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Intelligent Teaching Design Assistant for Primary Mathematics: A Large Language Model-Driven Framework with Retrieval-Augmented Generation and Problem-Chain Pedagogy

Artigo2026

Danna Tang; Ran Ding; Meng He; Yushen Wang; Kaka Cheng

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Resumo

Primary mathematics education faces systemic challenges in translating curriculum reforms into classroom practice, exacerbated by teachers' cognitive overload and limited support for pedagogical innovation. This study develops an Intelligent Teaching Design Assistant grounded in socio-constructivist and cognitive load theories to address these challenges. Thirty-four primary mathematics teachers participated in a quasi-experimental study. The Intelligent Teaching Design Assistant integrates Large Language Models with multi-dimensional knowledge bases (curriculum standards, teaching strategies, student profiles) and a multi-agent architecture (process planner, student simulator). The Intelligent Teaching Design Assistant significantly outperformed generic Large Language Models, improving overall lesson plan quality. This work pioneers a replicable pathway for AI to empower teacher agency and advance 21st-century educational transformation.

Dados da obra

Tipo
Artigo
Periódico
International Electronic Journal of Mathematics Education
Ano
2026
Idioma
en
Palavras-chave
Elementary School Mathematics; Mathematics Education; Intelligent Tutoring Systems; Elementary School Teachers; Mathematics Teachers; Artificial Intelligence; Technology Uses in Education; Program Effectiveness; Usability; Value Judgment
Temas
Currículo, Práticas Pedagógicas
Acesso
Download disponível
Fontes
ERIC — Education Resources Information Center
Na Biblioteca desde
01/10/2026 · verificada em 03/10/2026

Como citar

ABNT
TANG, Danna et al.. Intelligent Teaching Design Assistant for Primary Mathematics: A Large Language Model-Driven Framework with Retrieval-Augmented Generation and Problem-Chain Pedagogy. International Electronic Journal of Mathematics Education, 2026. Disponível em: https://eric.ed.gov/?id=EJ1505528. Acesso em: 5 nov. 2026.

APA

Tang, D., Ding, R., He, M., Wang, Y., & Cheng, K. (2026). Intelligent Teaching Design Assistant for Primary Mathematics: A Large Language Model-Driven Framework with Retrieval-Augmented Generation and Problem-Chain Pedagogy. International Electronic Journal of Mathematics Education. https://eric.ed.gov/?id=EJ1505528

BibTeX
@article{tang2026,
  author = {Tang, Danna and Ding, Ran and He, Meng and Wang, Yushen and Cheng, Kaka},
  title = {Intelligent Teaching Design Assistant for Primary Mathematics: A Large Language Model-Driven Framework with Retrieval-Augmented Generation and Problem-Chain Pedagogy},
  year = {2026},
  journal = {International Electronic Journal of Mathematics Education},
  url = {https://eric.ed.gov/?id=EJ1505528},
  language = {en}
}
RIS
TY  - JOUR
AU  - Tang, Danna
AU  - Ding, Ran
AU  - He, Meng
AU  - Wang, Yushen
AU  - Cheng, Kaka
TI  - Intelligent Teaching Design Assistant for Primary Mathematics: A Large Language Model-Driven Framework with Retrieval-Augmented Generation and Problem-Chain Pedagogy
PY  - 2026
JO  - International Electronic Journal of Mathematics Education
UR  - https://eric.ed.gov/?id=EJ1505528
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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