Exploration of computational thinking skills: A case study of islamic senior high school students
Abstract
This study aims to identify madrasah students' Computational Thinking (CT) skills on temperature and heat material. This research was conducted using a qualitative descriptive method using 5 CT-test essay questions to 53 grade XI IPA one of the Islamic Senior High School in Probolinggo. Data analysis techniques in research consist of 3 stages: data reduction, data presentation, and conclusions. Data analysis showed indicators of students' CT skills on a scale of 5 consisting of decomposition 3.90, recognition pattern 3.63, abstraction 2.83, and algorithm 2.37. Based on the study’s results, it can be concluded that the CT skills of the Islamic Senior High School in Probolinggo at temperature and heat are included in the medium category. Several indicators of CT skills are still challenging for students, especially in developing algorithms and abstractions. Some students need help identifying the steps to solve complex problems in understanding abstraction concepts and algorithms. In this case, practice, intensive tutoring, and student collaboration can help improve students' skills to overcome these difficulties.
References
Aminah, N., Sukestiyarno, Y. L., Wardono Wardono, & Cahyono, A. N. (2022). Computational thinking process of prospective mathematics teacher in solving diophantine linear equation problems. European Journal of Educational Research, 11(3), 1495–1507. https://doi.org/10.12973/eu-jer.11.3.1495
Annisa, N., Rikayana, A. E., Cahyo, S. D., Pambudi, S., Wijayanti, M., Yuniarti, Y., Zayadi, N. H. B., Adlawan, H. A., & Sukardi, R. R. (2023). Prospective elementary school teachers perceptions on the use of technology in natural science learning. Journal of Environment and Sustainability Education, 1(1), 27–35. https://doi.org/10.62672/joease.v1i1.7
Atqiya, N., Yuliati, L., & Diantoro, M. (2021). Argument-driven inquiry for STEM education in physics: Changes in students’ scientific reasoning patterns. AIP Conference Proceedings, 2330(March). https://doi.org/10.1063/5.0043636
Batlolona, J. R., & Souisa, H. F. (2020). Problem based learning: Students’ mental models on water conductivity concept. International Journal of Evaluation and Research in Education, 9(2), 269–277. https://doi.org/10.11591/ijere.v9i2.20468
Chevalier, M., Giang, C., Piatti, A., & Mondada, F. (2020). Fostering computational thinking through educational robotics: a model for creative computational problem solving. International Journal of STEM Education, 7(1). https://doi.org/10.1186/s40594-020-00238-z
Critten, V., Hagon, H., & Messer, D. (2022). Can pre-school children learn programming and coding through guided play activities? A case study in computational thinking. Early Childhood Education Journal, 50(6), 969–981. https://doi.org/10.1007/s10643-021-01236-8
Del Olmo-Muñoz, J., Bueno-Baquero, A., Cózar-Gutiérrez, R., & González-Calero, J. A. (2023). Exploring gamification approaches for enhancing computational thinking in young learners. Education Sciences, 13(5). https://doi.org/10.3390/educsci13050487
Delal, H., & Oner, D. (2020). Developing middle school students’ computational thinking skills using unplugged computing activities. Informatics in Education, 19(1), 1–13. https://doi.org/10.15388/INFEDU.2020.01
Docktor, J., & Heller, K. (2009). Assessment of student problem solving processes. AIP Conference Proceedings, 1179, 133–136. https://doi.org/10.1063/1.3266696
Etikamurni, D. P., Anggraeni, A., Diantoro, M., & Sutopo. (2020). Improving students’ problem solving skills of heat and temperature through modeling instruction. AIP Conference Proceedings, 2215(April). https://doi.org/10.1063/5.0003651
Fanchamps, N. L. J. A., Slangen, L., Hennissen, P., & Specht, M. (2021). The influence of SRA programming on algorithmic thinking and self-efficacy using Lego robotics in two types of instruction. International Journal of Technology and Design Education, 31(2), 203–222. https://doi.org/10.1007/s10798-019-09559-9
George-Reyes, C. E. (2023). Imbricación del pensamiento computacional y la alfabetización digital en la educación. Modelación a partir de una revisión sistemática de la literatura. Revista Española de Documentación Científica, 46(1), e345. https://doi.org/10.3989/redc.2023.1.1922
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). https://doi.org/10.1186/s41239-020-00196-0
Kong, S., & Lai, M. (2022). Computers & education validating a computational thinking concepts test for primary education using item response theory : An analysis of students ’ responses. Computers & Education, 187(August 2021), 104562. https://doi.org/10.1016/j.compedu.2022.104562
