Main Article Content
Abstract
Statistical literacy has emerged as a central competence in mathematics education, particularly for prospective teachers who must be able to interpret, analyze, and critically evaluate data in a world increasingly shaped by information and statistics. However, previous research shows that many prospective teachers continue to struggle with developing statistical literacy, especially in connecting abstract concepts to meaningful contexts. This gap highlights the need for instructional designs that not only strengthen statistical reasoning but also draw on culturally embedded practices to enhance relevance and engagement. Addressing this challenge, the present study develops a Local Instructional Theory (LIT) that supports prospective teachers’ statistical literacy through the integration of local cultural contexts in South Sumatra, designed within the framework of Realistic Mathematics Education (RME) as adapted in Indonesia, namely Pendidikan Matematika Realistik Indonesia (PMRI). Employing a design research methodology, the study was conducted in three phases: a preliminary investigation, a design experiment (pilot and teaching experiment), and a retrospective analysis. The resulting LIT was structured around three context-based learning trajectories, each targeting a key dimension of statistical literacy: data visualization, data interpretation, and critical evaluation. Instructional activities were grounded in authentic cultural contexts—such as Pempek demand during Ramadan, the Bekarang Iwak fishing tradition, and coffee productivity in Pagar Alam—which were used to bridge statistical concepts with learners lived experiences. Findings from the teaching experiments indicate that prospective teachers demonstrated notable shifts from procedural to conceptual reasoning and from descriptive analysis to reflective critique. Participants also showed improved ability to select appropriate graphical representations, interpret contextual data, and critically assess the credibility and sufficiency of statistical information. These outcomes underscore the potential of culturally relevant instructional design to foster holistic statistical literacy. The study contributes both theoretically and practically by offering a validated model for integrating cultural contexts into mathematics education, thereby enriching prospective teachers’ curriculum and providing a replicable approach for diverse educational settings.
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References
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- Bakker, A. (2018). Design Research in Education. Routledge. https://doi.org/10.4324/9780203701010
- Büscher, C. (2022). Design principles for developing statistical literacy on middle schools. Statistics Education Research Journal, 21(1), 8. https://doi.org/10.52041/serj.v21i1.80
- Callingham, R., & Watson, J. M. (2017). The development of statistical literacy at school. Statistics Education Research Journal, 16(1), 181–201. https://doi.org/https://doi.org/10.52041/serj.v16i1.223
- Doorman, L. M. (2005). Modelling motion: From trace graphs to instantaneous change. Freudhental Institute. https://doi.org/https://www.fisme.science.uu.nl/publicaties/literatuur/2005_Doorman_0-243.pdf
- Fauziah, A., Putri, R. I. I., Zulkardi, & Somakim. (2020). Developing PMRI learning environment through lesson study for pre-service primary school teacher. Journal on Mathematics Education, 11(2), 193–208. https://doi.org/10.22342/jme.11.2.10914.193-208
- Forgasz, H., Hall, J., & Robinson, T. (2024). Evaluating pre-service teachers’ statistical literacy capabilities. Mathematics Education Research Journal, 36(1), 231-258. https://doi.org/10.1007/s13394-022-00438-6
- François, K., Monteiro, C., & Allo, P. (2020). Big-data literacy as a new vocation for statistical literacy. Statistics Education Research Journal, 19(1), 194-205. https://doi.org/10.52041/serj.v19i1.130
