Validation of an ethnoscience-based inquiry learning instrument to measure engagement and readiness of pre-service elementary teachers: A Rasch analysis
Keywords:
Ethnoscience-inquiry based learning, Rasch analysis, student engagement, teacher readinessAbstract
This study investigates the psychometric properties of a questionnaire designed to assess pre-service elementary school teachers’ engagement and readiness within the context of ethnoscience-based inquiry learning. Ethnoscience integrates scientific knowledge with local cultural practices, aiming to enhance scientific literacy and critical thinking. The questionnaire was developed based on six key indicators Cultural Representation (CR), Connectivity with the Environment (CE), Student Engagement (SE), Integration with Other Lessons (IL), Representation of Values (RV), and the Reconstruction of Original Science into Scientific Science (ROSSS). Content validity was established through expert review, and a pilot study was conducted before full implementation. Using Rasch analysis, the instrument's validity and reliability were tested using data from 197 randomly selected pre-service teachers. Findings indicate that female participants showed significantly higher engagement, especially in SE (M = 4.62 vs. 2.83, t = 2.73, p = 0.007) and ROSSS (t = 2.40, p = 0.019). Overall, the questionnaire revealed medium to high levels of readiness. While the instrument demonstrates promising psychometric quality, limitations related to self-report bias, sampling representativeness, and cultural specificity should be considered. This study provides an evidence-based tool to support more inclusive and culturally relevant science education practices.
Downloads
References
Abdul, L., Laliyo, R., Sumintono, B., & Panigoro, C. (2022). Heliyon Measuring changes in hydrolysis concept of students taught by inquiry model : stacking and racking analysis techniques in Rasch model. Heliyon, 8(July 2021), e09126. https://doi.org/10.1016/j.heliyon.2022.e09126
Adams, D., Chuah, K. M., Sumintono, B., & Mohamed, A. (2022). Students’ readiness for e-learning during the COVID-19 pandemic in a South-East Asian university: a Rasch analysis. Asian Education and Development Studies, 11(2), 324–339. https://doi.org/10.1108/AEDS-05-2020-0100
Adams, R., & August, M. W. (2010). Modelling Polytomously Scored Items With The Rating Scale and Partial Credit Models. August, 1–17.
Adams, S., Farrelly, T., & Holland, J. (2020). Non-formal Education for Sustainable Development: A Case Study of the ‘Children in the Wilderness’ Eco-Club Programme in the Zambezi Region. Journal of Education for Sustainable Development, 14(2), 117–139. https://doi.org/10.1177/0973408220980871
Al Ali, R., & Shehab, R. T. (2020). Psychometric Properties of Social Perception of Mathematics: Rasch Model Analysis. International Education Studies, 13(12), 102–110.
Ardianti, S. D., Wanabuliandari, S., & Tanghal, A. B. (2023). Implementation the Ethnoscience-Based Smart Module To Improve Students’ Patriotism. Jurnal Pendidikan IPA Indonesia, 12(2), 293–300. https://doi.org/10.15294/jpii.v12i2.43789
Azizan, N. H., Mahmud, Z., & Rambli, A. (2020). Rasch rating scale item estimates using maximum likelihood approach: effects of sample size on the accuracy and bias of the estimates. International Journal of Advanced Science and Technology, 29(4), 2526–2531.
Bond, T. G., & Fox, C. M. (2015). Applying the Rasch Model Fundamental Measurement in the Human Sciences (Third Edit). Routledge. https://doi.org/https://doi.org/10.4324/9781315814698
Bond, T. G., Yan, Z., & Heene, M. (2020). Applying the Rasch Model, Fundamental Measurement in the Human Sciences. https://doi.org/10.4324/9780429030499
Browne, J. P., & Cano, S. J. (2019). A Rasch measurement theory approach to improve the interpretation of patient-reported outcomes. Medical Care, 57, S18–S23. https://doi.org/10.1097/MLR.0000000000001096
Budiarti, R. A., Wardani, S., Widiyatmoko, A., Marwoto, P., & Sumarni, W. (2022). Analysis Teacher Understanding on Based Ethnoscience Basic Learning. TA’DIB JOURNAL, 25, 285–292.
