Generative AI Literacy, Ethical Awareness, and Its Role in Supporting University Adaptation

Main Article Content

Natarpha Satchawatee
https://orcid.org/0000-0003-2925-9633
Pornpichit Phosri

Abstract

The rapid proliferation of Generative Artificial Intelligence (GenAI) necessitates a strategic understanding of its impact on higher education. This study investigates GenAI literacy, ethical awareness, and the perceived role of AI in supporting university adaptation among 525 first-year undergraduate students at Mahasarakham University. Using a quantitative survey grounded in the AI Literacy Framework and the Technology Acceptance Model (TAM), the study evaluates technical proficiency, critical evaluation skills, and perceived benefits across academic and psychological dimensions.Contrary to conventional assumptions, the comparative analysis revealed no statistically significant differences between students in Science and Technology disciplines and those in Social Sciences and Humanities (all p > 0.05$, Cohen's d < 0.15$), suggesting the widespread adoption of GenAI across academic fields. Furthermore, Pearson correlation analysis demonstrated strong positive relationships between AI literacy and university adaptation (r = 0.647, p < 0.001), as well as between ethical awareness and university adaptation (r = 0.646, p < 0.001). Notably, the only significant disciplinary difference was observed at the item level, where Science and Technology students reported greater concern regarding cognitive atrophy resulting from excessive reliance on AI (t = 2.778, p = 0.006). These findings suggest that students with higher levels of AI competency and stronger ethical awareness perceive greater adaptive benefits from GenAI tools. The results further indicate that universities should prioritize AI literacy and ethics education as a universal component of General Education curricula.

Article Details

How to Cite
Satchawatee, N., & Phosri, P. (2026). Generative AI Literacy, Ethical Awareness, and Its Role in Supporting University Adaptation. Journal of Applied Informatics and Technology, 265464. retrieved from https://ph01.tci-thaijo.org/index.php/jait/article/view/265464
Section
Research Article

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