Analysing Mathematical Communication between Pre-Service Mathematics Teachers and GenAI: A Case Study in Abstract Algebra Course

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.

Authors

Institutions

Publication Details

Journal
F1000Research
Published
2026-10-20
DOI
https://doi.org/10.12688/f1000research.190994.1
Primary Topic
Mathematics Education and Teaching Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysing Mathematical Communication between Pre-Service Mathematics Teachers and GenAI: A Case Study in Abstract Algebra Course

Elah Nurlaelah, Tia Purniati, Bill Chairy Rizki Bustaren, Made Juniantari et al.
F1000Research
Mathematics Education and Teaching Techniques
article

Analysing Mathematical Communication between Pre-Service Mathematics Teachers and GenAI: A Case Study in Abstract Algebra Course

Elah Nurlaelah, Tia Purniati, Bill Chairy Rizki Bustaren, Made Juniantari, I Made Suarsana, Irianto Irianto
article en

Abstract

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.

F1000ResearchVol. 15
Indonesia University of Education (ID), Universitas Pendidikan Ganesha (ID)
Openalex Percentile: Top 3%
Mathematics Education and Teaching Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.