Promoting AI literacy through U.S. academic libraries: an analysis of LibGuides from ARL and Oberlin group libraries using the EDUCAUSE AI literacy framework

Introduction. As the integration of artificial intelligence (AI) rapidly advances, academic libraries are increasingly pivotal in supporting AI literacy among students and faculty. Method. Through content analysis, the present study examines 70 newly developed generative AI LibGuides from academic libraries affiliated with the association of research libraries (ARL) and the Oberlin group, using the EDUCAUSE AI literacy framework. Analysis. Through a detailed examination, the present research reorganizes and improves the EDUCAUSE AI literacy framework, proposing a more comprehensive version tailored to higher education needs. The adapted framework fills the gaps in the original model and offers a nuanced approach to AI literacy, reflecting the unique challenges faced by academic libraries. Results. The findings reveal that most LibGuides emphasize foundational AI tools and responsible use, with less focus on advanced technical competencies related to AI creation. Significant differences were observed between ARL and Oberlin Group LibGuides, with ARL offering more comprehensive coverage. To address these differences, consistent training and knowledge sharing initiatives are recommended to ensure a common standard of AI literacy support across academic libraries. Conclusion. This study provides insights into the role of libraries in promoting generative AI literacy and identifies areas for future strategic partnerships and improvement.

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Publication Details

Journal
Information Research an international electronic journal
Published
2025-03-11
DOI
https://doi.org/10.47989/ir30iconf47182
Citations
12
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
20.32
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article

Promoting AI literacy through U.S. academic libraries: an analysis of LibGuides from ARL and Oberlin group libraries using the EDUCAUSE AI literacy framework

Rong Tang, Ko Chun Ru
12 citations
Information Research an international electronic journal
Online Learning and Analytics
20.32
article

Promoting AI literacy through U.S. academic libraries: an analysis of LibGuides from ARL and Oberlin group libraries using the EDUCAUSE AI literacy framework

Rong Tang, Ko Chun Ru
article en
12 citations

Abstract

Introduction. As the integration of artificial intelligence (AI) rapidly advances, academic libraries are increasingly pivotal in supporting AI literacy among students and faculty. Method. Through content analysis, the present study examines 70 newly developed generative AI LibGuides from academic libraries affiliated with the association of research libraries (ARL) and the Oberlin group, using the EDUCAUSE AI literacy framework. Analysis. Through a detailed examination, the present research reorganizes and improves the EDUCAUSE AI literacy framework, proposing a more comprehensive version tailored to higher education needs. The adapted framework fills the gaps in the original model and offers a nuanced approach to AI literacy, reflecting the unique challenges faced by academic libraries. Results. The findings reveal that most LibGuides emphasize foundational AI tools and responsible use, with less focus on advanced technical competencies related to AI creation. Significant differences were observed between ARL and Oberlin Group LibGuides, with ARL offering more comprehensive coverage. To address these differences, consistent training and knowledge sharing initiatives are recommended to ensure a common standard of AI literacy support across academic libraries. Conclusion. This study provides insights into the role of libraries in promoting generative AI literacy and identifies areas for future strategic partnerships and improvement.

Information Research an international electronic journalVol. 30(iConf)
National Taiwan Normal University (TW), Simmons University (US)
Openalex Percentile: Top 1%
Online Learning and Analytics
20.32
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