click: Teaching Students How To Think About Information.
Dervin, B. (1976). Strategies for dealing with human information needs: information or communication. Journal of Broadcasting and Electronic Media, 20(3), 324-333.
Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educaitonal Integrity, 20(1). doi:10.1007/s40979-024-00149-4
