Bridging Pedagogy and AI: A Systematic Review of Deep Learning in Mathematics Education

Artigo2025

Valeria Yekti Kwasaning Gusti; Fitria Amastini

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Resumo

Deep learning is interpreted differently in educational and computational contexts. The purpose of this study is to systematically examine how deep learning is conceptualized and applied in mathematics education research, and to evaluate the extent to which these applications align with the Indonesian Ministry of Education and Culture’s (Kemendikbud) definition of deep learning. A systematic literature review (SLR) was conducted using PRISMA guidelines. Searches in ScienceDirect, Scopus, Springer Link, and ProQuest produced 1,881 records containing the term “deep learning,’” published between 2015 and 2025. After duplicate removal and screening, 16 peer-reviewed journal articles explicitly addressing deep learning in mathematics education were included. Two main interpretations were found. Eleven studies framed deep learning pedagogically, focusing on conceptual understanding, problem-solving, collaborative learning, and real-world application. Five studies adopted a computational framing, using deep neural networks and other machine learning techniques for prediction, error analysis, adaptive instruction, and automated feedback. While the majority aligned with Kemendikbud’s pedagogical emphasis, some studies treated deep learning purely as a technical method, without explicit links to student-centered outcomes. The review highlights a conceptual gap between pedagogical and computational uses of deep learning in mathematics education. Bridging this gap requires interdisciplinary collaboration between educators and technology developers to ensure technological applications support meaningful learning. The findings provide a reference for aligning global research on deep learning with national education policy, ensuring relevance for curriculum design and classroom practice.

Dados da obra

Tipo
Artigo
Periódico
Jurnal Pendidikan Matematika (JPM), v. 11, n. 2, p. 141-156
Editora
Department of Mathematics Education, Faculty of Teacher Training and Education, Universitas Islam Malang
Ano
2025 (2025-11)
Idioma
en
Palavras-chave
deep learning; mathematics education; technology developer; artificial intelligence
Temas
Currículo, Práticas Pedagógicas, Resolução de Problemas
DOI
10.33474/jpm.v11i2.24319
ISSN
2442-4668, 2656-4564
Acesso
Acesso aberto
Fontes
DOAJ — Directory of Open Access Journals
Na Biblioteca desde
01/10/2026 · verificada em 03/10/2026

Como citar

ABNT
GUSTI, Valeria Yekti Kwasaning; AMASTINI, Fitria. Bridging Pedagogy and AI: A Systematic Review of Deep Learning in Mathematics Education. Jurnal Pendidikan Matematika (JPM), v. 11, n. 2, p. 141-156, 2025. DOI: https://doi.org/10.33474/jpm.v11i2.24319.

APA

Gusti, V. Y. K., & Amastini, F. (2025). Bridging Pedagogy and AI: A Systematic Review of Deep Learning in Mathematics Education. Jurnal Pendidikan Matematika (JPM), 11(2), 141-156. https://doi.org/10.33474/jpm.v11i2.24319

BibTeX
@article{gusti2025,
  author = {Gusti, Valeria Yekti Kwasaning and Amastini, Fitria},
  title = {Bridging Pedagogy and AI: A Systematic Review of Deep Learning in Mathematics Education},
  year = {2025},
  journal = {Jurnal Pendidikan Matematika (JPM)},
  volume = {11},
  number = {2},
  pages = {141-156},
  publisher = {Department of Mathematics Education, Faculty of Teacher Training and Education, Universitas Islam Malang},
  doi = {10.33474/jpm.v11i2.24319},
  language = {en}
}
RIS
TY  - JOUR
AU  - Gusti, Valeria Yekti Kwasaning
AU  - Amastini, Fitria
TI  - Bridging Pedagogy and AI: A Systematic Review of Deep Learning in Mathematics Education
PY  - 2025
JO  - Jurnal Pendidikan Matematika (JPM)
VL  - 11
IS  - 2
SP  - 141
EP  - 156
DO  - 10.33474/jpm.v11i2.24319
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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