Interrupting Generative AI in LIS: Using Analog, Project-Based, In-Class, Team Work to Validate Core Research Competency Learning
Generative AI is a powerful tool that we should be teaching our students to harness. At the same time, we must ensure that our students can perform core research tasks such as finding, reading, summarizing, and synthesizing academic research, in keeping with ALA Core Competency 7A. Because generative AI produces imperfect, college-level writing that can be difficult to identify as non-human, instructors face a new challenge in validating that students have learned 7A’s search-summarize-synthesize skills. One solution is the use of analog, scaffolded, in-class research skills activities accompanied by immediate instructor validation and feedback. This paper presents a 20-part literature review assignment as an example. This example demonstrates that when we watch our students reading, annotating, discussing, and mind mapping journal articles, we can be sure that they are learning the skills that will enable them to leverage tools like generative AI as a bridge to advanced work.
Authors
- Sarah Ryan (ORCID: https://orcid.org/0000-0003-3025-8574)
Institutions
- University of North Texas (US)
Publication Details
- Journal
- Proceedings of the ALISE Annual Conference
- Published
- 2024-10-16
- DOI
- https://doi.org/10.21900/j.alise.2024.1685
- Primary Topic
- Occupational Health and Safety Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00