A Hypothetical Learning Trajectory Design for Social Arithmetic to Fostering Computational Thinking and Self-Regulated Learning Abilities

Authors

  • Santika Lya Diah Pramesti Universitas Negeri Semarang
  • Scolastika Mariani Universitas Negeri Semarang
  • Putriaji Hendikawati Universitas Negeri Semarang
  • Kartono Kartono Universitas Negeri Semarang
  • Masrukan Masrukan Universitas Negeri Semarang

DOI:

https://doi.org/10.62775/edukasia.v6i2.1493

Keywords:

HLT; MiMOPBL; Computational thinking; Self-regulated learning; Predict-observe-explain (POE);

Abstract

This study aims to design a Hypothetical Learning Trajectory (HLT) on the topic of social arithmetic to address learning obstacles related to students’ computational thinking (CT) and self-regulated learning (SRL) abilities. Employing an Educational Design Research (EDR) approach, the study developed the Missouri Mathematics Open-Ended Problem-Based Learning (MiMOPBL) model supported by an e-module based on the Predict–Observe–Explain (POE) strategy. The HLT integrates CT and SRL by guiding students through prediction, observation, and explanation stages while solving open-ended contextual problems. Validation results confirmed that the instructional tools—including lesson plans, student worksheets, e-modules, CT and SRL instruments—are both valid and reliable. Content validity assessed using Aiken’s V showed values ranging from 0.80 to 0.98, while reliability testing using Cronbach’s Alpha indicated high internal consistency (SRL: α = 0.85; CT: α = 0.89; observation sheet: α = 0.88). These results indicate that the tools are suitable for use in mathematics classrooms. Although limited to the design phase and one topic, the study offers a structured, competency-based learning design that supports student engagement, problem-solving skills, and independent learning. Future research should explore the effectiveness of this learning design across various topics and student groups.

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References

Bangun, S. E., & W. L. Sihombing. (2023). The Effect of the Missouri Mathematics Project (MMP) Learning Model on Students’ Mathematical Problem Solving Ability in Algebra Material in Class VII Budi Murni 2 Catholic Private Middle School Medan. Jurnal Ilmiah Pendidikan Holistik (JIPH), 2(1), 1–16. https://doi.org/10.55927/jiph.v2i1.2827

Bebras Indonesia. (2024). Pengumuman Hasil Bebras Indonesia Challenge 2024. Bebras Indonesia. Keterampilan berpikir komputasi diperkirakan memiliki peran penting di hampir setiap bidang dan profesi di masa depan.

Bocconi, S., Chioccariello, G. A., Dettori, A. F., & Engelhardt, K. (2016). Developing Computational Thinking in Compulsory Education. In Joint Research Centre (JRC). https://doi.org/10.2791/792158

Bouck, E. C., & Yadav, A. (2022). Providing Access and Opportunity for Computational Thinking and Computer Science to Support Mathematics for Students With Disabilities. Journal of Special Education Technology, 37(1), 151–160. https://doi.org/10.1177/0162643420978564

Bråting, K., Kilhamn, C., & Rolandsson, L. (2022). Mathematical Competencies and Programming: The Swedish Case BT - Mathematical Competencies in the Digital Era (U. T. Jankvist & E. Geraniou (Eds.); pp. 293–310). Springer International Publishing. https://doi.org/10.1007/978-3-031-10141-0_16

Brown, N. C. C., Sentance, S., Crick, T., & Humphreys, S. (2014). Restart: The Resurgence of Computer Science in UK Schools. ACM Trans. Comput. Educ., 14(2). https://doi.org/10.1145/2602484

Callejo, M. L., Pérez-Tyteca, P., Moreno, M., & Sánchez-Matamoros, G. (2022). The Use of a Length and Measurement HLT by Pre-Service Kindergarten Teachers’ to Notice Children’s Mathematical Thinking. International Journal of Science and Mathematics Education, 20(3), 597–617. https://doi.org/10.1007/s10763-021-10163-4

Chen, G. (2017). Learning. 156(Seiem), 128–131.

