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Data-Driven Education: Data Processing as a Key to Improving the Quality of Mathematics Education

Artigo2023

Tuti Hartati; Nida Fitria; Maulana Al Aziz Harahap ORCID; Dadan Dasari ORCID

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Resumo

Education is a major pillar in the development of a nation, and the quality of education becomes a key factor in determining the progress of a society. In this digital era, there is a rapid development in the use of information technology, and this has a significant impact on the education sector. The purpose of this study is for data-driven education: data processing as the key to improving the quality of mathematics education. This research uses a mixed method that combines qualitative and quantitative methods. This approach was chosen to address the complexity of data management and the comprehensiveness of this topic. The research begins with an in-depth literature analysis to understand the potential of Data-Driven Education. By using data as a guide, educators can make smarter decisions, detail instructional strategies, and create an educational environment that allows each student to reach his or her full potential. This is done by combining the results of various data of educator learners who can make informational decisions to improve the quality of mathematics learning. The application of data management in the context of mathematics education can provide concrete solutions to overcome challenges and improve the quality of learning. The right use of data provides the basis for smarter decisions and more adaptive learning, creating a learning environment that fits the needs of each student. By integrating Data-Driven Education effectively, we can move towards a more inclusive, personalized and successful mathematics education. The use of data contributes significantly in improving the quality and inclusivity of mathematics education. The integration of data management in mathematics education is a critical step towards a more adaptive, inclusive, and effective education

Dados da obra

Tipo
Artigo
Periódico
ALSYSTECH Journal of Education Technology, v. 2, n. 1, p. 45-57
Ano
2023 (2023-12-19)
Idioma
en
Palavras-chave
data-driven education; mathematics education; educational data management; data processing; educational decision-making; personalized learning; adaptive learning; inclusive education
Temas
Inclusão
DOI
10.58578/alsystech.v2i1.2361
ISSN
2988-4403, 2988-442X
Licença
cc-by-nc-sa
Acesso
Download disponível
Fontes
OpenAlex
Na Biblioteca desde
02/10/2026 · verificada em 03/10/2026

Como citar

ABNT
HARTATI, Tuti et al.. Data-Driven Education: Data Processing as a Key to Improving the Quality of Mathematics Education. ALSYSTECH Journal of Education Technology, v. 2, n. 1, p. 45-57, 2023. DOI: https://doi.org/10.58578/alsystech.v2i1.2361.

APA

Hartati, T., Fitria, N., Harahap, M. A. A., & Dasari, D. (2023). Data-Driven Education: Data Processing as a Key to Improving the Quality of Mathematics Education. ALSYSTECH Journal of Education Technology, 2(1), 45-57. https://doi.org/10.58578/alsystech.v2i1.2361

BibTeX
@article{hartati2023,
  author = {Hartati, Tuti and Fitria, Nida and Harahap, Maulana Al Aziz and Dasari, Dadan},
  title = {Data-Driven Education: Data Processing as a Key to Improving the Quality of Mathematics Education},
  year = {2023},
  journal = {ALSYSTECH Journal of Education Technology},
  volume = {2},
  number = {1},
  pages = {45-57},
  doi = {10.58578/alsystech.v2i1.2361},
  language = {en}
}
RIS
TY  - JOUR
AU  - Hartati, Tuti
AU  - Fitria, Nida
AU  - Harahap, Maulana Al Aziz
AU  - Dasari, Dadan
TI  - Data-Driven Education: Data Processing as a Key to Improving the Quality of Mathematics Education
PY  - 2023
JO  - ALSYSTECH Journal of Education Technology
VL  - 2
IS  - 1
SP  - 45
EP  - 57
DO  - 10.58578/alsystech.v2i1.2361
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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