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LLMs as useful training tools for mathematics teachers: opportunities or hallucinations?

Artigo2026

Ulrich Kortenkamp ORCID; Kevin Larkin ORCID

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Resumo

Abstract We explore the extent to which answers to mathematics word problems generated by AI chatbots are comparable to students’ answers, and whether interaction with them is useful for replicating classroom discourse. We use a large language model (LLM) to solve ten standard textbook exercises 100 times for each question and analyse the answers to identify tasks suitable for further interaction through teacher prompts. Based on this analysis, we derive suitable teacher interventions, in the form of follow-up prompts, and determine their impact on the LLM output. We show that LLM-generated answers can indeed resemble students’ answers and argue that these answers can be used with preservice educators as they learn to intervene productively in student learning. However, we also found that generic follow-up prompts can be more effective than specific prompts based on pedagogical content knowledge in generating a correct LLM response. Taken together, these findings suggest that LLMs may be well suited to modelling students’ mathematical solutions, but less suited to modelling how students naturally respond to instructional prompts. This sheds light on the suitability of LLM training in teacher education, but also on modern reasoning models that can improve the reliability of LLM answers.

Dados da obra

Tipo
Artigo
Periódico
ZDM, v. 58, n. 5, p. 1011-1026
Editora
Springer Science+Business Media
Ano
2026 (2026-07-07)
Idioma
en
Palavras-chave
large language models; mathematical word problems; teacher professional development; pre-service teachers; classroom discourse; teacher intervention; pedagogical content knowledge; AI chatbots; reasoning models
Temas
Formação de Professores de Matemática
DOI
10.1007/s11858-026-01813-4
ISSN
1615-679X, 1863-9690, 1863-9704
Licença
cc-by
Acesso
Acesso aberto
Fontes
OpenAlex
Na Biblioteca desde
01/10/2026 · verificada em 03/10/2026

Como citar

ABNT
KORTENKAMP, Ulrich; LARKIN, Kevin. LLMs as useful training tools for mathematics teachers: opportunities or hallucinations?. ZDM, v. 58, n. 5, p. 1011-1026, 2026. DOI: https://doi.org/10.1007/s11858-026-01813-4.

APA

Kortenkamp, U., & Larkin, K. (2026). LLMs as useful training tools for mathematics teachers: opportunities or hallucinations?. ZDM, 58(5), 1011-1026. https://doi.org/10.1007/s11858-026-01813-4

BibTeX
@article{kortenkamp2026,
  author = {Kortenkamp, Ulrich and Larkin, Kevin},
  title = {LLMs as useful training tools for mathematics teachers: opportunities or hallucinations?},
  year = {2026},
  journal = {ZDM},
  volume = {58},
  number = {5},
  pages = {1011-1026},
  publisher = {Springer Science+Business Media},
  doi = {10.1007/s11858-026-01813-4},
  language = {en}
}
RIS
TY  - JOUR
AU  - Kortenkamp, Ulrich
AU  - Larkin, Kevin
TI  - LLMs as useful training tools for mathematics teachers: opportunities or hallucinations?
PY  - 2026
JO  - ZDM
VL  - 58
IS  - 5
SP  - 1011
EP  - 1026
DO  - 10.1007/s11858-026-01813-4
LA  - en
ER  -

Referência gerada automaticamente a partir dos metadados das fontes; confira com o documento original. Baixar BibTeX · Baixar RIS

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