Teaching AI Across the Research Life Cycle

Picture this: a student sends an email to you looking for a specific article. You search for hours only to find out that the student found this article through an AI research platform. It’s fake. One of your most popular databases is promoting a new AI research assistant within the software, but they are not being transparent about how they utilize user information. Do these scenarios sound familiar? Then this course is for you. This course would describe how health sciences librarians can integrate their information literacy expertise into instruction surrounding AI in the context of research. Both instructors of this course have the micro-credential Teaching with AI offered by Auburn University.

Resource URL: pending

Learning Objectives

After completing this course, you will be able to: 

• Participants will be able to identify different types of AI platforms in order to prioritize content to instruct researchers.
• Participants will be able to describe different stations of the research cycle in order to determine what level of AI instruction to deliver.
• Participants will be able to articulate librarian expertise in education in order to successfully implement librarian interventions in research education.

Agenda

• Lecture on what is generative AI and different generative AI platforms that students are encountering in the health sciences at the presenters’ institutions ~30 minutes
• Break out into small groups to investigate different generative AI platforms. Discuss in the small groups ~20 minutes
• Presenters lecture on how librarians can be successfully integrated in research education on generative AI ~30 minutes
• Break out into small groups to investigate strategies for implementation in their own environment ~20 minutes
• Discussion with everyone in the group ~10 minutes
• Survey ~10 minutes

MLA CE Credits: 2