Dewi, C. C. A., Erna, M., Haris, I., & Kundera, I. N. (2021). The effect of contextual collaborative learning based ethnoscience to increase student’s scientific literacy ability. Journal of Turkish Science Education, 18(3), 525–541.
Elfrida, E., Nursamsu, N., Mahyuny, S. R., & Manurung, B. (2023). Development Project Based Learning Model with Performance Assessment Based Ethnoscience to Improve Students’ Critical Thinking. Jurnal Penelitian Pendidikan IPA, 9(8 SE-Research Articles), 6406–6414. https://doi.org/10.29303/jppipa.v9i8.4799
Fahrudin, D., Saputro, S., & Sarwanto. (2023). Ethnoscience In Science Learning Research Trend: A Systematic Literature Review From 2013-2022. Jurnal Penelitian Pendidikan IPA, 9(8 SE-Review), 458–467. https://doi.org/10.29303/jppipa.v9i8.3813
Fisher Jr, W. P. (1991). The Rasch Debate: Validity and Revolution in Educational Measurement.
Fisher, W. P. (2007). Rating scale instrument quality criteria. Rasch measurement transactions, 21(1), 1095.
Fitria, A., Siburian, J., Falani, I., & Muhammad, D. (2024). Applying the Rasch Model to Assess Retention and Transfer Test Instruments in Science Education on Additive and Addictive Substances. Integrated Science Education Journal, 5(2 SE-Articles), 101–109. https://doi.org/10.37251/isej.v5i2.864
Hairida, H., Benő, C., Soeharto, S., Charalambos, C., Rasmawan, R., Martono, M., Arifiyanti, F., Winarti, A., & Enawaty, E. (2023). Evaluating Digital Literacy of Pre-service Chemistry Teachers: Multidimensional Rasch Analysis. Journal of Science Education and Technology, 32(5), 643–654. https://doi.org/10.1007/s10956-023-10070-z
Hartini, S., Khairiyah, N., Wati, M., Dewantara, D., Zainuddin, Z., Ismail, I., Saehena, S., & Rahman, N. F. A. (2024). Student’S Science Literacy Skill Through Implementation of Integrating Teaching Modules With Sets Approach on Renewable Energy Topics. Journal of Engineering Science and Technology, 19(5), 1693–1715.
Hikmawati, H., Sutrio, Wahyudi, & Syahidi, K. (2022). Effects of Learning with Ethnoscience Context on Learning Outcomes in Cognitive Aspects of Prospective Physics Teacher Students. Jurnal Penelitian Pendidikan IPA, 8(6 SE-Research Articles), 2793–2801. https://doi.org/10.29303/jppipa.v8i6.2388
Hrnjicic, A., & Alihodžic, A. (2024). Measuring Students’ Conceptual Understanding of Real Functions: A Rasch Model Analysis. International Electronic Journal of Mathematics Education, 19(1).
Ismail, I., Riandi, R., Kaniawati, I., Sopandi, W., Soeharto, S., Rochman, S., Hidayat, F. A., Suhendar, S., & Supriyadi, S. (2025). Assessing science teachers’ readiness for technology-integrated green energy instruction: Development and validation of TPACK instrument using Rasch analysis. Social Sciences and Humanities Open, 12(September), 101948. https://doi.org/10.1016/j.ssaho.2025.101948
Ismail, I., Riandi, R., Kaniawati, I., Sopandi, W., Supriyadi, S., Suhendar, S., & Hidayat, F. A. (2024). Gender Roles in Understanding and Implementing Green Energy Technology in Indonesian Schools: Rasch Analysis . Qubahan Academic Journal, 4(3 SE-Articles), 298–314. https://doi.org/10.48161/qaj.v4n3a752
Khine, M. S. (2020). Objective measurement in psychometric analysis. Rasch Measurement: Applications in Quantitative Educational Research, 3–7.
