Moh. Badrus Sholeh Arif

Universitas Jember, Indonesia

Aris Singgih Budiarso

Universitas Jember, Indonesia

Naomi Dias Laksita Dewi

Universitas Jember, Indonesia

Vivi Darmayanti

Universitas Jember, Indonesia

DOI: https://doi.org/10.19184/jipsd.v13i1.6002

ABSTRAK

Pengintegrasian berpikir komputasional (CT) dalam pembelajaran IPA di Sekolah Dasar merupakan kebutuhan mendesak di era digital. Meskipun Buku Koding dan Kecerdasan Artifisial (KKA) kelas 5 dalam Kurikulum Merdeka memuat konsep CT, analisis mengenai model integrasinya dengan IPA belum tersedia. Penelitian ini bertujuan menganalisis konsep CT dalam buku KKA kelas 5, mengidentifikasi potensi integrasinya dengan materi IPA dalam buku IPAS kelas 3-6, serta mengembangkan matriks integrasi sebagai panduan praktis. Penelitian ini menggunakan pendekatan kualitatif dengan metode analisis konten. Penelitian ini mengkaji Buku Siswa KKA dan IPA. Analisis dilakukan melalui pengkodean lima konsep CT dan penilaian potensi integrasi menggunakan skala Likert. Hasil penelitian mengungkap 20 aktivitas CT dalam buku KKA dengan distribusi dominan pada pengenalan pola (35%) dan algoritma (30%). Rata-rata potensi integrasi dengan IPA mencapai skor tinggi sebesar 4,25. Sebanyak 28 topik IPA teridentifikasi memiliki potensi CT, dengan konsentrasi tertinggi di kelas 5 (42,9%). Luaran penelitian ini berupa matriks integrasi yang mencakup rancangan pembelajaran konkret seperti "Robot Siklus Air" dan "KA Klasifikasi Hewan". Kesimpulannya, buku KKA kelas 5 memiliki potensi signifikan sebagai sumber penguatan CT dalam IPA. Matriks yang dihasilkan dapat menjadi panduan praktis bagi guru untuk merancang pembelajaran berbasis CT melalui pendekatan unplugged.

Kata kunci: Analisis konten, Berpikir komputasional, Integrasi kurikulum, IPA, KKA, Sekolah dasar

ABSTRACT 

The integration of computational thinking (CT) into elementary science education is increasingly important in the digital era. Although the Grade 5 Coding and Artificial Intelligence (Koding dan Kecerdasan Artifisial/KKA) textbook in the Merdeka Curriculum introduces CT concepts, systematic analyses of its integration with science learning remain limited. This study aims to analyze CT concepts embedded in the Grade 5 KKA textbook, identify their integration potential with science content in Grades 3–6 IPAS textbooks, and develop an integration matrix as a practical instructional guide. A qualitative content analysis approach was employed by examining KKA and science (IPAS) student textbooks. Data were analyzed through coding of five CT concepts and assessment of integration potential using a Likert scale. The findings revealed 20 CT-related activities in the KKA textbook, dominated by pattern recognition (35%) and algorithms (30%). The average integration potential with science learning reached a high score of 4.25. In total, 28 science topics were identified as having CT integration potential, with the highest concentration at Grade 5 (42.9%). The study produced an integration matrix featuring concrete instructional designs such as “Water Cycle Robot” and “Animal Classification AI.” Overall, the Grade 5 KKA textbook shows significant potential for strengthening CT in elementary science learning through unplugged approaches.

Keywords: Coding and artificial intelligence, Computational thinking, Content analysis, Curriculum integration, Elementary school, Science education.

REFERENCES

Anderson, C. A., Bushman, B. J., Bandura, A., Braun, V., Clarke, V., Bussey, K., Bandura, A., Carnagey, N. L., Anderson, C. A., Ferguson, C. J., Smith, J. a, Osborn, M., Willig, C., & Stainton-Rogers, W. (2014). Using thematic analysis in psychology Using thematic analysis in psychology. Psychiatric Quarterly, 0887(1), 37–41. http://www.ncbi.nlm.nih.gov/pubmed/11752478

Angeli, C., & Giannakos, M. (2020). Computational thinking education: Issues and challenges. Computers in Human Behavior, 105. https://doi.org/10.1016/j.chb.2019.106185

Arifin, C., Fedora, & Sulthony, M. M. M. (2025). Koding dan Kecerdasan Artifisial untuk SD/MI Kelas V. Kementerian Pendidikan Dasar dan Menengah Republik Indonesia Dikeluarkan. https://books.google.co.id/books?hl=en&lr=&id=qIp0EQAAQBAJ&oi=fnd&pg=PR1&dq=kecerdasan+artifisial&ots=IZ0o68rBCV&sig=3PB1icQFmNJ6A5L5f2yuTml9spc&redir_esc=y#v=onepage&q=kecerdasan artifisial&f=false

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12. ACM Inroads, 2(1), 48–54. https://doi.org/10.1145/1929887.1929905

Bell, T., & Vahrenhold, J. (2018). CS unplugged—How is it used, and does it work? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 11011 LNCS. Springer International Publishing. https://doi.org/10.1007/978-3-319-98355-4_29