Lee, I., & Malyn-Smith, J. (2020). Computational tinking integration patterns along the framework defining computational thinking from a disciplinary perspective. Journal of Science Education and Technology, 29(1), 9–18. https://doi.org/10.1007/s10956-019-09802-x
Markandan, N., Osman, K., & Halim, L. (2022). Integrating computational thinking and empowering metacognitive awareness in stem education. Frontiers in Psychology, 13(June), 1–18. https://doi.org/10.3389/fpsyg.2022.872593
Mayub, A., Suryani, E., & Farid, M. (2020). Implementation of discovery learning model based on calor characteristic bricks mixed by (Durio zibethinus) and coconut (cocos nucifera) skin to improve students’ cognitive learning outcomes. In Jurnal Pendidikan IPA Indonesia (Vol. 9, Issue 2, pp. 287–293). https://doi.org/10.15294/jpii.v9i2.23803
Nurul Fazita, M. R., Jayaraman, K., Bhattacharyya, D., Mohamad Haafiz, M. K., Saurabh, C. K., Hazwan Hussin, M., & Abdul Khalil, H. P. S. (2016). Green composites made of bamboo fabric and poly (lactic) acid for packaging applications-a review. Materials, 9(6). https://doi.org/10.3390/ma9060435
Palts, T., & Pedaste, M. (2020). A model for developing computational thinking skills. Informatics in Education, 19(1), 113–128. https://doi.org/10.15388/INFEDU.2020.06
Parno, Yuliati, L., Supriana, E., Taufiq, A., Ali, M. B., Widarti, A. N., & Azizah, U. (2020). The Influence of STEM-Integrated 7E Learning Cycle on Students’ Creative Thinking Skills in The Topic of Temperature and Heat. Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019. https://doi.org/10.4108/eai.12-10-2019.2296493
Piedade, J., Dorotea, N., Pedro, A., & Matos, J. F. (2020). On teaching programming fundamentals and computational thinking with educational robotics: A didactic experience with pre-service teachers. Education Sciences, 10(9), 1–15. https://doi.org/10.3390/educsci10090214
Priyadi, R., Diantoro, M., Parno, P., & Helmi, H. (2019). An Exploration of Students’ Mental Models on Heat and Temperature: A Preliminary Study. Jurnal Penelitian Fisika Dan Aplikasinya (JPFA), 9(2), 114. https://doi.org/10.26740/jpfa.v9n2.p114-122
Saidin, N. D., Khalid, F., Martin, R., Kuppusamy, Y., & Munusamy, N. A. P. (2021). Benefits and challenges of applying computational thinking in education. International Journal of Information and Education Technology, 11(5), 248–254. https://doi.org/10.18178/ijiet.2021.11.5.1519
Saxena, A., Lo, C. K., Hew, K. F., & Wong, G. K. W. (2020). Designing unplugged and plugged activities to cultivate computational thinking: an exploratory study in early childhood education. Asia-Pacific Education Researcher, 29(1), 55–66. https://doi.org/10.1007/s40299-019-00478-w
Su, J., & Yang, W. (2023). A systematic review of integrating computational thinking in early childhood education. Computers and Education Open, 4(December 2022), 100122. https://doi.org/10.1016/j.caeo.2023.100122
Sugioyono. (2013). Metode penelitian penelitian pendidikan pendekatan kuantitaif, kualitatif, dan R&D. Alfabeta.
Sujito, S., Pebriana, I. N., Pratiwi, H. Y., Hayyi, A., Masjkur, K., Asim, A., & Sutopo, S. (2018). Students Misconception: the Developing of Socratic Dialogue Media on Temperature and Heat. Jurnal Pena Sains, 5(2), 87. https://doi.org/10.21107/jps.v5i2.4551
Sukarelawan, M. I., Sulisworo, D., Jumadi, Kuswanto, H., & Rofiqah, S. A. (2021). Heat and temperature metacognition awareness inventory: A confirmatory factor analysis. International Journal of Evaluation and Research in Education, 10(2), 389–395. https://doi.org/10.11591/ijere.v10i2.20917
Sulman, F. F., Yuliati, L. L., Kusairi, S. S., & ... (2023). Investigating concept mastery of physics students during online lectures through Rasch models on force and motion materials. Jurnal Inovasi …, 9(1), 95–106.
Taggart, G., Ridley, R., Peter, R., & Benefield, P. (2002). Thinking skills in the early years. National Foundation for Educational Research, 1–63.
Ulus, B., & Oner, D. (2020). Fostering middle school students’ knowledge integration using the web-based inquiry science environment (WISE). Journal of Science Education and Technology, 29(2), 242–256. https://doi.org/10.1007/s10956-019-09809-4
Weese, J. L., & Feldhausen, R. (2017). STEM outreach: Assessing computational thinking and problem solving. ASEE Annual Conference and Exposition, Conference Proceedings, 2017-June. https://doi.org/10.18260/1-2--28845
Wegerif, R. (2017). Literature review in thinking skills, technology and learning literature review in thinking skills, technology and rearning REPORT 2: FUTURELAB SERIES. Technology and Learning. A NESTA Futurelab Series-Report, 2, 1–44.
