Development and Preliminary Evaluation of a Creative micro:bit-Based Learning Model to Support Computational Thinking and Technological Design in Small Rural Schools
Main Article Content
Abstract
Limited access to digital technologies, instructional resources, and teachers with specialized computing expertise continues to restrict learning opportunities for students in small rural schools. Low-cost physical computing tools combined with hands-on and creative learning activities may provide a practical approach to reducing these limitations. This study aimed to (1) design and develop a creative micro:bit-based learning model for Grade 4 students in small rural schools, (2) evaluate the process and outcome efficiency of the developed model and compare students’ learning achievement before and after participating in the learning activities, and (3) evaluate the appropriateness and feasibility of the developed model through expert assessment. The study employed a multi-phase Research and Development approach with a one-group pretest–posttest evaluation design. The development group comprised 10 in-service teachers and 20 pre-service teachers, while the implementation group comprised 30 Grade 4 students from five small rural schools. The developed model consisted of four two-hour learning modules: Fun Thinking, Traffic Light, Micro Servo, and the Meow Cat Project. Three experts examined the content congruence of the model and research instruments using the Index of Item-Objective Congruence. Process and outcome efficiencies were analyzed using the E1/E2 criterion, while students’ module-based pretest and post-test scores were compared using paired-samples t-tests. The results showed that the research instruments obtained IOC values ranging from 0.94 to 1.00. The main implementation produced E1/E2 values of 91.74/79.00, exceeding the predetermined 75/75 criterion. Students’ post-test scores were significantly higher than their pretest scores in all four modules, with mean differences ranging from 4.51 to 5.24 points and p < .001. The experts rated the overall appropriateness and feasibility of the model at a high level (M = 3.65, SD = 0.49), although sustainability and budget feasibility received the lowest mean among the evaluated dimensions (M = 3.45, SD = 0.52). The developed model provides a structured and context-sensitive approach for introducing computing and physical computing activities in small rural schools. It may serve as a practical foundation for teachers and schools seeking to broaden students’ access to technology-enhanced learning; however, further studies with comparison groups, direct measures of computational thinking and technological design, and delayed assessments are needed to confirm its effectiveness, learning retention, and transferability.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Amenyo, J.-T., & Kpo, W. (2023). Leveraging programmable educational drones, robots and AI for learning STEM, computational thinking and higher order thinking in schools in rural villages. In Drones—Various applications. IntechOpen. https://doi.org/10.5772/intechopen.1002465
Cápay, M., & Klimová, N. (2019). Engage your students via physical computing! In 2019 IEEE Global Engineering Education Conference (EDUCON) (pp. 1216–1223). IEEE. https://doi.org/10.1109/EDUCON.2019.8725101
Chisag Guaman, E. D., Yumbo Chimbo, M. N., Chisag Guaman, W. G., & Yumbo Chimbo, K. V. (2025). Innovación digital educativa con TIC, robótica e inteligencia artificial en comunidades rurales del Ecuador. Editorial CID – Centro de Investigación y Desarrollo. https://doi.org/10.37811/cli_w1251
Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Educational research: An introduction (8th ed.). Pearson.
Kastner-Hauler, O., Tengler, K., Sabitzer, B., & Lavicza, Z. (2022). Combined effects of block-based programming and physical computing on primary students’ computational thinking skills. Frontiers in Psychology, 13, 875382. https://doi.org/10.3389/fpsyg.2022.875382
Kim, J. Y., Seo, J. S., & Kim, K. (2022). Development of novel-engineering-based maker education instructional model. Education and Information Technologies, 27(5), 7327–7371. https://doi.org/10.1007/s10639-021-10841-4
Li, L., Huang, C.-W., Morgan, C., Luttgen, K., Chow, E., & Yang, S. (2025). Empowering rural students through computational thinking and real-world STEM applications: Insights from an innovative high school curriculum. Frontiers in Education, 9, 1452470. https://doi.org/10.3389/feduc.2024.1452470
Manikutty, G., Akshay, N., Shruti, C. M., Shetty, R., Mukil, M. V., & Bhavani, R. R. (2020). Social making: Teaching children to design solutions for the global goals. Extended Abstracts - Proceedings of the 2020 ACM Interaction Design and Children Conference, IDC 2020, 145–150. https://doi.org/10.1145/3397617.3397834
Philbin, C. A. (2024). Beyond apps: Tablet and micro:bit devices as tools for creative computing in primary schools. In Proceedings of the 7th Computing Education Practice Conference (CEP 2024) (pp. 25–28). Association for Computing Machinery. https://doi.org/10.1145/3633053.3633054
Sarapak, C., Jumpatam, J., Lunnoo, T., Kongngarm, N., Raso, S., & Kearns, K. (2025). Comparing 3D virtual labs and traditional labs: Impact on teacher training and student learning in physics education. Jurnal Pendidikan IPA Indonesia, 14(4), 772–783. https://doi.org/10.15294/jpii.v14i4.21115
Sarapak, C., Kong-In, P., Jindasri, P., Kakkaew, V., Wattanakornsiri, A., Yoomark, J., Sumrandee, C., Sreejivungsa, K., Malingam, N., Krongsuk, S., & Lunnoo, T. (2025). Instrument design and validation for enhancing instructional design using the TPACK framework: A study in Surin Province. Journal of Innovation, Advancement, and Methodology in STEM Education, 2(1), 10–24. https://so13.tci-thaijo.org/index.php/J_IAMSTEM/article/view/1170
Sarapak, C., Luengsiriwan, A., Kong-In, P., Wattanakornsiri, A., Yoomark, J., Malingam, N., Hardthakwong, B., & Lunnoo, T. (2025). Conceptual understanding in fundamental and mechanical physics among pre-service physics teachers of Surindra Rajabhat University: A statistic and machine learning analysis. Journal of Innovation, Advancement, and Methodology in STEM Education, 2(2), 80–97. https://so13.tci-thaijo.org/index.php/J_IAMSTEM/article/view/1171
Sreejivungsa, K., Sarapak, C., Sumrandee, C., Kong-In, P., Jindasri, P., Kakkaew, V., Wattanakornsiri, A., Yoomark, J., Malingam, N., Nakchat, O., Hardthakwong, B., & Lunnoo, T. (2025). Enhancing student understanding of basic physics concepts through mobile science experiments: A study at Thung Kula Pittayakom School, Surin Province. Journal of Innovation, Advancement, and Methodology in STEM Education, 2(4), 233–246. https://so13.tci-thaijo.org/index.php/J_IAMSTEM/article/view/1169
Vásquez Gómez, E. P., Quevedo Buitrago, J. E., Merchán Hernández, A. E., & Méndez Pineda, D. O. (2025). Robótica educativa para el desarrollo del pensamiento computacional: Un estudio en escuela rural de Colombia. Revista Portuguesa de Educação, 38(2), e25021. https://doi.org/10.21814/rpe.36792
Zhang, H., Jackson, D., Shah, S. A., Beal, K., Phatak, J., & Barnett, M. (2025). Seeding future scientists with computational thinking through the smart greenhouse project. Science Scope, 48(5), 58–66. https://doi.org/10.1080/08872376.2025.2537631