From Hallucination to Critical Thinking: Developing an AI-MIL Framework in Korean School Libraries

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Kim, Eunhyun
Kim, Seohyun

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International Federation of Library Associations and Institutions (IFLA)

Abstract

When students accept ChatGPT's answers uncritically, AI hallucination silently erodes the foundation of learning. But what if that very hallucination could become a powerful teaching tool for critical thinking? As generative AI reshapes information seeking, information literacy has shifted from "finding information" to "designing questions and verifying AI-generated answers." Yet existing instructional models have not caught up. Six school librarians from six Korean high schools collaboratively developed the AI-MIL (Artificial Intelligence–Media and Information Literacy) Framework, redesigning the traditional Big6 model by integrating UNESCO MIL competencies and Computational Thinking. In school library sessions, students progressively refined their prompts through a Question Continuum model and directly detected hallucinations and biases in AI outputs using the SIFT strategy—turning verification itself into a vehicle for critical thinking. Where empirical evidence of generative AI literacy education in K–12 school libraries remains globally scarce, a pilot study with 33 students (32 completing both surveys) using paired t-tests confirmed significant improvements in search strategy (p=.015) and evaluation skills (p=.021). Students demonstrated habitual cross-verification and evidence-demanding behaviours. Designed to ensure equitable AI literacy regardless of socioeconomic context, this framework offers a scalable, ready-to-implement model for school libraries...

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