- Gal, I. (2019). Understanding statistical literacy: About knowledge of contexts and models. Actas Del Tercer Congreso Internacional Virtual de Educación Estadística, 1–15. https://www.ugr.es/~fqm126/civeest/ponencias/gal.pdf
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- Gravemeijer, K., & Van Eerde, D. (2009). Design research as a means for building a knowledge base for teachers and teaching in mathematics education. Elementary School Journal, 109(5), 510–524. https://doi.org/10.1086/596999
- Gunawan, Ulia, N., Akhsani, L., & Untarti, R. (2023). Statistical literacy process of prospective mathematics teachers: A case study of PISA model problems. Journal of Higher Education Theory and Practice, 23(7), 45–58. https://doi.org/https://doi.org/10.33423/jhetp.v23i7.6011
- Johannssen, A., Chukhrova, N., Schmal, F., & Stabenow, K. (2021). Statistical literacy—misuse of statistics and its consequences. Journal of Statistics and Data Science Education, 29(1), 54-62. https://doi.org/10.1080/10691898.2020.1860727
- Kalobo, L. (2016). Teachers’ perceptions of learners’ proficiency in statistical literacy, reasoning and thinking. African Journal of Research in Mathematics, Science and Technology Education, 20(3), 225–233. https://doi.org/10.1080/18117295.2016.1215965
- Kus, M., & Çakiroglu, E. (2020). Prospective mathematics teachers’ critical thinking processes about scientific research: Newspaper article example. Turkish Journal of Education, 9(1), 22–45. https://doi.org/10.19128/turje.605456
- Meitrilova, A., & Putri, R. I. I. (2020). learning design using PMRI to teach central tendency materials. Journal of Physics: Conference Series, 1470(1), 012086. https://doi.org/10.1088/1742-6596/1470/1/012086
- Monteiro, C. E. F., & Carvalho, R. N. (2023). Toward statistical literacy to critically approach big data in mathematics education. In Research on reasoning with data and statistical thinking: International perspectives (pp. 227-242). Springer International Publishing. https://doi.org/10.1007/978-3-031-29459-4_18
- Peedikayil, J. V., Vijayan, V., & Kaliappan, T. (2023). Teachers’ attitude towards education for sustainable development: A descriptive research. International Journal of Evaluation and Research in Education (IJERE), 12(1), 86-95. https://doi.org/10.11591/ijere.v12i1.23019
- Phadke, S. (2022). Measurement, assessment, and improvement of statistical literacy in relevant contexts. The Pennsylvania State University. https://search.proquest.com/openview/73df13b3587cf31fec7ace6374293338/1?pq-origsite=gscholar&cbl=18750&diss=y
- Putri, R. I. I., Dolk, M., & Zulkardi. (2015). Professional development of PMRI teachers for introduction social norm. Journal on Mathematics Education, 6(1), 11–19. https://doi.org/dx.doi.org/10.22342/jme.61.11
- Rahayu, P. T., & Putri, R. I. I. (2020). Fruit salad’s recipes in the design of learning mean in eighth grade. Journal of Physics: Conference Series, 1657(1), 012059. https://doi.org/10.1088/1742-6596/1657/1/012059
- Ramadhani, R., Prahmana, R. C. I., Soeharto, & Saleh, A. (2024). Integrating traditional food and technology in statistical learning: A learning trajectory. Journal on Mathematics Education, 15(4), 1277–1310. https://doi.org/10.22342/jme.v15i4.pp1277-1310
- Rawani, D., Putri, R. I. I., Zulkardi, & Susanti, E. (2023). RME-based local instructional theory for translation and reflection using of South Sumatra dance context. Journal on Mathematics Education, 14(3), 545–562. https://doi.org/10.22342/jme.v14i3.pp545-562
- Sharma, S. (2017). Definitions and models of statistical literacy: A literature review. Open Review of Educational Research, 4(1), 118–133. https://doi.org/10.1080/23265507.2017.1354313
- Utari, R. S., Putri, R. I. I., & Zulkardi. (2024a). Designing a hypothetical learning trajectory using the local wisdom of south Sumatera as a context through hybrid learning. Jurnal Pendidikan Matematika, 18(1), 79–96. https://doi.org/10.22342/jpm.v18i1.pp79-96
- Utari, R. S., Putri, R. I. I., Zulkardi, & Hapizah. (2024b). Integrating South Sumatera’s local wisdom context into statistical literacy education: An exploration study. Journal of Honai Math, 7(2), 327–346. https://doi.org/10.30862/jhm.v7i2.653
