Abstract
This chapter situates the emerging scholarly conversation around AI literacy within the established Association for College and Research Libraries (ACRL) Framework for Information Literacy for Higher Education. We apply three frames in particular: 1) Authority Is Constructed and Contextual, 2) Information Creation as a Process, and 3) Research as Inquiry, considering competencies relevant to students encountering generative AI applications in educational contexts and addressing ways that both students and instructors may seek to engage productively with such tools.
This chapter primarily focuses on tools such as ChatGPT that are built atop large language models (LLMs)—systems trained on massive text corpora—rather than other AI applications such as image generators. With librarians in mind, we draw on some of their particular strengths and approaches to the student learning process. Given their professional skills in teaching information literacy concepts, librarians are uniquely situated to engage students directly on how generative AI applications are impacting their educational experiences, future academic work, and civic lives.
Document Type
Book Chapter
Publication Date
2025
Repository Citation
Wink, Isaac and Hootman, Jennifer, "Framing Large Language Models: Teaching Foundational Concepts of Generative AI and Information Literacy for Critical Student Engagement" (2025). Library Faculty and Staff Publications. 362.
https://uknowledge.uky.edu/libraries_facpub/362
Notes/Citation Information
Published in Text and Data Mining Literacy for Librarians. Whitney Kramer, Iliana Burgos, & Evan Muzzall, (Eds.). p. 89-102.