From privacy concerns to digital literacies: negotiating trust and authenticity in AI-mediated student records systems
DOI:
https://doi.org/10.47989/ir31iConf64208Keywords:
Privacy literacy, AI-mediated student records systems, AI trust, Digital inclusion, APCO modelAbstract
Introduction. This study examines how students negotiate privacy concerns in AI-mediated student record systems, focusing on Xuexin.com, China’s national digital archive of university student records. Using the antecedent–privacy concern–outcome (APCO) model, privacy practices are framed as forms of information literacy tied to authenticity, trust, and digital inclusion.
Method. Semi-structured interviews were conducted with fifteen students and recent graduates (aged 20–27) between May and July 2025. Interviews lasted 30–60 minutes, face-to-face or online, guided by APCO categories while allowing emergent themes.
Analysis. Directed content analysis with NVivo was applied. APCO codes were refined to include themes of algorithmic opacity, fragile trust, and resistance. Reliability was checked by re-coding 20% of transcripts.
Results. Four antecedents (breaches, literacy, risk, and trust) shaped behaviours from reluctant compliance to withdrawal. Privacy literacy emerged as unevenly distributed, with implications for authenticity and digital inclusion.
Conclusion. Privacy in digital student records systems is best understood as a fragile, uneven literacy practice. Its unequal distribution risks deepening exclusion, raising questions about authenticity, trust, and the conditions for a digitally enlightened society.
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Copyright (c) 2026 Yang Lu , Yunjie Tang , Yijia Song
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