- van den Heuvel-Panhuizen, M., Drijvers, P., Education, M., Sciences, B., & Goffree, F. (2014). Realistic Mathematics Education. In Encyclopedia of Mathematics Education (pp. 521–532). Springer. https://doi.org/10.1007/978-94-007-4978-8
- van Dijke-Droogers, M., Drijvers, P., & Bakker, A. (2022). Introducing statistical inference: Design of a theoretically and empirically based learning trajectory. International Journal of Science and Mathematics Education, 20(8), 1743–1766. https://doi.org/10.1007/s10763-021-10208-8
- Waard, J. de, Bogaerts, L., Moorselaar, D. van, & Theeuwes, J. (2021). Surprisingly inflexible: Statistically learned suppression of distractors generalizes across contexts. Attention Perception & Psychophysics, 84(2), 459–473. https://doi.org/10.3758/s13414-021-02387-x
- Zulkardi, Putri, R. I. I., & Wijaya, A. (2020). Two decades of Realistic Mathematics Education in Indonesia. In International Reflection on the Netherland Didactic of Mathematics (pp. 325–340). Spinger. https://doi.org/10.1007/978-3-030-20223-1_18
References
Bakker, A. (2004). Design research in statistics education: On symbolizing and computer tools. CD-β Press, Center for Science and Mathematics Education. https://doi.org/https://dspace.library.uu.nl/bitstream/handle/1874/893/title.pdf
Bakker, A. (2018). Design Research in Education. Routledge. https://doi.org/10.4324/9780203701010
Büscher, C. (2022). Design principles for developing statistical literacy on middle schools. Statistics Education Research Journal, 21(1), 8. https://doi.org/10.52041/serj.v21i1.80
Callingham, R., & Watson, J. M. (2017). The development of statistical literacy at school. Statistics Education Research Journal, 16(1), 181–201. https://doi.org/https://doi.org/10.52041/serj.v16i1.223
Doorman, L. M. (2005). Modelling motion: From trace graphs to instantaneous change. Freudhental Institute. https://doi.org/https://www.fisme.science.uu.nl/publicaties/literatuur/2005_Doorman_0-243.pdf
Fauziah, A., Putri, R. I. I., Zulkardi, & Somakim. (2020). Developing PMRI learning environment through lesson study for pre-service primary school teacher. Journal on Mathematics Education, 11(2), 193–208. https://doi.org/10.22342/jme.11.2.10914.193-208
Forgasz, H., Hall, J., & Robinson, T. (2024). Evaluating pre-service teachers’ statistical literacy capabilities. Mathematics Education Research Journal, 36(1), 231-258. https://doi.org/10.1007/s13394-022-00438-6
François, K., Monteiro, C., & Allo, P. (2020). Big-data literacy as a new vocation for statistical literacy. Statistics Education Research Journal, 19(1), 194-205. https://doi.org/10.52041/serj.v19i1.130
Gal, I. (2019). Understanding statistical literacy: About knowledge of contexts and models. Actas Del Tercer Congreso Internacional Virtual de Educación Estadística, 1–15. https://www.ugr.es/~fqm126/civeest/ponencias/gal.pdf
Gravemeijer, K., & Cobb, P. (2006). Design research from a learning design perspective. In Akker, Jan van den., Gravemeijer, Koeno., McKenney, Susan., & Nieeven, Nienke. (Ed.), Educational Design Research (pp. 29–63). Routledge. https://doi.org/10.4324/9780203088364-12
Gravemeijer, K., & Van Eerde, D. (2009). Design research as a means for building a knowledge base for teachers and teaching in mathematics education. Elementary School Journal, 109(5), 510–524. https://doi.org/10.1086/596999
Gunawan, Ulia, N., Akhsani, L., & Untarti, R. (2023). Statistical literacy process of prospective mathematics teachers: A case study of PISA model problems. Journal of Higher Education Theory and Practice, 23(7), 45–58. https://doi.org/https://doi.org/10.33423/jhetp.v23i7.6011
Johannssen, A., Chukhrova, N., Schmal, F., & Stabenow, K. (2021). Statistical literacy—misuse of statistics and its consequences. Journal of Statistics and Data Science Education, 29(1), 54-62. https://doi.org/10.1080/10691898.2020.1860727
Kalobo, L. (2016). Teachers’ perceptions of learners’ proficiency in statistical literacy, reasoning and thinking. African Journal of Research in Mathematics, Science and Technology Education, 20(3), 225–233. https://doi.org/10.1080/18117295.2016.1215965