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(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5
Wing, J. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
Yang, Y., Hu, L., Zhang, R., Zhu, X., & Wang, M. (2021). Investigation of students’ short-term memory performance and thermal sensation with heart rate variability under different environments in summer. Building and Environment, 195(February), 107765. https://doi.org/10.1016/j.buildenv.2021.107765
Yeo, J., Lim, E., Tan, K. C. D., & Ong, Y. S. (2021). The efficacy of an image-to-writing approach to learning abstract scientific concepts: temperature and heat. International Journal of Science and Mathematics Education, 19(1), 21–44. https://doi.org/10.1007/s10763-019-10026-z
Zhang, Y., & Savard, A. (2023). Defining computational thinking as an evident tool in problem-solving: comparative research on chinese and canadian mathematics textbooks. ECNU Review of Education. https://doi.org/10.1177/20965311231158393
Annisa, N., Rikayana, A. E., Cahyo, S. D., Pambudi, S., Wijayanti, M., Yuniarti, Y., Zayadi, N. H. B., Adlawan, H. A., & Sukardi, R. R. (2023). Prospective elementary school teachers perceptions on the use of technology in natural science learning. Journal of Environment and Sustainability Education, 1(1), 27–35. https://doi.org/10.62672/joease.v1i1.7
Atqiya, N., Yuliati, L., & Diantoro, M. (2021). Argument-driven inquiry for STEM education in physics: Changes in students’ scientific reasoning patterns. AIP Conference Proceedings, 2330(March). https://doi.org/10.1063/5.0043636
Batlolona, J. R., & Souisa, H. F. (2020). Problem based learning: Students’ mental models on water conductivity concept. International Journal of Evaluation and Research in Education, 9(2), 269–277. https://doi.org/10.11591/ijere.v9i2.20468
Chevalier, M., Giang, C., Piatti, A., & Mondada, F. (2020). Fostering computational thinking through educational robotics: a model for creative computational problem solving. International Journal of STEM Education, 7(1). https://doi.org/10.1186/s40594-020-00238-z
Critten, V., Hagon, H., & Messer, D. (2022). Can pre-school children learn programming and coding through guided play activities? A case study in computational thinking. Early Childhood Education Journal, 50(6), 969–981. https://doi.org/10.1007/s10643-021-01236-8
Del Olmo-Muñoz, J., Bueno-Baquero, A., Cózar-Gutiérrez, R., & González-Calero, J. A. (2023). Exploring gamification approaches for enhancing computational thinking in young learners. Education Sciences, 13(5). https://doi.org/10.3390/educsci13050487
Delal, H., & Oner, D. (2020). Developing middle school students’ computational thinking skills using unplugged computing activities. Informatics in Education, 19(1), 1–13. https://doi.org/10.15388/INFEDU.2020.01
Docktor, J., & Heller, K. (2009). Assessment of student problem solving processes. AIP Conference Proceedings, 1179, 133–136. https://doi.org/10.1063/1.3266696
Etikamurni, D. P., Anggraeni, A., Diantoro, M., & Sutopo. (2020). Improving students’ problem solving skills of heat and temperature through modeling instruction. AIP Conference Proceedings, 2215(April). https://doi.org/10.1063/5.0003651
Fanchamps, N. L. J. A., Slangen, L., Hennissen, P., & Specht, M. (2021). The influence of SRA programming on algorithmic thinking and self-efficacy using Lego robotics in two types of instruction. International Journal of Technology and Design Education, 31(2), 203–222. https://doi.org/10.1007/s10798-019-09559-9
George-Reyes, C. E. (2023). Imbricación del pensamiento computacional y la alfabetización digital en la educación. Modelación a partir de una revisión sistemática de la literatura. Revista Española de Documentación Científica, 46(1), e345. https://doi.org/10.3989/redc.2023.1.1922
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). https://doi.org/10.1186/s41239-020-00196-0
Kong, S., & Lai, M. (2022). Computers & education validating a computational thinking concepts test for primary education using item response theory : An analysis of students ’ responses. Computers & Education, 187(August 2021), 104562. https://doi.org/10.1016/j.compedu.2022.104562
Lee, I., & Malyn-Smith, J. (2020). Computational tinking integration patterns along the framework defining computational thinking from a disciplinary perspective. Journal of Science Education and Technology, 29(1), 9–18. https://doi.org/10.1007/s10956-019-09802-x
