Implementation of Coding and Artificial Intelligence as an Additional Subject in an Indonesian Private Elementary School: A Qualitative Case Study
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- Published
- 2026-07-30
- Pages
- 625-648
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- Original Research Article
Abstract
Coding and artificial intelligence (Coding-AI) are increasingly introduced in elementary schools to provide age-appropriate experiences in computational thinking, purposeful technology use, and responsible engagement with artificial intelligence. However, evidence on how Coding-AI is implemented as an additional subject in Indonesian private elementary schools remains limited. This qualitative case study examined the implementation of Coding-AI in one Grade-5 class at SD Muhammadiyah 1 Kesamben, Blitar, Indonesia, during the 2025/2026 academic year. Participants were one teacher and 15 students. Data were generated through classroom observations, semi-structured interviews, and documentation and analyzed using the interactive processes of data condensation, data display, and conclusion drawing/verification. The analysis used six sensitizing competence elements: computational thinking, digital literacy, algorithms and programming, data analysis, AI literacy and ethics, and AI use for learning. Case-specific coded evidence was documented for digital literacy among 15/15 students (100.0%), computational thinking among 14/15 (93.3%), AI literacy and ethics among 14/15 (93.3%), algorithms and programming among 13/15 (86.7%), AI use for learning among 13/15 (86.7%), and data analysis among 12/15 (80.0%). These frequencies summarize observed or reported behaviors within the case and do not represent standardized competency scores or changes over time. The teacher facilitated stepwise problem solving, purposeful and safe technology use, introductory programming, and ethical AI exploration, while students described systematic task completion, information seeking, and guided engagement with digital learning resources. The convergence of classroom, interview, and documentary evidence informed a contextual representation of Coding-AI implementation that emphasizes scaffolded participation rather than independent mastery. Because the findings derive from one teacher and 15 Grade-5 students in one private school, they should be interpreted as analytically, rather than statistically, transferable.
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Novinda Ristanti Faradila, Dian Fitri Nur Aini. (2026). Implementation of Coding and Artificial Intelligence as an Additional Subject in an Indonesian Private Elementary School: A Qualitative Case Study. Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika, 10(2), 625-648. https://journal-center.litpam.com/index.php/e-Saintika/article/view/5912
References
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
Al-Abdullatif, A. M. (2025). Auditing AI Literacy Competency in K–12 Education: The Role of Awareness, Ethics, Evaluation, and Use in Human–Machine Cooperation. Systems, 13(6), 490. https://doi.org/10.3390/systems13060490
Alfiras, M. I. I., Emran, A. Q., & Mohamed, A. M. (2025). Ethics and governance of generative AI in education: a systematic review on responsible adoption. Discover Education, 5(1), 37. https://doi.org/10.1007/s44217-025-01051-y
Aliyyah, R. R., Prasetyo, T., & Widyasari, W. (2025). Perspectives of Teachers on Digital Literacy Implementation Curriculum in Elementary Schools. F1000Research, 14, 1299. https://doi.org/10.12688/f1000research.172273.2
Chiu, T. K. F. (2025). AI literacy and competency: definitions, frameworks, development and future research directions. Interactive Learning Environments, 33(5), 3225–3229. https://doi.org/10.1080/10494820.2025.2514372
Chiu, T. K. F., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171. https://doi.org/10.1016/j.caeo.2024.100171
Cimino, S., Maremmani, A. G., & Cerniglia, L. (2025). The Use of Artificial Intelligence (AI) in Early Childhood Education. Societies, 15(12), 341. https://doi.org/10.3390/soc15120341
Farchan, A. (2025). Integration of Coding and Artificial Intelligence (AI) Subjects in Primary School Curriculum as an Effort to Improve 21st Century Skills. Jurnal Penelitian Pendidikan, 42(2), 238–242.