Cobb, Confey, Disessa, Lehrer, & S. (2011). Design experoment in educational research.

Falkner, K., Vivian, R., & Falkner, N. (2015). Teaching computational thinking in K-6: The CSER digital technologies MOOC. Conferences in Research and Practice in Information Technology Series, 160(May), 63–72.

Fisher, L. M. (2016). A decade of ACM efforts contribute to computer science for all. Commun. ACM, 59(4), 25–27. https://doi.org/10.1145/2892740

Grover, S., & Pea, R. (2013). Computational Thinking in K-12: A Review of the State of the Field. Educational Researcher, 42(1), 38–43. https://doi.org/10.3102/0013189X12463051

Hasdi, H., Manuharawati, M., & Sulaiman, R. (2024). Kemampuan Pemecahan Masalah Matematika Siswa dengan Gaya Kognitif Field Dependent dan Field Independent. EDUKASIA: Jurnal Pendidikan Dan Pembelajaran, 5(1), 1393–1398. https://doi.org/10.62775/edukasia.v5i1.1040

Indrawati, Zaida, S., & Lestari, P. E. P. (2024). Pengaruh Model Missouri Mathematics Project (MMP) terhadap Hasil Belajar Matematika ditinjau dari Kemandirian Belajar. Circle: Jurnal Pendidikan Matematika, 4(1), 52–64. https://doi.org/10.28918/circle.v4i1.6897

Jasdilla, L., Fitria, Y., & Sopandi, W. (2019). Predict Observe Explain (POE) strategy toward mental model of primary students. Journal of Physics: Conference Series, 1157(2). https://doi.org/10.1088/1742-6596/1157/2/022043

Kong, S.-C., & Wang, Y.-Q. (2024). Dynamic interplays between self-regulated learning and computational thinking in primary school students through animations and worksheets. Computers and Education, 220. https://doi.org/10.1016/j.compedu.2024.105126

Kwon, H., & Lee, E. (2019). Research trends and issues of education for sustainable development-related research in South Korea. Journal of Baltic Science Education, 18(3), 379–388. https://doi.org/10.33225/jbse/19.18.379

Leikin, Mark. (2012). The effect of bilingualism on creativity: Developmental and educational perspectives. International Journal of Bilingualism, 17(4), 431–447. https://doi.org/10.1177/1367006912438300

Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., & Settle, A. (2014). Computational Thinking in K-9 Education. Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference, 1–29. https://doi.org/10.1145/2713609.2713610

McKenney, S., & Reeves, T. C. (2018). Conducting educational design research. (2nd ed.). Routledge. https://doi.org/10.4324/9781315105642

McKnight, K., O’Malley, K., Ruzic, R., Horsley, M. K., Franey, J. J., & Bassett, K. (2016). Teaching in a Digital Age: How Educators Use Technology to Improve Student Learning. Journal of Research on Technology in Education, 48(3), 194–211. https://doi.org/10.1080/15391523.2016.1175856

Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative Data Analysis.

Nurjanah, A., Nurcahyono, N. A., & Imswatama, A. (2022). Penerapan Model Problem Based Learning terhadap Kemampuan Pemecahan Masalah Matematis Ditinjau dari Gaya Belajar Siswa SMP. Prisma, 11(2), 406. https://doi.org/10.35194/jp.v11i2.2420

OECD. (2023). PISA 2022 Results (Volume I). https://doi.org/https://doi.org/https://doi.org/10.1787/53f23881-en

Paris, S. G., & Paris, A. H. (2001). Classroom Applications of Research on Self-Regulated Learning. 36(2), 89–101.

Paris, S. G., & Paris, A. H. (2001). Classroom Applications of Research on Self-Regulated Learning. 36(2), 89–101.

Pektaş, H. M., Çelik, H., & Karamustafaoğlu, O. (2024). P OE Activity Enriched with Augmented Reality : Conceptual Change on Pressure in Liquids. 20(December), 124–138. https://doi.org/10.15294/jpfi.v20i2.

