IJIET 2025 Vol.15(4): 732-751
doi: 10.18178/ijiet.2025.15.4.2279
doi: 10.18178/ijiet.2025.15.4.2279
Integrating Chat-GPT in the Classroom: A Study on Linear Algebra Learning in Higher Education
Dilham Fardian1,2, Didi Suryadi1,2,*, Sufyani Prabawanto1,2, and Al Jupri1,
1. Department of Mathematics Education, Faculty of Mathematics and Natural Sciences Education,
Universitas Pendidikan Indonesia, Indonesia
2. Indonesian Didactical Design Research Development Center (PUSBANGDDRINDO), Universitas Pendidikan Indonesia, Indonesia
Email: dilhamfardian@upi.edu (D.F.); didisuryadi@upi.edu (D.S.); sufyani@upi.edu (S.P.); aljupri@upi.edu (A.J.)
*Corresponding author
2. Indonesian Didactical Design Research Development Center (PUSBANGDDRINDO), Universitas Pendidikan Indonesia, Indonesia
Email: dilhamfardian@upi.edu (D.F.); didisuryadi@upi.edu (D.S.); sufyani@upi.edu (S.P.); aljupri@upi.edu (A.J.)
*Corresponding author
Manuscript received September 13, 2024; revised October 14, 2024; accepted December 14, 2024; published April 15, 2025
Abstract—The transition to higher education often presents considerable challenges for students in mastering linear algebra, particularly due to its abstract nature and increased complexity compared to secondary education curricula. Chat Generative Pre-trained Transformer (Chat-GPT) has the potential to mitigate these challenges by providing tailored support that enhances students’ conceptual understanding. This research aims to investigate the integration of Chat-GPT as a supplementary educational tool to enhance linear algebra learning experience. Study participants included mathematics education students aged 20–23 in three Indonesian universities who had completed an elementary linear algebra course. The study employed both quantitative and qualitative methodologies. Quantitatively, this study utilized a quasi-experimental design and a meta-analysis. The experimental groups included students who received instructions solely through Chat-GPT and those in which Chat-GPT was used in conjunction with a mathematics expert. The Chat-GPT version 3.5 was used for the experimental groups, while the control group was taught using conventional instructional methods. Qualitatively, hermeneutic phenomenology was used to understand students’ perspectives on technology in education. The findings indicated that Chat- GPT can provide step-by-step explanations for solving math problems and make mathematics learning more engaging and accessible. Although technology represents a valuable asset in enriching the educational experience, educators’ roles as a facilitator, elucidator, and guide remains indispensable. Therefore, it is recommended that Chat-GPT be used in education primarily for teaching fundamental concepts, while instructors remain heavily involved in explaining more abstract linear algebra concepts.
Keywords—Analysis of Variance (ANOVA), Artificial Intelligence (AI), Chat-GPT, meta-analysis, phenomenology
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—Analysis of Variance (ANOVA), Artificial Intelligence (AI), Chat-GPT, meta-analysis, phenomenology
Cite: Dilham Fardian, Didi Suryadi, Sufyani Prabawanto, and Al Jupri, "Integrating Chat-GPT in the Classroom: A Study on Linear Algebra Learning in Higher Education," International Journal of Information and Education Technology, vol. 15, no. 4, pp. 732-751, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).