Gardeli, A., & Vosinakis, S. (2025). Fostering computational thinking in young students through student generated challenges in tangible mobile augmented reality games. Discover Education, 4(1), 529. https://doi.org/10.1007/s44217-025-00899-4
Golrang, A., & Sharma, K. (2025). The role of AI in shaping educational experiences in computer science: A systematic review. Computers in Human Behavior: Artificial Humans, 6, 100199. https://doi.org/10.1016/j.chbah.2025.100199
Gouseti, A., James, F., Fallin, L., & Burden, K. (2025). The ethics of using AI in K-12 education: a systematic literature review. Technology, Pedagogy and Education, 34(2), 161–182. https://doi.org/10.1080/1475939X.2024.2428601
Güner, H., & Er, E. (2025). AI in the classroom: Exploring students’ interaction with ChatGPT in programming learning. Education and Information Technologies, 30(9), 12681–12707. https://doi.org/10.1007/s10639-025-13337-7
Hennessy, S., D’Angelo, S., McIntyre, N., Koomar, S., Kreimeia, A., Cao, L., Brugha, M., & Zubairi, A. (2022). Technology Use for Teacher Professional Development in Low- and Middle-Income Countries: A systematic review. Computers and Education Open, 3, 100080. https://doi.org/10.1016/j.caeo.2022.100080
Hsu, H.-P. (2025). From Programming to Prompting: Developing Computational Thinking through Large Language Model-Based Generative Artificial Intelligence. TechTrends, 69(3), 485–506. https://doi.org/10.1007/s11528-025-01052-6
Huang, Y.-T., Li, C.-L., Chang, C.-C., & Tarng, W. (2025). Enhancing Computational Thinking and Programming Logic Skills with App Inventor 2 and Robotics: Effects on Learning Outcomes, Motivation, and Cognitive Load. Sensors (Basel, Switzerland), 25(22). https://doi.org/10.3390/s25227059
Kashif, M., Ammar, M., Sellami, A., Chiu, T. K. F., Abbasi, S. A., & Ahmad, Z. (2025). Teachers’ perspectives on AI integration in K-12 education: challenges, opportunities, and preliminary assessment model – a systematic review. Computers in the Schools, 1–27. https://doi.org/10.1080/07380569.2025.2602507
Kong, S.-C., Cheung, M.-Y. W., & Tsang, O. (2024). Developing an artificial intelligence literacy framework: Evaluation of a literacy course for senior secondary students using a project-based learning approach. Computers and Education: Artificial Intelligence, 6, 100214. https://doi.org/10.1016/j.caeai.2024.100214
Lai, C.-H., & Lin, C.-Y. (2025). Analysis of Learning Behaviors and Outcomes for Students with Different Knowledge Levels: A Case Study of Intelligent Tutoring System for Coding and Learning (ITS-CAL). Applied Sciences, 15(4), 1922. https://doi.org/10.3390/app15041922
Lee, H., Kim, H., & Yan, W. (2025). Promoting inclusive AI and technology in K-12 education: A review of context, instructional strategies, and learning outcomes. Computers and Education: Artificial Intelligence, 9, 100478. https://doi.org/10.1016/j.caeai.2025.100478
Lee, S. J., & Kwon, K. (2024). A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomes. Computers and Education: Artificial Intelligence, 6, 100211. https://doi.org/10.1016/j.caeai.2024.100211
Li, L., Valdez, J. P. M., & Du, Y. (2025). Digital citizenship education at the early childhood level: how is it implemented? A systematic review. International Journal of Child Care and Education Policy, 19(1), 13. https://doi.org/10.1186/s40723-025-00153-2
Liu, X., & Zhong, B. (2025). Integrating generative Artificial Intelligence into student learning: A systematic review from a TPACK perspective. Educational Research Review, 49, 100741. https://doi.org/10.1016/j.edurev.2025.100741
Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61. https://doi.org/10.1016/j.chb.2014.09.012
Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative data analysis: A methods sourcebook. SAGE Publications Inc.
