AI Dilemma in Schoolwork: Student Anxiety and Fairness Perceptions in AI Schoolwork Accusations

Abstract

This qualitative study explored senior high school students’ experiences of anxiety and perceptions of fairness when accused of using Artificial Intelligence (AI) tools in their academic work. Sixteen students from both public and private schools were purposively selected to provide in-depth insights into the emotional, cognitive, and social implications of AI-related accusations. Data were collected through semi-structured interviews and analyzed thematically to identify recurring patterns and experiences. Findings revealed that students experienced intense shock, disbelief, anxiety, and self-doubt upon being accused of AI-assisted work. These emotional responses often led to decreased academic confidence, reduced motivation, heightened self-consciousness, and perfectionism, affecting their engagement and approach to learning. Regarding fairness, participants reported concerns about the lack of transparency, inconsistent application of rules, and minimal involvement in verification processes, which contributed to feelings of injustice and diminished trust in educational institutions. Students recommended clear communication, inclusion in discussions, and the use of reliable, multi-method verification approaches to ensure procedural fairness and mitigate anxiety. The study highlights the complex interplay between AI integration, academic integrity, and student well-being. It underscores the importance of transparent policies, supportive faculty communication, and AI literacy programs to promote both ethical AI use and psychological safety in educational settings. The results provide valuable implications for educators, administrators, and policymakers seeking to balance academic accountability with students’ emotional and cognitive needs in the evolving landscape of AI-assisted learning.

Keywords: Artificial Intelligence (AI), Student Anxiety, Fairness Perceptions AI-Related Accusations

DOI: 10.7176/JEP/16-11-01

Publication date: October 30th 2025