Enhancing Aigc credibility assessment in higher education

An extended framework integrating user trust, AI literacy, and behavioral adoption

Bibliographic Data

ID21632707
AuthorsJian Teng (0000-0003-1876-989X, Lingnan Normal University), Sukyoung Cho (Sehan University, corresponding author)
Year2026
Pages1-17
Publication date2026-06-17
Open AccessNo
TypeARTICLE
VenueInteractive Learning Environments (JOURNAL)
Journal identifiersISSN: 1049-4820 • E-ISSN: 1744-5191
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/10494820.2026.2676667
OpenAlexW7165024498
LanguageEN
References cited45

This study extends the foundational work of Cui and Zhang (2025. Can student accurately identify artificial intelligence generated content? An exploration of AIGC credibility from user perspective in education. Education and Information Technologies, 30 (12), 16321–16346. https://doi.org/10.1007/s10639-025-13448-1) by examining AI-generated content (AIGC) credibility assessment among 286 higher education students across three Chinese universities. Employing an extended Technology Acceptance Model (TAM) framework integrated with AI literacy and critical thinking constructs, we investigated factors influencing students’ ability to distinguish AIGC from human-created content. Results revealed that participants achieved 68.4% accuracy in general AIGC recognition but only 57.9% for domain-specific content. Structural equation modelling demonstrated that perceived usefulness (β = .44) and ease of use (β = .31) significantly predicted attitudes towards AIGC (R2 = .72), while interpretability (β = .63) and ease of use (β = .29) explained 91% of variance in AI illusion. AI literacy mediated the relationship between perceived usefulness and attitudes (β indirect = .07, p = .008), while critical thinking mediated the perceived ease of use–AI illusion pathway (β indirect = −.05, p = .024). These findings inform the development of comprehensive training programs for appropriate AIGC credibility assessment and trust calibration in educational contexts

Credibility · Electronic learning · Higher education · Mobile device · Technology integration · Usability · Educational Strategies and Epistemologies · Intelligent Tutoring Systems and Adaptive Learning · Misinformation and Its Impacts

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