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

Students’ Perspectives on the Ethical Use of Generative AI in Mathematics Learning: A Case Study

Kelly Angelly hevardani (Department of Mathematics, Universitas Negeri Padang, Padang, Indonesia)
Redy Williantama Zulhafendi (Department of Mathematics, Universitas Negeri Padang, Padang, Indonesia)



Article Info

Publish Date
23 Jan 2026

Abstract

The increasing integration of Generative AI tools into mathematics classrooms has transformed how students access explanations, solve problems, and receive feedback. While these technologies offer significant pedagogical benefits, their ethical implications from students’ perspectives remain underexplored. This study investigates students’ perceptions of the ethical use of Generative AI in secondary mathematics learning through a qualitative case study design. The research was conducted in a senior secondary school that has integrated AI-powered tools into classroom instruction and homework activities. Data were collected from 24 students through semi-structured interviews, focus group discussions, classroom observations, and analysis of AI-assisted learning artifacts. Thematic analysis revealed five major ethical dimensions perceived by students: (1) academic integrity and dependency risk, (2) fairness and unequal access, (3) transparency and trust in AI-generated solutions, (4) data privacy concerns, and (5) shifting responsibility in mathematical reasoning. Findings indicate that while students value AI for instant explanations and efficiency, they also express uncertainty about overreliance, authenticity of learning, and the credibility of AI outputs. Based on these findings, the study proposes student-informed ethical guidelines for responsible AI integration in mathematics learning. The results contribute to ongoing discussions on governance, digital literacy, and the pedagogical alignment of Generative AI in 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 ...