Your Information ZODIAC

Building on information evaluation mnemonics like the CRAAP Test, SIFT, and ACT UP, among others, the authors propose the ZODIAC of information evaluation for an AI-dominated information environment: Zooming in, Other opinions, Dataset, Intent, Authenticity, and Consistency. Each letter introduces students to considerations unique to the critical thinking considerations of AI-generated information, such as datasets and their large language models, evaluating the purpose of a given generative AI, and questioning the authenticity and consistency of generative AI output. Additionally, as an introductory framework geared toward first-year students, the ZODIAC evaluation method does not fully address all aspects of information literacy; social and environmental aspects of AI literacy are noticeably absent. Accordingly, the authors address social and environmental considerations in the discussion, which serves to inspire other information and AI literacy professionals to build a more holistic framework of evaluating AI-generated information.

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Publication Details

Journal
Journal of New Librarianship
Published
2025-12-09
DOI
https://doi.org/10.33011/newlibs/19/9
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00
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article

Your Information ZODIAC

Jessica Swaringen, Kevin J. Reagan, Kay Coates
Journal of New Librarianship
Teaching and Learning Programming
article

Your Information ZODIAC

Jessica Swaringen, Kevin J. Reagan, Kay Coates
article en

Abstract

Building on information evaluation mnemonics like the CRAAP Test, SIFT, and ACT UP, among others, the authors propose the ZODIAC of information evaluation for an AI-dominated information environment: Zooming in, Other opinions, Dataset, Intent, Authenticity, and Consistency. Each letter introduces students to considerations unique to the critical thinking considerations of AI-generated information, such as datasets and their large language models, evaluating the purpose of a given generative AI, and questioning the authenticity and consistency of generative AI output. Additionally, as an introductory framework geared toward first-year students, the ZODIAC evaluation method does not fully address all aspects of information literacy; social and environmental aspects of AI literacy are noticeably absent. Accordingly, the authors address social and environmental considerations in the discussion, which serves to inspire other information and AI literacy professionals to build a more holistic framework of evaluating AI-generated information.

Journal of New LibrarianshipVol. 10(2)
Georgia Southern University (US)
Openalex Percentile: Top 59%
Teaching and Learning Programming
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