Learning trajectory of non-Euclidean geometry through ethnomathematics learning approaches to improve spatial ability
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Resumo
Non-Euclidean geometry is an abstract subject and difficult to learn, but mandatory for students. The ethnomathematics approach as a learning approach to improve students’ spatial abilities. The aim of this research is to discover new elements of the spatial abilities of non-Euclidean geometry; determine the relationship between spatial abilities for Euclid, Lobachevsky, and Riemann geometry. This study used the micro genetic method with a 2×2 factorial experimental research design. The sample of this research is 100 students of mathematics education. There are three valid and reliable research instruments through expert trials and field trials. Data collection was carried out in two ways, namely tests and observations. Quantitative data were analyzed through ANCOVA, and observational data were analyzed through the percentage of implementation of the learning trajectory stages. The result is that the spatial ability of students who are given the ethnomathematics learning approach is higher than students who are given the conventional learning approach for Lobachevsky geometry material after controlling for the effect of Euclidean geometry spatial ability. Also, the same thing happened for the spatial abilities of Riemann geometry students. The learning trajectory is conveying learning objectives (learning objective); providing ethnomathematics-based visual problems; students do exploration; students make conclusions and summaries of exploration results; and ends with students sharing conclusions/summaries about concepts and principles in geometric systems. It was concluded that learning non-Euclid geometry through learning paths with an ethnomathematics approach had a positive impact on increasing students’ spatial abilities.
Dados da obra
- Tipo
- Artigo
- Periódico
- Eurasia Journal of Mathematics, Science and Technology Education, v. 19, n. 6, p. em2285
- Editora
- Modestum Ltd
- Ano
- 2023 (2023-06-01)
- Idioma
- en
- Palavras-chave
- non-Euclidean geometry; ethnomathematics; spatial ability; learning trajectories; Lobachevsky geometry; Euclidean geometry; mathematics education students
- Temas
- Etnomatemática, Geometria
- DOI
- 10.29333/ejmste/13269
- ISSN
- 1305-8215, 1305-8223
- Licença
- cc-by
- Acesso
- Download disponível
- Fontes
- Crossref; OpenAlex
- Na Biblioteca desde
- 01/10/2026 · verificada em 03/10/2026
Como citar
ABNT
SUKESTIYARNO, Yohanes Leonardus et al.. Learning trajectory of non-Euclidean geometry through ethnomathematics learning approaches to improve spatial ability. Eurasia Journal of Mathematics, Science and Technology Education, v. 19, n. 6, p. em2285, 2023. DOI: https://doi.org/10.29333/ejmste/13269.
APA
Sukestiyarno, Y. L., Nugroho, K. U. Z., Sugiman, S., & Waluya, B. (2023). Learning trajectory of non-Euclidean geometry through ethnomathematics learning approaches to improve spatial ability. Eurasia Journal of Mathematics, Science and Technology Education, 19(6), em2285. https://doi.org/10.29333/ejmste/13269
BibTeX
@article{sukestiyarno2023,
author = {Sukestiyarno, Yohanes Leonardus and Nugroho, Khathibul Umam Zaid and Sugiman, Sugiman and Waluya, Budi},
title = {Learning trajectory of non-Euclidean geometry through ethnomathematics learning approaches to improve spatial ability},
year = {2023},
journal = {Eurasia Journal of Mathematics, Science and Technology Education},
volume = {19},
number = {6},
pages = {em2285},
publisher = {Modestum Ltd},
doi = {10.29333/ejmste/13269},
language = {en}
}RIS
TY - JOUR AU - Sukestiyarno, Yohanes Leonardus AU - Nugroho, Khathibul Umam Zaid AU - Sugiman, Sugiman AU - Waluya, Budi TI - Learning trajectory of non-Euclidean geometry through ethnomathematics learning approaches to improve spatial ability PY - 2023 JO - Eurasia Journal of Mathematics, Science and Technology Education VL - 19 IS - 6 SP - em2285 DO - 10.29333/ejmste/13269 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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