Kus, M., & Çakiroglu, E. (2020). Prospective mathematics teachers’ critical thinking processes about scientific research: Newspaper article example. Turkish Journal of Education, 9(1), 22–45. https://doi.org/10.19128/turje.605456
Meitrilova, A., & Putri, R. I. I. (2020). learning design using PMRI to teach central tendency materials. Journal of Physics: Conference Series, 1470(1), 012086. https://doi.org/10.1088/1742-6596/1470/1/012086
Monteiro, C. E. F., & Carvalho, R. N. (2023). Toward statistical literacy to critically approach big data in mathematics education. In Research on reasoning with data and statistical thinking: International perspectives (pp. 227-242). Springer International Publishing. https://doi.org/10.1007/978-3-031-29459-4_18
Peedikayil, J. V., Vijayan, V., & Kaliappan, T. (2023). Teachers’ attitude towards education for sustainable development: A descriptive research. International Journal of Evaluation and Research in Education (IJERE), 12(1), 86-95. https://doi.org/10.11591/ijere.v12i1.23019
Phadke, S. (2022). Measurement, assessment, and improvement of statistical literacy in relevant contexts. The Pennsylvania State University. https://search.proquest.com/openview/73df13b3587cf31fec7ace6374293338/1?pq-origsite=gscholar&cbl=18750&diss=y
Putri, R. I. I., Dolk, M., & Zulkardi. (2015). Professional development of PMRI teachers for introduction social norm. Journal on Mathematics Education, 6(1), 11–19. https://doi.org/dx.doi.org/10.22342/jme.61.11
Rahayu, P. T., & Putri, R. I. I. (2020). Fruit salad’s recipes in the design of learning mean in eighth grade. Journal of Physics: Conference Series, 1657(1), 012059. https://doi.org/10.1088/1742-6596/1657/1/012059
Ramadhani, R., Prahmana, R. C. I., Soeharto, & Saleh, A. (2024). Integrating traditional food and technology in statistical learning: A learning trajectory. Journal on Mathematics Education, 15(4), 1277–1310. https://doi.org/10.22342/jme.v15i4.pp1277-1310
Rawani, D., Putri, R. I. I., Zulkardi, & Susanti, E. (2023). RME-based local instructional theory for translation and reflection using of South Sumatra dance context. Journal on Mathematics Education, 14(3), 545–562. https://doi.org/10.22342/jme.v14i3.pp545-562
Sharma, S. (2017). Definitions and models of statistical literacy: A literature review. Open Review of Educational Research, 4(1), 118–133. https://doi.org/10.1080/23265507.2017.1354313
Utari, R. S., Putri, R. I. I., & Zulkardi. (2024a). Designing a hypothetical learning trajectory using the local wisdom of south Sumatera as a context through hybrid learning. Jurnal Pendidikan Matematika, 18(1), 79–96. https://doi.org/10.22342/jpm.v18i1.pp79-96
Utari, R. S., Putri, R. I. I., Zulkardi, & Hapizah. (2024b). Integrating South Sumatera’s local wisdom context into statistical literacy education: An exploration study. Journal of Honai Math, 7(2), 327–346. https://doi.org/10.30862/jhm.v7i2.653
van den Heuvel-Panhuizen, M., Drijvers, P., Education, M., Sciences, B., & Goffree, F. (2014). Realistic Mathematics Education. In Encyclopedia of Mathematics Education (pp. 521–532). Springer. https://doi.org/10.1007/978-94-007-4978-8
van Dijke-Droogers, M., Drijvers, P., & Bakker, A. (2022). Introducing statistical inference: Design of a theoretically and empirically based learning trajectory. International Journal of Science and Mathematics Education, 20(8), 1743–1766. https://doi.org/10.1007/s10763-021-10208-8
Waard, J. de, Bogaerts, L., Moorselaar, D. van, & Theeuwes, J. (2021). Surprisingly inflexible: Statistically learned suppression of distractors generalizes across contexts. Attention Perception & Psychophysics, 84(2), 459–473. https://doi.org/10.3758/s13414-021-02387-x
Zulkardi, Putri, R. I. I., & Wijaya, A. (2020). Two decades of Realistic Mathematics Education in Indonesia. In International Reflection on the Netherland Didactic of Mathematics (pp. 325–340). Spinger. https://doi.org/10.1007/978-3-030-20223-1_18
