The Effectiveness of Unplugged Coding and Artificial Intelligence (KKA) Learning in Improving the Computational Thinking Ability of Primary School Students

Suttrisno Suttrisno; Nurul Mahruzah Yulia; Nanin Verina Widya  Putri

doi:10.63922/ijevss.v5i03.4559

Suttrisno Suttrisno Primary School Teacher Education Study Program, Universitas Nahdlatul Ulama Sunan Giri Bojonegoro, East Java, Indonesia
Nurul Mahruzah Yulia Primary School Teacher Education Study Program, Universitas Nahdlatul Ulama Sunan Giri Bojonegoro, East Java, Indonesia
Nanin Verina Widya Putri Primary School Teacher Education Study Program, Universitas Nahdlatul Ulama Sunan Giri Bojonegoro, East Java, Indonesia

DOI: https://doi.org/10.63922/ijevss.v5i03.4559

Keywords: artificial intelligence, unplugged coding, computational thinking, primary education, quasi-experiment

Abstract

The Indonesian Ministry of Education has formally introduced Coding and Artificial Intelligence (Koding dan Kecerdasan Artifisial, KKA) as a learning content area for primary and secondary education, yet many primary schools remain constrained by limited digital infrastructure and low teacher technological readiness. This study evaluates the effectiveness of an unplugged-based KKA instructional model in improving the computational thinking ability of fifth-grade primary school students. The model integrates two phases, namely unplugged coding activities that build conceptual foundations through concrete manipulation and an artificial intelligence phase combining age-appropriate AI literacy with AI-assisted tutoring support. A quasi-experimental design using a non-equivalent pretest-posttest control group was applied to 64 students from two state primary schools in Bojonegoro Regency, divided into an experimental group (n = 32) receiving the KKA model and a control group (n = 32) receiving conventional expository instruction. Computational thinking was measured through a validated Bebras-based test covering decomposition, pattern recognition, abstraction, and algorithmic thinking. Data were analysed using normality and homogeneity tests, an independent sample t-test, the normalised gain score, and Cohen’s effect size. The experimental group achieved a mean posttest score of 82.19 against 68.44 in the control group, with a normalised gain of 0.66 (moderate-to-high) compared to 0.35 (moderate). The t-test confirmed a statistically significant difference (t = 6.473; p < 0.001), and the effect size of d = 1.62 indicated a large practical impact. The KKA model proved most influential on algorithmic thinking and decomposition while also strengthening engagement and collaborative problem solving. The study contributes a structured, low-cost, and policy-aligned instructional model that addresses the equity gap in computational thinking education for resource-limited primary schools.