Khusniati, M., Heriyanti, A. P., Aryani, N. P., Fariz, T. R., & Harjunowibowo, D. (2023). Indigenous science constructs based on Troso woven fabric local wisdom: a study in ethnoscience and ethnoecology. Journal of Turkish Science Education, 20(3), 549–566. https://doi.org/10.36681/tused.2023.031
Kusumastuti, A. (2024). Bahan Ajar Etnosains untuk Siswa Sekolah Dasar Kelas III berbasis Unsusr Budaya Masyarakat Sragen. Universitas Pendidikan Indonesia.
Linacre, J. M. (2022). R Statistics: survey and review of packages for the estimation of Rasch models. International Journal of Medical Education, 13, 171.
Manishimwe, H., Shivoga, W. A., & Nsengimana, V. (2022). Effect of Inquiry-Based Learning on Students’ Attitude Towards Learning Biology at Upper Secondary Schools in Rwanda. Journal of Baltic Science Education, 21(5), 862–874.
Muliani, M., Novita, N., Mellyzar, M., Pasaribu, A. I., & Fadli, M. R. (2022). Analysis of the Characteristics of the Ethnoscience-Based Numeracy Test Instrument Using the Rasch Model. Jurnal Penelitian Pendidikan IPA, 8(5 SE-Research Articles), 2176–2183. https://doi.org/10.29303/jppipa.v8i5.2285
Murwitaningsih, S., & Maesaroh, M. (2023). Ethnoscience in Indonesia and Itâ€TMs Implication to Environmental Education: A Systematic Literature Review. Jurnal Penelitian Pendidikan IPA, 9(10 SE-Review), 903–911. https://doi.org/10.29303/jppipa.v9i10.5447
Oktaviyanthi, R., Agus, R. N., Garcia, M. L. B., & Lertdechapat, K. (2024). Cognitive Load Scale in Learning Formal Definition of Limit: a Rasch Model Approach. Infinity Journal, 13(1), 99–118. https://doi.org/10.22460/infinity.v13i1.p99-118
Omarov, N. B., Mohammed, A., Alghurabi, A. M. K., Alallo, H. M. I., Ali, Y. M., Hassan, A. Y., Demeuova, L., Viktorovna, S. I., Nazym, B., & Al Khateeb, N. S. A. (2023). Distractor Analysis in Multiple-Choice Items Using the Rasch Model. International Journal of Language Testing, 13, 69–78.
Pamudiah, M. K., & Setiawan, B. (2023). Application of Student Worksheets Based on Ethnoscience of Tempe Making on Biotechnology Material to Improve Science Process Skills. Science Education and Application Journal (SEAJ), 5(2 SE-), 99–108. https://doi.org/10.30736/seaj.v5i2.873
Prayogi, S., Ahzan, S., Indriaturrahmi, Rokhmat, J., & Verawati, N. N. S. P. (2023). Dynamic blend of ethnoscience and inquiry in a digital learning platform (e-learning) for empowering future science educators’ critical thinking. Journal of Education and e-Learning Research, 10(4 SE-Articles), 819–828. https://doi.org/10.20448/jeelr.v10i4.5233
Rahayu, R., Sutikno, & Indriyanti, D. R. (2023). An Ethnosains Based Project Based Learning Model with Flipped Classroom on Creative Thinking Skills. Jurnal Penelitian Pendidikan IPA, 9(8 SE-Review), 348–355. https://doi.org/10.29303/jppipa.v9i8.3051
Riandi, R., Ismail, I., Kaniawati, I., Sopandi, W., Rostikawati, D. A., Hamka, D., & Suhendar, S. (2026). Teacher involvement in developing sustainable education materials for AI integration in green energy education. Scientific Reports, 16(4286), 1–16.