Bers, M. (2020). Coding as a Playground: Programming and Computational Thinking in the Early Childhood Classroom. In Coding as a Playground: Programming and Computational Thinking in the Early Childhood Classroom. https://doi.org/10.4324/9781003022602

Bocconi, S., Chioccariello, A., & Earp, J. (2018). the Nordic Approach To Introducing Computational Thinking and Programming in Compulsory Education. National Research Council of Italy, Institute for Educational Technology (CNR-ITD), 9(9), 574–575. https://doi.org/https://doi.org/10.17471/54007

Brackmann, C. P., Moreno-León, J., Román-González, M., Casali, A., Robles, G., & Barone, D. (2017). Development of computational thinking skills through unplugged activities in primary school. ACM International Conference Proceeding Series, 65–72. https://doi.org/10.1145/3137065.3137069

Branch, R. M. (2009). Instructional Design: The ADDIE Approach. In Journal GEEJ (Vol. 7, Issue 2). Springer US. https://doi.org/10.1007/978-0-387-09506-6

Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Annual American Educational Research Association Meeting, Vancouver, BC, Canada, 1–25. http://web.media.mit.edu/~kbrennan/files/Brennan_Resnick_AERA2012_CT.pdf

Fauzi, A., Kusumah, Y., Nurlaelah, E., & Juandi, D. (2023). Computational thinking education in K-12 artificial intelligence literacy and physical computing Computational thinking education in K-12 artificial intelligence literacy and physical computing , edited by Siu-Cheung Kong and Harold Abelson, Cambridge, Th. Education 3-13, 53, 1–2. https://doi.org/10.1080/03004279.2023.2271019

Fitri, A., Kusumawardhani, A., Fatimah, K., Setiningsih, N. I., Nursya’bani, K. K., & Rasa, A. A. (2023). Ilmu Pengetahuan Alam dan Sosial untuk SD/MI Kelas IV (Edisi Revisi) Penulis.

Fitri, A., Oktora, A. H., Tresnawati, E., & Wahyudi, M. J. (2025). Ilmu Pengetahuan Alam dan Sosial untuk SD/MI Kelas VI (Edisi Revisi). Kementerian Pendidikan Dasar dan Menengah Dikeluarkan. https://buku.kemdikbud.go.id

Fitri, A., Rasa, A. A., Oktora, A. H., & Yasella, M. (2021). Ilmu Pengetahuan Alam dan Sosial untuk SD/MI kelas III. Pusat Perbukuan Badan Standar, Kurikulum, dan Asesmen Pendidikan Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi.

Ghaniem, A. F., Oktora, A. H., Wahyudi, M. J., & Tresnasari, E. (2023). Ilmu Pengetahuan Alam dan Sosial untuk SD/MI Kelas V (Edisi Revisi). Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi Dikeluarkan.

Grover, S., & Pea, R. (2017). Computational Thinking: A Competency Whose Time Has Come. https://doi.org/10.5040/9781350057142.ch-003

Hsu, T., Chang, S.-C., & Hung, Y.-T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126. https://doi.org/10.1016/j.compedu.2018.07.004

Lye, S., & Koh, J. (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., Huberman, M., & Saldaña, J. (2013). Qualitative Data Analysis: A Methods Sourcebook. In Zeitschrift fur Personalforschung (Vol. 28).

Mu’ti, A. (2025). Naskah Akademik Pembelajaran Koding dan Kecerdasan Artifisial Pada Pendidikan Dasar dan Menengah (pp. 1–110). Badan Standar, Kurikulum, dan Asesmen Pendidikan Kementerian Pendidikan Dasar dan Menengah Republik Indonesia. https://kodingka.kemendikdasmen.go.id/

Pratiwi, H. Y., Sujito, S., Sunardi, S., & Sayyadi, M. (2024). The Learning Revolution: Investigating the Use of Technology to Explore Mathematical Physics Learning. Kasuari: Physics Education Journal (KPEJ), 7(1), 216–226. http://jurnal.unipa.ac.id/index.php/kpej

Sáez-López, J.-M., Román-González, M., & Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education, 97, 129–141. https://doi.org/10.1016/j.compedu.2016.03.003

Selby, C. (2013). Computational Thinking : The Developing Definition. ITiCSE Conference 2013, 5–8.

Sengupta, P., Kinnebrew, J., Basu, S., Biswas, G., Clark, D., Clark, D., Kinnebrew, J., Basu, S., & Biswas, G. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18, 351–380. https://doi.org/10.1007/s10639-012-9240-x

Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020). Assessing computational thinking: A systematic review of empirical studies. Computers & Education, 148, 103798. https://doi.org/10.1016/j.compedu.2019.103798

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining Computational Thinking for Mathematics and Science Classrooms. Journal of Science Education and Technology, 25. https://doi.org/10.1007/s10956-015-9581-5

Wing, J. (2006). Computational Thinking. Communications of the ACM, 49, 33–35. https://doi.org/10.1145/1118178.1118215

Yadav, A., Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55–62. https://doi.org/10.1145/2994591