Development of a Sigi Cultural Ethnomathematics-Based Student Learning Needs Questionnaire to Support SDG 4: Quality Education

Mailili Wahyuni H; Jamhari  Mohammad; Ratman Ratman; Astija Astija

doi:10.63230/jocsis.2.2.179

Authors

Mailili Wahyuni H Tadulako University Author
Jamhari Mohammad Tadulako University Author
Ratman Ratman Tadulako University Author
Astija Astija Tadulako University Author

DOI:

https://doi.org/10.63230/jocsis.2.2.179

Keywords:

Cultural-Based Teaching Materials, Ethnomathematics, Instrument Development, Sigi Culture, Student Characteristics, Students’ Learning Needs

Abstract

Objective: To develop a valid and reliable questionnaire and teacher interview instrument for assessing students’ learning needs and characteristics in junior high schools in Sigi Regency, and to analyze these needs as a basis for developing Sigi culture-based ethnomathematics teaching materials. Method: The study employed a Research and Development (R&D) approach using the 4D model (Define, Design, Development, and Dissemination). Instrument development involved needs analysis, instrument design, expert validation, empirical testing, and reliability analysis. Results: Expert validation indicated that the instruments were feasible for use with minor revisions. Empirical testing showed that 17 of 26 questionnaire items and 11 of 15 interview questions were valid. Reliability analysis produced coefficients of 0.786 for the questionnaire and 0.798 for the interview guideline, indicating good reliability. Novelty: Developing and validating a student learning needs questionnaire specifically designed to support the development of Sigi cultural ethnomathematics-based mathematics teaching materials. By integrating students’ learning needs with local cultural contexts, the instrument provides a systematic framework for designing culturally responsive mathematics instruction that contributes to SDG 4 (Quality Education) through inclusive, contextual, and meaningful learning while supporting the preservation of local cultural heritage in line with SDG 11 (Sustainable Cities and Communities).

References

Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement, 45(1), 131–142. https://doi.org/10.1177/0013164485451012

Agustyaningrun, N., Sari, R. N., Abadi, A. M., & Mahmudi, A. (2021). Dominant factors that cause students’ difficulties in learning abstract algebra: A case study at a university in Indonesia. International Journal of Instruction, 14(1), 847–866. https://doi.org/10.29333/iji.2021.14151a

Artino, A. R., La Rochelle, J. S., Dezee, K. J., & Gehlbach, H. (2014). Developing questionnaires for educational research: AMEE Guide No. 87. Medical Teacher, 36(6), 463–474. https://doi.org/10.3109/0142159X.2014.889814

Batiibwe, M. S. K. (2025). Ethnomathematics as a pedagogical tool for mathematics education: Opportunities and challenges. SN Social Sciences, 5, 221. https://doi.org/10.1007/s43545-025-01260-0

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 41, 745–783. https://doi.org/10.1007/s10490-023-09871-y

Cruchinho, P., López-Franco, M. D., Capelas, M. L., Almeida, S., Bennett, P. M., da Silva, M. M., Teixeira, G., Nunes, E., Lucas, P., & Gaspar, F. (2024). Translation, cross-cultural adaptation, and validation of measurement instruments: A practical guideline for novice researchers. Journal of Multidisciplinary Healthcare, 17, 2701–2728. https://doi.org/10.2147/JMDH.S419714

Doran, J., Kirby, A., & Bourke, J. (2026). Survey & questionnaire design: Collecting primary data to answer research questions. Axel NEEFS.

Ferrari, R. (2015). Writing narrative style literature reviews. Medical Writing, 24(4), 230–235. https://doi.org/10.1179/2047480615Z.000000000329

Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286–299. https://doi.org/10.1037/1040-3590.7.3.286

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw Hill.