References

Aytekin, A., & Topçu, M. S. (2024). Improving 6th-grade students’ creative problem-solving skills through plugged and unplugged computational thinking approaches. Journal of Science Education and Technology, 33(1), 1–25. https://doi.org/10.1007/s10956-023-10072-x
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Dağ, F., Şumuer, E., & Durdu, L. (2023). The effect of an unplugged coding course on primary school students’ improvement in their computational thinking skills. Journal of Computer Assisted Learning, 39(6), 1902–1918. https://doi.org/10.1111/jcal.12850
del Olmo-Muñoz, J., Cózar-Gutiérrez, R., & González-Calero, J. A. (2020). Computational thinking through unplugged activities in early years of primary education. Computers & Education, 150, 103832. https://doi.org/10.1016/j.compedu.2020.103832
Education Standards, Curriculum, and Assessment Agency. (2025). Academic manuscript on coding and artificial intelligence learning for primary and secondary education. Ministry of Primary and Secondary Education of the Republic of Indonesia.
Erümit, S. F. (2024). Collaboration of unplugged and plugged activities for primary school students: Developing computational thinking skills with programming. International Journal of Computer Science Education in Schools, 6(3), 1–20. https://doi.org/10.21585/ijcses.v6i3.173
Fagerlund, J., Häkkinen, P., Vesisenaho, M., & Viiri, J. (2021). Computational thinking in programming with Scratch in primary schools: A systematic review. Computer Applications in Engineering Education, 29(1), 12–28. https://doi.org/10.1002/cae.22255
Fitri, Y., & Iswatiningsih, D. (2025). The implementation of artificial intelligence in primary school learning: Opportunities and challenges for teachers at SDN Madang Musi Rawas. Sibatik Journal, 4(5), 559–568. https://doi.org/10.54443/sibatik.v4i5.2716
Günaltay, M. İ., Balcı, S., & Orhan Özen, S. (2025). The effect of computational thinking on creativity: A meta-analysis for teaching strategies. Pedagogical Perspective, 4(2), 110–132. https://doi.org/10.29329/pedper.2025.125
Han, J., Kim, S., & Lee, Y. (2024). Barriers to teaching computer science in primary schools: A systematic review. Education and Information Technologies, 29(10), 12567–12590. https://doi.org/10.1007/s10639-023-12345-9
Hu, L., & Wang, H. (2024). Unplugged activities in the elementary school mathematics classroom: The effects on students’ computational thinking and mathematical creativity. Thinking Skills and Creativity, 54, 101653. https://doi.org/10.1016/j.tsc.2024.101653
Huang, W., & Looi, C.-K. (2021). A critical review of literature on “unplugged” pedagogies in K–12 computer science and computational thinking education. Computer Science Education, 31(1), 83–111. https://doi.org/10.1080/08993408.2020.1789411
Lin, Z., Dai, Y., & Ng, O.-L. (2025). Constructionism in K-12 AI literacy education: A systematic review of pedagogical designs, student outcomes, and learning mechanisms. Journal of Educational Computing Research, 63(5), 1–32. https://doi.org/10.1177/07356331251360442
Misbahrudin, M., Suttrisno, S., Yulia, N. M., & Habibullah, M. R. (2026). Koding dan Kecerdasan Artifisial: Mengenal, Memahami, dan Mencipta untuk Kelas V. Yayasan Drestanta Pelita Indonesia.
Memari, M. (2025). Artificial intelligence in elementary STEM education: A systematic review of current applications and future challenges. Education and Information Technologies. Advance online publication. https://doi.org/10.48550/arXiv.2511.00105
Mladenović, M., Krpan, D., Dragičević, J., & Zaharija, G. (2026). CS Unplugged: Fostering computational thinking in early childhood. In D. Vasić & E. Brajković (Eds.), Digital transformation in education and artificial intelligence application (pp. 41–56). Springer. https://doi.org/10.1007/978-3-032-02801-3_4
Montuori, C., Gambarota, F., Altoè, G., & Arfè, B. (2024). The cognitive effects of computational thinking: A systematic review and meta-analytic study. Computers & Education, 210, 104961. https://doi.org/10.1016/j.compedu.2023.104961
Nur Marifah, S., Abdul Mu’ti, D., & Rijal Wahid, M. M. (2022). Systematic literature review: The integration of computational thinking in the primary school curriculum in Indonesia. Journal of Elementary Education (COLLASE), 5(5), 893–904. https://doi.org/10.22460/collase.v5i5.12148
Relkin, E., de Ruiter, L. E., & Bers, M. U. (2021). Learning to code and the acquisition of computational thinking by young children. Computers & Education, 169, 104222. https://doi.org/10.1016/j.compedu.2021.104222
Seung, H., Cukurova, M., & Lee, Y. (2025). Exploring artificial intelligence integration and student-AI interaction in K-12 education: A scoping review. Journal of Computer Assisted Learning, 41(4), e70144. https://doi.org/10.1111/jcal.70144
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003
Sigayret, K., Tricot, A., & Blanc, N. (2022). Unplugged or plugged-in programming learning: A comparative experimental study. Computers & Education, 184, 104505. https://doi.org/10.1016/j.compedu.2022.104505
Suharyo, S., Pramono, S. E., & Atmaja, H. T. (2024). Artificial intelligence in the context of the Merdeka Curriculum at the primary and secondary education levels: Building skills toward a Golden Indonesia 2045. Humanika, 30(2), 208–217. https://doi.org/10.14710/humanika.v30i2.60563
Sun, L., Hu, L., & Zhou, D. (2021). Improving 7th-graders’ computational thinking skills through unplugged programming activities: A study on the influence of multiple factors. Thinking Skills and Creativity, 42, 100926. https://doi.org/10.1016/j.tsc.2021.100926
Suttrisno, S., & Baisroh, S. R. A. N. (2025). Integrating Artificial Intelligence and Coding Education in Elementary Schools: A Systematic Literature Review of Pedagogical Strategies and Learning Outcomes. Journal of Multidisciplinary Research of Education, 1(2), 110-117.
Wang, C., Luo, F., Liu, X., & Yang, Y. (2023). Fostering computational thinking through unplugged activities: A systematic literature review and meta-analysis. International Journal of STEM Education, 10, 47. https://doi.org/10.1186/s40594-023-00434-7
Wang, Y., & Kale, U. (2025). Unplugged activities to support preservice teachers’ competence, interest, and utility value on computational thinking: A mixed-method inquiry. Education and Information Technologies, 30(13), 19075–19109. https://doi.org/10.1007/s10639-025-13552-2
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
Yeter, I. H., Tan, V. S. Q., & Le, N. (2024). Global initiatives and challenges in integrating artificial intelligence literacy in elementary education: Mapping policies and empirical literature. Future in Educational Research, 2(3), 191–211. https://doi.org/10.1002/fer3.59
Yılmaz, T., & İzmirli, S. (2023). Effect of unplugged and plugged coding activities on secondary school students’ computational thinking skills. Journal of Educational Technology and Online Learning, 6(4), 1180–1193. https://doi.org/10.31681/jetol.1304267