Prahmana, R. C. I., Kusaka, S., Peni, N. R. N., Endo, H., Azhari, A., & Tanikawa, K. (2024). Cross-cultural insights on computational thinking in geometry: Indonesian and Japanese students’ perspectives. Journal on Mathematics Education, 15(2), 613–638. https://doi.org/10.22342/jme.v15i2.pp613-638

Santika Lya Diah Pramesti, Heni Lilia Dewi, N. A. (2024). View of Analysis of Students’ Computational Thinking Processes in Merdeka Curriculum Differentiation Learning using The Open-Ended Problem Based Learning Model.pdf. https://doi.org/https://doi.org/10.18326/hipotenusa.v6i2.1899

Schunk, D. H., & Zimmerman, B. J. (1998). Self-regulated learning: From teaching to self-reflective practice. In Self-regulated learning: From teaching to self-reflective practice. (pp. xii, 244–xii, 244). Guilford Publications.

Shute, V. J., Sun, C., & Asbell-clarke, J. (2017). Version of Record: https://www.sciencedirect.com/science/article/pii/S1747938X17300350.

Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Computational Thinking in High School Science Classrooms: Exploring the Science “Framework” and “NGSS.” Science Teacher, 81(5), 53–59. https://www.learntechlib.org/p/155904

Song, D., Hong, H., & Oh, E. Y. (2021). Applying computational analysis of novice learners’ computer programming patterns to reveal self-regulated learning, computational thinking, and learning performance. Computers in Human Behavior, 120, 106746. https://doi.org/https://doi.org/10.1016/j.chb.2021.106746

Steck, T. R., DiBiase, W., Wang, C., & Boukhtiarov, A. (2012). The Use of Open-Ended Problem-Based Learning Scenarios in an Interdisciplinary Biotechnology Class: Evaluation of a Problem-Based Learning Course Across Three Years. Journal of Microbiology & Biology Education, 13(1), 2–10. https://doi.org/10.1128/jmbe.v13i1.389

Sudrajat. (2008). Pengertian, Strategi, Metode, Teknik, dan Model Pembelajaran. Sinar Baru Algensindo.

Sullivan, A. M., Johnson, B., Owens, L., & Conway, R. (2014). Punish them or engage them? Teachers’ views of unproductive student behaviours in the classroom. Australian Journal of Teacher Education, 39(6), 43–56. https://doi.org/10.14221/ajte.2014v39n6.6

Tuysuz, A., & and Özdemİr, Ö. faruk. (2025). An experimental study exploring the effects of predict–observe–explain method supported with simulations. Research in Science & Technological Education, 43(2), 512–524. https://doi.org/10.1080/02635143.2023.2296458

Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 Computational Thinking Curriculum Framework: Implications for Teacher Knowledge. 19, 47–57.

Wing, J. M. (2006). Computational thinking. Commun. ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215

Wiraharta, I. P. R. N., Yudiana, K., & Kusmariyatni, N. N. (2020). Meningkatkan Hasil Belajar Matematika Siswa Melalui Model Pembelajaran Open Ended Berbasis Tri Kaya Parisudha. Jurnal Adat Dan Budaya Indonesia, 2(1), 41–51. https://doi.org/10.23887/jabi.v2i1.28907

Yadav, A., Hong, H., & Stephenson, C. (2016). Computational Thinking for All: Pedagogical Approaches to Embedding 21st Century Problem Solving in K-12 Classrooms. TechTrends, 60(6), 565–568. https://doi.org/10.1007/s11528-016-0087-7

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Published

2025-08-17

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How to Cite

A Hypothetical Learning Trajectory Design for Social Arithmetic to Fostering Computational Thinking and Self-Regulated Learning Abilities. (2025). EDUKASIA Jurnal Pendidikan Dan Pembelajaran, 6(2), 733-748. https://doi.org/10.62775/edukasia.v6i2.1493