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Undergraduate Students’ Attitudes Toward the Use of Generative AI as Peer Instruction in an Abstract Algebra Course (106997)

Session Information: Teaching and Learning
Session Chair: Dana Badau

Monday, 11 May 2026 18:15
Session: Session 5
Room: Room G407 (4F)
Presentation Type: Oral Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

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.

Authors:
Lee Sassanapitax, Chulalongkorn University, Thailand
Trai Unyapoti, Srinakharinwirot University, Thailand
Tanakorn Puraram, Chulalongkorn University, Thailand
Thanida Sujarittham, Bansomdejchaopraya Rajabhat University, Thailand


About the Presenter(s)
Dr. Trai Unyapoti is currently a lecturer of Department of Curriculum and Instruction, Faculty of Education, Srinakharinwirot University, Thailand.
Dr. Trai Unyapoti has expertise in physics education.

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Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00