Journal of Applied Artificial Intelligence in Education
Vol 1, No 2 (2026): January 2026

Affective Drivers and Ethical Concerns Shaping AI Use Among University Students

Nabilah Auliah Rahman (Universitas Negeri Makassar)
Melda Auliyah Zakina (Universitas Negeri Makassar)
Aprilianti Nirmala S (Universitas Negeri Makassar)
Saipul Abbas (Sunchon National University)



Article Info

Publish Date
20 Jan 2026

Abstract

The rapid growth of artificial intelligence (AI) use in higher education raises concerns about how students’ emotional states and the quality of their interactions with AI shape both affective engagement and ethical awareness in academic contexts. This study aims to examine the effects of emotional well-being, AI credibility, and AI interaction quality on students’ ethical awareness, with affective engagement positioned as a mediating mechanism. A quantitative cross-sectional survey was administered to higher education students who use AI tools for academic activities, and the proposed relationships were tested using PLS-based structural modeling with bootstrapping procedures. The findings indicate that emotional well-being (β = 0.549, p < 0.001) and AI interaction quality (β = 0.420, p < 0.001) significantly enhance affective engagement, whereas AI credibility shows no significant effect (β = –0.045, p = 0.342). Affective engagement has a significant positive influence on ethical awareness (β = 0.597, p < 0.001) and significantly mediates the effects of emotional well-being and interaction quality on ethical awareness, while no indirect effect is observed for AI credibility. Overall, these results imply that ethical awareness in student AI use is fostered more strongly through emotionally supportive experiences and high-quality human–AI interactions than through credibility perceptions alone, underscoring the need for human-centered AI integration and ethics-oriented guidance in higher education

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Journal Info

Abbrev

JAAIE

Publisher

Subject

Computer Science & IT Education

Description

Applied AI in Classroom Practice, exploring practical classroom implementations such as smart content delivery, AI-powered virtual assistants, and automated learning support tools. Intelligent Tutoring Systems, focusing on adaptive AI-driven systems that personalize instruction based on individual ...