Twenty Years of Research on Technology in Mathematics Education at CERME: A Literature Review Based on a Data Science Approach

Artigo2023

Jonas Dreyøe Herfort ORCID; Andreas Lindenskov Tamborg ORCID; Florian Meier ORCID; Benjamin Brink Allsopp ORCID; Morten Misfeldt ORCID

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Resumo

Mathematics education is like many scientific disciplines witnessing an increase in scientific output. Examining and reviewing every paper in an area in detail are time-consuming, making comprehensive reviews a challenging task. Unsupervised machine learning algorithms like topic models have become increasingly popular in recent years. Their ability to summarize large amounts of unstructured text into coherent themes or topics allows researchers in any field to keep an overview of state of the art by creating automated literature reviews. In this article, we apply topic modeling in the context of mathematics education and showcase the use of this data science approach for creating literature reviews by training a model of all papers (n = 336) that have been presented in Thematic Working Groups related to technology in the first eleven Congresses of the European Society for Research in Mathematics Education (CERME). We guide the reader through the stepwise process of training a model and give recommendations for best practices and decisions that are decisive for the success of such an approach to a literature review. We find that research in this period revolved around 25 distinct topics that can be grouped into four clusters: digital tools, teachers and their resources, technology experimentation, and a diverse cluster with a strong focus on student activity. Finally, a temporal analysis of these topics reveals a correlation between technology trends and research focus, allowing for reflection on future research in the field.

Dados da obra

Tipo
Artigo
Periódico
Educational Studies in Mathematics, v. 112, n. 2, p. 309-336
Editora
Springer Science+Business Media
Ano
2023 (2023-01-04)
Idioma
en
Palavras-chave
Mathematics Education; Technology Uses in Education; Artificial Intelligence; Algorithms; Models; Training; Data Science; Best Practices; technology in mathematics education; topic modeling; literature review automation; digital tools; teacher resources; technology experimentation; student activity; research trends
DOI
10.1007/s10649-022-10202-z
ISSN
0013-1954, 1573-0816
Licença
other-oa
Acesso
Acesso aberto
Fontes
ERIC — Education Resources Information Center; OpenAlex
Na Biblioteca desde
01/10/2026 · verificada em 03/10/2026

Como citar

ABNT
HERFORT, Jonas Dreyøe et al.. Twenty Years of Research on Technology in Mathematics Education at CERME: A Literature Review Based on a Data Science Approach. Educational Studies in Mathematics, v. 112, n. 2, p. 309-336, 2023. DOI: https://doi.org/10.1007/s10649-022-10202-z.

APA

Herfort, J. D., Tamborg, A. L., Meier, F., Allsopp, B. B., & Misfeldt, M. (2023). Twenty Years of Research on Technology in Mathematics Education at CERME: A Literature Review Based on a Data Science Approach. Educational Studies in Mathematics, 112(2), 309-336. https://doi.org/10.1007/s10649-022-10202-z

BibTeX
@article{herfort2023,
  author = {Herfort, Jonas Dreyøe and Tamborg, Andreas Lindenskov and Meier, Florian and Allsopp, Benjamin Brink and Misfeldt, Morten},
  title = {Twenty Years of Research on Technology in Mathematics Education at CERME: A Literature Review Based on a Data Science Approach},
  year = {2023},
  journal = {Educational Studies in Mathematics},
  volume = {112},
  number = {2},
  pages = {309-336},
  publisher = {Springer Science+Business Media},
  doi = {10.1007/s10649-022-10202-z},
  language = {en}
}
RIS
TY  - JOUR
AU  - Herfort, Jonas Dreyøe
AU  - Tamborg, Andreas Lindenskov
AU  - Meier, Florian
AU  - Allsopp, Benjamin Brink
AU  - Misfeldt, Morten
TI  - Twenty Years of Research on Technology in Mathematics Education at CERME: A Literature Review Based on a Data Science Approach
PY  - 2023
JO  - Educational Studies in Mathematics
VL  - 112
IS  - 2
SP  - 309
EP  - 336
DO  - 10.1007/s10649-022-10202-z
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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