Global Trends in Computational Thinking Research in Physics Learning: A Systematic Literature Review

Inayatun Diraya; Sentot Kusairi; Parno Parno

doi:10.20527/jipf.v9i1.14262

Global Trends in Computational Thinking Research in Physics Learning: A Systematic Literature Review

Inayatun Diraya, Sentot Kusairi, Parno Parno

Abstract

This research examines the global trends regarding applying computational thinking (CT) in physics learning through a Systematic Literature Review (SLR) approach. By analyzing 30 selected articles published in 2019-2024, this study aims to provide insight into the types of research, subjects, instruments, physics materials, and supporting media used. The results showed that most studies focused on developing CT-based learning products, such as interactive modules and simulations, which were predominantly applied to high school students with materials such as electricity, temperature, and heat. Frequently used media include Scratch, Arduino, and Visual Python, which are proven to improve students' critical thinking, collaboration, and algorithmic skills. However, CT implementation is faced with challenges such as limited technology facilities, teacher training needs, and the complexity of curriculum integration. This research recommends the exploration of problem-, project-, and game-based learning approaches to support the development of CT at different levels of education. The results are expected to be the basis for developing more innovative and effective learning strategies to face the challenges of the 21st century.

Keywords

Computational thinking; Physics; Systematic literature

Full Text:

PDF

References

Akmam, A., Anshari, R., Jalinus, N., & Amran, A. (2019). Factors influencing the critical and creative thinking skills of college students in computational physics courses. Journal of Physics: Conference Series, 1317(1), 012172. https://doi.org/10.1088/1742-6596/1317/1/012172

Akmam, A., Hidayat, R., Mufit, F., Anshari, R., & Jalinus, N. (2023). Effect of generative learning models based on cognitive conflict on students’ creative thinking processes based on metacognitive. Journal of Physics: Conference Series, 2582(1), 012058. https://doi.org/10.1088/1742-6596/2582/1/012058

Amenyo, J.-T., Kpo, W., 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

Amrizaldi, A., Yuliati, L., Supriana, E., Diantoro, M., & Halim, L. (2024). Exploration of computational thinking skills: A case study of islamic senior high school students. Momentum: Physics Education Journal, 8(2), 210-216.

Anderson, A., Pressler, P., & Lane, W. B. (2022). Coding expediently: A computationally situated epistemic game. 44–50. https://www.per-central.org/items/detail.cfm?ID=16207

Anfusiyah, D., Samsudin, A., & Danawan, A. (2024). Implementation of conceptual change model-computational thinking (ccm-ct) to increase students’ conceptual understanding in pascal’s law. Jurnal Ilmiah Pendidikan Fisika, 8(1), 44-57.

Ashraf, M. A., Yang, M., Zhang, Y., Denden, M., Tlili, A., Liu, J., Huang, R., & Burgos, D. (2021). A Systematic review of systematic reviews on blended learning: trends, gaps and future directions. Psychology Research and Behavior Management, 14(null), 1525–1541. https://doi.org/10.2147/PRBM.S331741

Benek, İ., & Akçay, B. (2022). The effects of socio-scientific STEM activities on 21st century skills of middle school students. Participatory Educational Research, 9(2), Article 2. https://doi.org/10.17275/per.22.27.9.2

Berk, G., & Gülcü, A. (2024). The effect of computer-supported stem applications on secondary students’ achievement and computational thinking skills. Participatory Educational Research, 11(4), Article 4. https://doi.org/10.17275/per.24.54.11.4

Bufasi, E. (2022). Developing student’s comprehensive knowledge of physics concepts by using computational thinking activities: Effects of a 6-week intervention. International Journal of Emerging Technologies in Learning, 17(18), 161–176.

https://doi.org/10.3991/ijet.v17i18.31743

Çevik, M., Bakioğlu, B., & Temiz, Z. (2024). The effects of out-of-school learning environments on stem education: teachers’ stem awareness and 21st-century skills. Journal of Theoretical Educational Science, 17(1), Article 1. https://doi.org/10.30831/akukeg.1309078

Dewi, C. A., Erna, M., Martini, M., Haris, I., & Kundera, I. N. (2021). The effect of contextual collaborative learning based ethnoscience to increase student’s scientific literacy ability. Journal of Turkish Science Education, 18(3), 525–541. https://doi.org/10.36681/tused.2021.88

