From credibility to reliance

Trust in generative AI as an academic information source

Bibliographic Data

ID21501138
AuthorsSanjaya Pudasaini (0009-0009-9914-0372, Kathmandu University School of Management (KUSOM), Lalitpur, Nepal, corresponding author)
Year2026
Publication date2026-07-09
Open AccessYes
TypeARTICLE
VenueInformation Development (JOURNAL)
Journal identifiersISSN: 0266-6669 • E-ISSN: 1741-6469
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/02666669261468286
OpenAlexW7167794733
LanguageEN
References cited42

Generative AI is increasingly used by students as a source of academic information, yet less is known about how they judge, verify, and rely on AI-generated content. Grounded in Source Credibility Theory and informed by information literacy and digital verification perspectives, this study examines associations among perceived credibility, trust, verification behaviour, and reliance. Survey data from 650 undergraduate and postgraduate students across four universities in Nepal were analysed using covariance-based structural equation modelling. Perceived credibility was positively associated with trust, while trust and verification behaviour were positively associated with reliance. The direct association between perceived credibility and reliance was not significant after trust was included, whereas the indirect association through trust was significant. Because the data are cross-sectional, this pattern is interpreted as an indirect association rather than causal mediation. The study positions generative AI as an academic information source requiring credibility judgement, verification, and cautious academic incorporation

Credibility · Generative grammar · Generative model · Information literacy · Source credibility · Structural equation modeling · Educational Strategies and Epistemologies · Misinformation and Its Impacts · Social Media and Politics

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