Integrating large language models and generative artificial intelligence tools into information literacy instruction

Abstract

Generative artificial intelligence (AI) and large language models (LLMs) have induced a mixture of excitement and panic among educators. However, there is a lack of consensus over how much experience science and engineering students have with using these tools for research-related tasks. Likewise, it is not yet known how educators and information professionals can leverage these tools to teach students strategies for information retrieval and knowledge synthesis. This study assesses the extent of students' use of AI tools in research-related tasks and if information literacy instruction could impact their perception of these tools. Responses to Likert-scale questions indicate that many students did not have extensive experience using LLMs for research-related purposes prior to the information literacy sessions. However, after participating in a didactic lecture and discussion with an engineering librarian that explored how to use these tools effectively and responsibly, many students reported viewing these tools as potentially useful for future assignments. Student responses to open-response questions suggest that librarian-led information literacy training can assist students in developing more sophisticated understandings of the limitations and use cases for artificial intelligence in inquiry-based coursework.