Analysing Mathematical Communication between Pre-Service Mathematics Teachers and GenAI: A Case Study in Abstract Algebra Course
Elah Nurlaelah, Tia Purniati, Bill Chairy Rizky Bustaren, I Made Suarsana, Made Juniantari, Irianto Irianto
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Source: Crossref
Published: Oct 20, 2026
DOI: 10.12688/f1000research.190994.1
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Background The emergence of Generative Artificial Intelligence (GenAI), particularly ChatGPT, offers new possibilities for mathematics learning in higher education. Although ChatGPT can provide explanations, examples, guiding questions, and feedback, its use in Abstract Algebra courses has largely been limited to answering questions and verifying mathematical answers or proofs. This study analyses pre-service mathematics teachers’ mathematical communication when interacting with ChatGPT through seven indicators, including: interpreting formal definitions; using mathematical terms, symbols, variables, and notation appropriately; constructing examples, non-examples, and counter-examples; explaining relationships between algebraic objects and their properties; justifying arguments or proofs; evaluating the validity of mathematical responses; and formulating coherent conclusions. Method A qualitative case study involved 18 pre-service mathematics teachers enrolled in an Abstract Algebra course in the department of mathematics education at a public university in Bandung City, West Java, Indonesia. Data comprised written dialogues between the pre-service mathematics teachers and ChatGPT while solving Abstract Algebra problems and were analysed using the seven indicators. Results The findings indicate that the pre-service mathematics teachers’ mathematical communication generally ranged from developing to adequate. They performed relatively well in using terminology and notation, constructing examples or counter-examples, and explaining relationships among algebraic objects and properties. However, justification, critical evaluation of ChatGPT responses, and independent conclusion-making remained weak. While some pre-service mathematics teachers accepted inaccurate AI responses, others identified and connected them. Conclusion The findings suggest that GenAI should serve as a dialogue partner and scaffolding, rather than an authority on mathematical truth. Mathematics course should emphasise verification, justification, critical evaluation, and argument reconstruction to foster independent mathematical communication skills.
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