Integrating Chat-GPT in the Classroom: A Study on Linear Algebra Learning in Higher Education

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.