Samsudin, A., Afif, N. F., Nugraha, M. G., Suhandi, A., Fratiwi, N. J., Aminudin, A. H., Adimayuda, R., Linuwih, S., & Costu, B. (2021). Reconstructing Students’ Misconceptions on Work and Energy through the PDEODE*E Tasks with Think-Pair-Share. Journal of Turkish Science Education, 18(1), 118–144. https://doi.org/10.36681/tused.2021.56
Sharoni, S. K. A., Seman, N., Razali, N., & Zamri, Z. (2022). Embracing online learning: The readiness and perceived challenges among health sciences distance learners. Malaysian Journal of Medicine and Health Sciences, 18(6), 251–258.
Soeharto, S. (2021). Development of A Diagnostic Assessment Test to Evaluate Science Misconceptions in Terms of School Grades : A Rasch Measurement Approach. Journal of Turkish Science Education, 18(3), 351–370.
Soeharto, S., & Csapó, B. (2022). Assessing Indonesian student inductive reasoning: Rasch analysis. Thinking Skills and Creativity, 46(September). https://doi.org/10.1016/j.tsc.2022.101132
Soeharto, S., Martono, M., Hairida, H., Akhmetova, A., Arifiyanti, F., Benő, C., & Charalambos, C. (2024). The metacognitive awareness of reading strategy among pre-service primary teachers and the possibility of rating improvement using Rasch analysis. Studies in Educational Evaluation, 80(December 2023). https://doi.org/10.1016/j.stueduc.2023.101319
Soemardiawan, S., Wardhani, H. A. K., & Muliadi, A. (2023). Integration of Sasaknese Traditional Game in Ethnoscience Learning: Preservice Teacher’s Perception. Jurnal Penelitian Pendidikan IPA, 9(12 SE-Research Articles), 12295–12302. https://doi.org/10.29303/jppipa.v9i12.6431
Sukarelawan, M. I., Jumadi, Kuswanto, H., Soeharto, & Hikmah, F. N. (2021). Rasch analysis to evaluate the psychometric properties of junior metacognitive awareness inventory in the indonesian context. Jurnal Pendidikan IPA Indonesia, 10(4), 486–495. https://doi.org/10.15294/jpii.v10i4.27114
Sumintono, B., & Widhiarso, W. (2015). Aplikasi pemodelan rasch pada assessment pendidikan. Trim komunikata.
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.
Testa, I., Capasso, G., Colantonio, A., Galano, S., Marzoli, I., Scotti di Uccio, U., & Serroni, G. (2020). Validation of university entrance tests through rasch analysis. Rasch Measurement: Applications in Quantitative Educational Research, 99–124.
Wati, S., Al Idrus, A., & Syukur, A. (2021). Analysis of student scientific literacy: study on learning using ethnoscience integrated science teaching materials based on guided inquiry. Jurnal Pijar MIPA, 16(5), 624–630.
Winarto, Sarwi, S., Cahyono, E., & Sumarni, W. (2022). Developing a Problem-Solving Essay Test Instrument (PSETI) in the Instruction of Basic Science Concepts in Ethnoscience Context. Journal of Turkish Science Education, 19(1), 37–51. https://doi.org/10.36681/tused.2022.108
Zafrullah, Sa’adatul Ulwiyah, & Nofriyandi. (2023). Rasch Model Analysis on Mathematics Test Instruments: Biblioshiny (1983-2023). Mathematics Research and Education Journal, 7(2), 1–13. https://doi.org/10.25299/mrej.2023.vol7(2).14550
Zwick, R., Thayer, D. T., & Lewis, C. (1999). An empirical Bayes approach to Mantel‐Haenszel DIF analysis. Journal of Educational Measurement, 36(1), 1–28.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Journal of Turkish Science Education
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This license enables reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. CC BY-NC-ND includes the following elements: Credit must be given to the creator; only noncommercial uses of the work are permitted; no derivatives or adaptations of the work are permitted.