Huang, C., Li, C., Zhao, F., Zhu, J., Wang, S., & Sun, G. (2022). The association between childhood exposure to ambient air pollution and obesity: A systematic review and meta-analysis. International Journal of Environmental Research and Public Health, 19(8), 4491. https://doi.org/10.3390/ijerph19084491

Holmes, A. G. D. (2023). The design and use of questionnaires in educational research: A new (student) researcher guide. Innovare Journal of Education, 11(3), 1–5. https://doi.org/10.22159/ijoe.2023v11i3.47599

Jupri, A., Drijvers, P., & van den Heuvel-Panhuizen, M. (2014). Difficulties in initial algebra learning in Indonesia. Mathematics Education Research Journal, 26, 683–710. https://doi.org/10.1007/s13394-013-0097-0

Lambert, L. S., & Newman, D. A. (2023). Construct development and validation in three practical steps: Recommendations for reviewers, editors, and authors. Organizational Research Methods, 26(4), 574–607. https://doi.org/10.1177/10944281221115374

Lee, H., Cho, J. K., Park, J., Lee, H., Fond, G., Boyer, L., Kim, H. J., Park, S., Cho, W., Lee, H., Lee, J., & Yon, D. K. (2024). Machine learning–based prediction of suicidality in adolescents with allergic rhinitis: Derivation and validation in 2 independent nationwide cohorts. Journal of Medical Internet Research, 26, e51473. https://doi.org/10.2196/51473

Mullis, I. V. S., Martin, M. O., Foy, P., Kelly, D. L., & Fishbein, B. (2020). TIMSS 2019 international results in mathematics and science. Boston College, TIMSS & PIRLS International Study Center. https://timssandpirls.bc.edu/timss2019/international-results/

Mullis, I. V. S., Martin, M. O., Hooper, M. (2017). Measuring changing educational contexts in a changing world: Evolution of the TIMSS and PIRLS questionnaires. In M. Rosén, K. Yang Hansen, & U. Wolff (Eds.), Cognitive abilities and educational outcomes (pp. 1–20). Springer. https://doi.org/10.1007/978-3-319-43473-5_11

OECD. (2019). PISA 2018 results (Vol. 1): What students know and can do. OECD Publishing. https://doi.org/10.1787/5f07c754-en

Sakti, S. A., Endraswara, S., & Rohman, A. (2024). Revitalizing local wisdom within character education through ethnopedagogy approach: A case study on a preschool in Yogyakarta. Heliyon, 10(10), e31370. https://doi.org/10.1016/j.heliyon.2024.e31370

Simbolon, R. (2024). Literature study: Integration of ethnomathematics in mathematics learning in schools. JMEA: Journal of Mathematics Education and Application, 3(2), 70–76. https://doi.org/10.30596/jmea.v3i2.20332

Siregar, R. S. (2024). Students’ preferences for varied learning methods: An empirical study of the effectiveness and appeal of diverse instructional approaches. Jurnal Profesi Guru Indonesia, 1(2), 140–152. https://doi.org/10.62945/jpgi.v1i2.679

Suciati, I., Windra, W., Al-Afandi, A.-A., Hajerina, H., & Alaydrus, S. H. (2023). Ethnomathematics explorations on the concept of two-dimensional shape in “Tadulako Bulili” folk story. Alifmatika: Jurnal Pendidikan dan Pembelajaran Matematika, 5(2), 171–187. https://doi.org/10.35316/alifmatika.2023.v5i2.171-187

Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48, 1273–1296. https://doi.org/10.1007/s11165-016-9602-2

Taherdoost, H. (2022). What are different research approaches? Comprehensive review of qualitative, quantitative, and mixed method research, their applications, types, and limitations. Journal of Management Science & Engineering Research, 5(1), 53–63. https://doi.org/10.30564/jmser.v5i1.4538

Widoyoko, S. E. P. (2018). Teknik penyusunan instrumen penelitian (Cet. 7). Pustaka Pelajar.

Wijaya, A., Retnawati, H., Setyaningrum, W., Aoyama, K., & Sugiman. (2019). Diagnosing students’ learning difficulties in the eyes of Indonesian mathematics teachers. Journal on Mathematics Education, 10(3), 357–364. https://jme.ejournal.unsri.ac.id/index.php/jme/article/view/3799

Yin, M., & Lee, E.-J. (2023). Exposure to loneliness cues reduces prosocial behavior: Evidence from N400 and P300. Frontiers in Psychology, 14, 1094652. https://doi.org/10.3389/fpsyg.2023.1094652