Author Information
Lee Sassanapitax, Burapha University, ThailandTrai Unyapoti, Srinakharinwirot University, Thailand
Tanakorn Puraram, Chulalongkorn University, Thailand
Thanida Sujarittham, Bansomdejchaopraya Rajabhat University, Thailand
Abstract
This study investigated undergraduate students’ attitudes toward the integration of Generative Artificial Intelligence (Generative AI) as a Peer Instruction (PI) tool in an Abstract Algebra course at a university in Thailand. Guided by the TPACK framework and the Technology Acceptance Model (TAM), the study employed a quantitative survey design. The participants were two groups of students—teacher education and science students—totaling 69 individuals enrolled in the course during the first semester of the 2025 academic year. Over a three-week intervention, Generative AI served as a “peer-like learning assistant,” providing conceptual explanations, worked examples, and step-by-step reasoning to support engagement with abstract mathematical concepts. Data were collected via a validated questionnaire measuring demographics and attitudes across four dimensions: cognitive, affective, behavioral, and perceptions of AI’s peer-instruction role. The results showed that students held a high overall level of positive attitudes toward using Generative AI as a Peer Instructor (M = 4.03, SD = 0.51, on a 5-point scale). All four dimensions—role perception, cognitive understanding, behavioral engagement, and affective motivation—showed consistently high mean scores. The overall attitude level was significantly higher than the benchmark for a high level (3.55; t(65) = 7.74, p < .001). These findings suggest that Generative AI effectively supported conceptual understanding, enhanced motivation, and fostered peer-like interaction in line with Peer Instruction principles. The study highlights the potential of integrating Generative AI to strengthen active learning in mathematically demanding courses.
Paper Information
Conference: ACSS2026Stream: Teaching and Learning
This paper is part of the ACSS2026 Conference Proceedings (View)
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To cite this article:
Sassanapitax L., Unyapoti T., Puraram T., & Sujarittham T. (2026) Undergraduate Students’ Attitudes Toward the Use of Generative AI as Peer Instruction in an Abstract Algebra Course ISSN: 2186-2303 – The Asian Conference on the Social Sciences 2026: Official Conference Proceedings (pp. 583-596) https://doi.org/10.22492/issn.2186-2303.2026.46
To link to this article: https://doi.org/10.22492/issn.2186-2303.2026.46
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