Misirli, A., & Komis, V. (2023). Computational thinking in early childhood education: The impact of programming a tangible robot on developing debugging knowledge. Early Childhood Research Quarterly, 65, 139–158. https://doi.org/10.1016/j.ecresq.2023.05.014
Ogegbo, A. A., & Ramnarain, U. (2022). A systematic review of computational thinking in science classrooms. Studies in Science Education, 58(2), 203–230. https://doi.org/10.1080/03057267.2021.1963580
Palop, B., Díaz, I., Rodríguez-Muñiz, L. J., & Santaengracia, J. J. (2025). Redefining computational thinking: A holistic framework and its implications for K-12 education. Education and Information Technologies, 30(10), 13385–13410. https://doi.org/10.1007/s10639-024-13297-4
Qian, Y. (2026). Building early AI literacy: developing a pedagogical framework for early childhood education. AI, Brain and Child, 2(1), 6. https://doi.org/10.1007/s44436-026-00030-w
Rahmatullah, N., & Azzahra, S. F. (2026). Strategies for Preparing Teachers for Coding and Artificial Intelligence Education. EDUMATSAINS, 10(4), 276–290.
Sari, G. I., Winasis, S., Pratiwi, I., Wildan Nuryanto, U., & Basrowi. (2024). Strengthening digital literacy in Indonesia: Collaboration, innovation, and sustainability education. Social Sciences & Humanities Open, 10, 101100. https://doi.org/10.1016/j.ssaho.2024.101100
Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities. Computers and Education: Artificial Intelligence, 4, 100124. https://doi.org/10.1016/j.caeai.2023.100124
Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions. Computers and Education: Artificial Intelligence, 3, 100072. https://doi.org/10.1016/j.caeai.2022.100072
Sulasmono, B., Friska, Y., Sajiman, S. U., & Purnama, S. (2026). School Readiness for Coding and AI Education : A Case Study of Policy Implementation and Pedagogical Adaptation in Indonesia. Al-Ishlah: Jurnal Pendidikan, 18(1), 407–420. https://doi.org/10.35445/alishlah.v18i1.8910
Wang, H., Li, X., Zhang, C., & Kang, Z. (2026). The constructing and empirical research on primary and secondary school teachers’ digital competencies in the age of artificial intelligence. Discover Artificial Intelligence, 6(1), 119. https://doi.org/10.1007/s44163-026-00838-8
Wang, X., Wan, F., & Dai, J. (2026). Enhancing computational thinking through coding education in primary school students: an experimental study on the impact of early programming exposure on problem-solving skills. Frontiers in Psychology, 17, 1734482. https://doi.org/10.3389/fpsyg.2026.1734482
Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 366(1881), 3717–3725. https://doi.org/10.1098/rsta.2008.0118
Wu, D., Chen, M., Chen, X., & Liu, X. (2024). Analyzing K-12 AI education: A large language model study of classroom instruction on learning theories, pedagogy, tools, and AI literacy. Computers and Education: Artificial Intelligence, 7, 100295. https://doi.org/10.1016/j.caeai.2024.100295
Yang, J., Xie, W., & Ni, J. (2025). A framework for AI ethics literacy: development, validation, and its role in fostering students’ self-rated learning competence. Scientific Reports, 15(1), 38030. https://doi.org/10.1038/s41598-025-21977-5
Yang, W. (2025). Redefining educational objectives in the age of artificial intelligence: The SCALE taxonomy. TAO, 1(2), 100018. https://doi.org/10.1016/j.tao.2025.100018
Yeni, S., Nijenhuis-Voogt, J., Saeli, M., Barendsen, E., & Hermans, F. (2024). Computational thinking integrated in school subjects – A cross-case analysis of students’ experiences. International Journal of Child-Computer Interaction, 42, 100696. https://doi.org/10.1016/j.ijcci.2024.100696
Yim, I. H. Y., & Su, J. (2025). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. Journal of Computers in Education, 12(1), 93–131. https://doi.org/10.1007/s40692-023-00304-9
Yuana, R. A., Sajidan, S., Wiranto, W., & Nizam, M. (2025). Strategies for integrating computational thinking and scientific approaches in programming education: a systematic literature review. Discover Education, 4(1), 371. https://doi.org/10.1007/s44217-025-00834-7