Fayanto, S. (2024). The analyze comparative of physics computational thinking skill (cts) in experiment laboratory. Qubahan Academic Journal, 4(3), 14–33. https://doi.org/10.48161/qaj.v4n3a699

Gambrell, J. (2024). Analyzing interviews on computational thinking for introductory physics students: Toward a generalized assessment. Physical Review Physics Education Research, 20(1). https://doi.org/10.1103/PhysRevPhysEducRes.20.010128

Gong, D., Yang, H. H., & Cai, J. (2020). Exploring the key influencing factors on college students’ computational thinking skills through flipped-classroom instruction. International Journal of Educational Technology in Higher Education, 17(1), 19. https://doi.org/10.1186/s41239-020-00196-0

Hadad, R. (2020). Practicing formative assessment for computational thinking in making environments. Journal of Science Education and Technology, 29(1), 162–173. https://doi.org/10.1007/s10956-019-09796-6

Handayani, I. D., Lestari, D. A. P., & Sulistyowati, S. (2023). Analisis konstanta pegas dan percepatan gravitasi ayunan sederhana dengan tracker video analysis untuk meningkatkan computational thinking. ORBITA: Jurnal Pendidikan dan Ilmu Fisika, 9(1), 155-161.

Herwinarso. (2023). Investigation of science process skills and computational thinking dispositions during the implementation of collaborative modeling-based learning in high school physics class. Journal of Education and E-Learning Research, 10(4), 753–760. https://doi.org/10.20448/jeelr.v10i4.5200

Khasyyatillah, I., & Osman, K. (2019). The development of ct-s learning module on the linear motion topic to promote computational thinking thinking. Journal of Educational Sciences, 3(3), 270. https://doi.org/10.31258/jes.3.3.p.270-280

Kumala, F., Yasa, A., Wibawa, A., & Hidayah, L. (2024). Application of the hybrid learning project STEAMER in science courses for prospective elementary school teachers: Computational thinking and creative thinking. Multidisciplinary Science Journal, 6(6), 2024113-2024223.

Latifah, S., Diani, R., & Malik, S. L. M. (2022). Icare model (introduction, connection, application, reflection, extension) in physics learning: analysis of its effect on students’ computational thinking skills based on gender. Jurnal Penelitian & Pengembangan Pendidikan Fisika, 8(2), 229-240.

Li, Y., Wang, K., Xiao, Y., & Froyd, J. E. (2020). Research and trends in STEM education: A systematic review of journal publications. International Journal of STEM Education, 7(1), 11. https://doi.org/10.1186/s40594-020-00207-6

Maharani, S., Nusantara, T., As’ari, A. R., & Qohar, A. (2020). Computational thinking pemecahan masalah di abad ke-21. Madiun: Perpustakan Nasional: Katalog Dalam Terbitan (KDT).

Maharani, S., Susanti, V. D., Andari, T., Krisdiana, I., & Astuti, I. P. (2023). Computational thinking (ct)-based student worksheet to improve the mathematical literacy of mathematics prospective teacher. AL-ISHLAH: Jurnal Pendidikan, 15(3), 2690-2702.

Marifah, S. N. (2022). Systematic literatur review: Integrasi conputational thinking dalam kurikulum sekolah dasar di indonesia. COLLASE (Creative of Learning Students Elementary Education), 5(5), 928–938. https://doi.org/10.22460/collase.v5i5.12148

Marín, V. I., Duart, J. M., Galvis, A. H., & Zawacki-Richter, O. (2018). Thematic analysis of the international journal of educational Technology in Higher Education (ETHE) between 2004 and 2017. International Journal of Educational Technology in Higher Education, 15(1), 8. https://doi.org/10.1186/s41239-018-0089-y

Martins, I., & Baptista, M. (2024). Teacher professional development in integrated steam education: A study on its contribution to the development of the pck of physics teachers. Education Sciences, 14(2). https://doi.org/10.3390/educsci14020164

Muliyati, D. (2022). Development and evaluation of granular simulation for integrating computational thinking into computational physics courses. Education and Information Technologies, 27(2), 2585–2612. https://doi.org/10.1007/s10639-021-10724-8

Pérez, A. (2018). A Framework for computational thinking dispositions in mathematics education. https://doi.org/10.5951/jresematheduc.49.4.0424

Rahman, A. A. (2022). Integrasi computational thinking dalam model edp-stem untuk meningkatkan kemampuan berpikir kritis siswa smp. Jurnal Didaktika Pendidikan Dasar, 6(2). https://doi.org/10.26811/didaktika.v6i2.409

Rahmawati, S., Fauzi, A., & Supurwoko, S. (2024). Computational-thinking based learning activities for physics in indonesian new curriculum through a student worksheet development. JIPF (Jurnal Ilmu Pendidikan Fisika), 9(3), 426-437.

