The Effectiveness of Ethnomathematics-Based Learning on Students’ Mathematical Representation in Indonesia: A Meta-Analysis Study

This meta-analysis aims to examine the extent to which ethnomathematics-based learning improves students' mathematical representation abilities and to identify moderator variables that influence its effectiveness. The results of the literature review in the Google Scholar database yielded 11 studies that met the inclusion criteria. Furthermore, the effect sizes were combined according to the Random Effects Model (REM). Data analysis was performed using CMA v3 and R Studio (Meta Package). The results of the study showed that ethnomathematics learning had a significant effect, with an effect size of . This value indicates that the ethnomathematics approach has a strong positive impact on students' mathematical representation abilities. In addition, the effectiveness of ethnomathematics-based learning is influenced by several moderator variables, including education level, cultural background, independent variables, experimental design, and type of publication. However, other variables such as duration of learning, subject matter, and number of students were not proven to moderate the relationship between ethnomathematics-based learning and students’ mathematical representation. It is also hoped that the results of this study can be the basis for policy making for stakeholders in the world of education (in this case teachers/schools/education offices) so that the quality of mathematics learning in the classroom can be more optimal.

Authors

Institutions

Publication Details

Journal
Journal of Teaching and Learning
Published
2026-02-02
DOI
https://doi.org/10.22329/jtl.v20i2.8873
Primary Topic
Mathematics Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effectiveness of Ethnomathematics-Based Learning on Students’ Mathematical Representation in Indonesia: A Meta-Analysis Study

Rika Afriani, Ryan Angga Pratama
Journal of Teaching and Learning
Mathematics Education and Pedagogy
article

The Effectiveness of Ethnomathematics-Based Learning on Students’ Mathematical Representation in Indonesia: A Meta-Analysis Study

Rika Afriani, Ryan Angga Pratama
article en

Abstract

This meta-analysis aims to examine the extent to which ethnomathematics-based learning improves students' mathematical representation abilities and to identify moderator variables that influence its effectiveness. The results of the literature review in the Google Scholar database yielded 11 studies that met the inclusion criteria. Furthermore, the effect sizes were combined according to the Random Effects Model (REM). Data analysis was performed using CMA v3 and R Studio (Meta Package). The results of the study showed that ethnomathematics learning had a significant effect, with an effect size of . This value indicates that the ethnomathematics approach has a strong positive impact on students' mathematical representation abilities. In addition, the effectiveness of ethnomathematics-based learning is influenced by several moderator variables, including education level, cultural background, independent variables, experimental design, and type of publication. However, other variables such as duration of learning, subject matter, and number of students were not proven to moderate the relationship between ethnomathematics-based learning and students’ mathematical representation. It is also hoped that the results of this study can be the basis for policy making for stakeholders in the world of education (in this case teachers/schools/education offices) so that the quality of mathematics learning in the classroom can be more optimal.

Journal of Teaching and LearningVol. 20(2)
Mulawarman University (ID), Mersin Üniversitesi (TR)
Mersin Üniversitesi
Quality Education
Openalex Percentile: Top 65%
Mathematics Education and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.