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.

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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
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article

Interrupting Generative AI in LIS: Using Analog, Project-Based, In-Class, Team Work to Validate Core Research Competency Learning

Sarah Ryan
Proceedings of the ALISE Annual Conference
Occupational Health and Safety Research
article

Interrupting Generative AI in LIS: Using Analog, Project-Based, In-Class, Team Work to Validate Core Research Competency Learning

Sarah Ryan
article en

Abstract

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.

Proceedings of the ALISE Annual Conference
University of North Texas (US)
Quality Education
Openalex Percentile: Top 73%
Occupational Health and Safety Research
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