Rother, E. T. (2007). Systematic literature review X narrative review. Acta Paulista de Enfermagem, 20, v–vi. https://doi.org/10.1590/S0103-21002007000200001

Saputra, A., Saprudin, S., & Sambiri, U. (2023). The analysis of pre-service physics teachers’ computational thinking skills in designing computer simulations of projectile motion using the scratch application. EduLine: Journal of Education and Learning Innovation, 3(4), 629-637

Sari, A. D. I. S. A. D. I., Herman, T., Sopandi, W., & Jupri, A. (2023). A Systematic Literature Review (SLR): Implementasi Audiobook pada Pembelajaran di Sekolah Dasar. Jurnal Elementaria Edukasia, 6(2). https://doi.org/10.31949/jee.v6i2.5238

Seiter, L., & Foreman, B. (2013). Modeling the learning progressions of computational thinking of primary grade students. Proceedings of the Ninth Annual International ACM Conference on International Computing Education Research, 59–66. https://doi.org/10.1145/2493394.2493403

Sugiyono, S. (2010). Metode penelitian kuantitatif dan kualitatif dan R&D. Alfabeta Bandung, 170–182.

Syafril, S. (2022). Prospective science teachers’ self-confidence in computational thinking skills. Jurnal Pendidikan IPA Indonesia, 11(1), 119–128. https://doi.org/10.15294/jpii.v11i1.33125

Tofel-Grehl, C. (2022). Thinking thru making: Mapping computational thinking practices onto scientific reasoning. Journal of Science Education and Technology, 31(6), 730–746. https://doi.org/10.1007/s10956-022-09989-6

Ulfa, E., Wahyuni, S., & Ridlo, Z. (2023). Development of e-module-based pjbl to develop computational thinking skills integrategration with ccr implementation in science education. JPPS (Jurnal Penelitian Pendidikan Sains), 12(2), 176-191.

Weller, D. P. (2022). Development and illustration of a framework for computational thinking practices in introductory physics. Physical Review Physics Education Research, 18(2). https://doi.org/10.1103/PhysRevPhysEducRes.18.020106

Wu, S.-Y., & Su, Y.-S. (2021). Visual programming environments and computational thinking performance of fifth- and sixth-grade students. Journal of Educational Computing Research, 59(6), 1075–1092. https://doi.org/10.1177/0735633120988807

Wulandari, T. D., Listaji, P., Sulaiman, T., Jaafar, W. M. W., & Rahim, S. S. A. (2024). Development of stem-based science educational game using scratch to train computational thinking skill for secondary school students. Jurnal Pendidikan Sains Indonesia, 12(4), 867-884. https://jurnal.usk.ac.id/JPSI/article/view/39893

Yeni, S. (2024). Computational thinking integrated in school subjects – A cross-case analysis of students’ experiences. International Journal of Child-Computer Interaction, 42(Query date: 2024-11-29 11:13:13). https://doi.org/10.1016/j.ijcci.2024.100696

Yin, Y. (2020). Improving and assessing computational thinking in maker activities: the integration with physics and engineering learning. Journal of Science Education and Technology, 29(2), 189–214. https://doi.org/10.1007/s10956-019-09794-8

Yin, Y. (2022). Developing effective and accessible activities to improve and assess computational thinking and engineering learning. Educational Technology Research and Development, 70(3), 951–988. https://doi.org/10.1007/s11423-022-10097-w

Zakwandi, R. (2024). A two-tier computerized adaptive test to measure student computational thinking skills. Education and Information Technologies, 29(7), 8579–8608. https://doi.org/10.1007/s10639-023-12093-w

DOI: https://doi.org/10.20527/jipf.v9i1.14262