Markandan, N., Osman, K., & Halim, L. (2022). Integrating computational thinking and empowering metacognitive awareness in stem education. Frontiers in Psychology, 13(June), 1–18. https://doi.org/10.3389/fpsyg.2022.872593
Mayub, A., Suryani, E., & Farid, M. (2020). Implementation of discovery learning model based on calor characteristic bricks mixed by (Durio zibethinus) and coconut (cocos nucifera) skin to improve students’ cognitive learning outcomes. In Jurnal Pendidikan IPA Indonesia (Vol. 9, Issue 2, pp. 287–293). https://doi.org/10.15294/jpii.v9i2.23803
Nurul Fazita, M. R., Jayaraman, K., Bhattacharyya, D., Mohamad Haafiz, M. K., Saurabh, C. K., Hazwan Hussin, M., & Abdul Khalil, H. P. S. (2016). Green composites made of bamboo fabric and poly (lactic) acid for packaging applications-a review. Materials, 9(6). https://doi.org/10.3390/ma9060435
Palts, T., & Pedaste, M. (2020). A model for developing computational thinking skills. Informatics in Education, 19(1), 113–128. https://doi.org/10.15388/INFEDU.2020.06
Parno, Yuliati, L., Supriana, E., Taufiq, A., Ali, M. B., Widarti, A. N., & Azizah, U. (2020). The Influence of STEM-Integrated 7E Learning Cycle on Students’ Creative Thinking Skills in The Topic of Temperature and Heat. Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019. https://doi.org/10.4108/eai.12-10-2019.2296493
Piedade, J., Dorotea, N., Pedro, A., & Matos, J. F. (2020). On teaching programming fundamentals and computational thinking with educational robotics: A didactic experience with pre-service teachers. Education Sciences, 10(9), 1–15. https://doi.org/10.3390/educsci10090214
Priyadi, R., Diantoro, M., Parno, P., & Helmi, H. (2019). An Exploration of Students’ Mental Models on Heat and Temperature: A Preliminary Study. Jurnal Penelitian Fisika Dan Aplikasinya (JPFA), 9(2), 114. https://doi.org/10.26740/jpfa.v9n2.p114-122
Saidin, N. D., Khalid, F., Martin, R., Kuppusamy, Y., & Munusamy, N. A. P. (2021). Benefits and challenges of applying computational thinking in education. International Journal of Information and Education Technology, 11(5), 248–254. https://doi.org/10.18178/ijiet.2021.11.5.1519
Saxena, A., Lo, C. K., Hew, K. F., & Wong, G. K. W. (2020). Designing unplugged and plugged activities to cultivate computational thinking: an exploratory study in early childhood education. Asia-Pacific Education Researcher, 29(1), 55–66. https://doi.org/10.1007/s40299-019-00478-w
Su, J., & Yang, W. (2023). A systematic review of integrating computational thinking in early childhood education. Computers and Education Open, 4(December 2022), 100122. https://doi.org/10.1016/j.caeo.2023.100122
Sugioyono. (2013). Metode penelitian penelitian pendidikan pendekatan kuantitaif, kualitatif, dan R&D. Alfabeta.
Sujito, S., Pebriana, I. N., Pratiwi, H. Y., Hayyi, A., Masjkur, K., Asim, A., & Sutopo, S. (2018). Students Misconception: the Developing of Socratic Dialogue Media on Temperature and Heat. Jurnal Pena Sains, 5(2), 87. https://doi.org/10.21107/jps.v5i2.4551
Sukarelawan, M. I., Sulisworo, D., Jumadi, Kuswanto, H., & Rofiqah, S. A. (2021). Heat and temperature metacognition awareness inventory: A confirmatory factor analysis. International Journal of Evaluation and Research in Education, 10(2), 389–395. https://doi.org/10.11591/ijere.v10i2.20917
Sulman, F. F., Yuliati, L. L., Kusairi, S. S., & ... (2023). Investigating concept mastery of physics students during online lectures through Rasch models on force and motion materials. Jurnal Inovasi …, 9(1), 95–106.
Taggart, G., Ridley, R., Peter, R., & Benefield, P. (2002). Thinking skills in the early years. National Foundation for Educational Research, 1–63.
Ulus, B., & Oner, D. (2020). Fostering middle school students’ knowledge integration using the web-based inquiry science environment (WISE). Journal of Science Education and Technology, 29(2), 242–256. https://doi.org/10.1007/s10956-019-09809-4
Weese, J. L., & Feldhausen, R. (2017). STEM outreach: Assessing computational thinking and problem solving. ASEE Annual Conference and Exposition, Conference Proceedings, 2017-June. https://doi.org/10.18260/1-2--28845
Wegerif, R. (2017). Literature review in thinking skills, technology and learning literature review in thinking skills, technology and rearning REPORT 2: FUTURELAB SERIES. Technology and Learning. A NESTA Futurelab Series-Report, 2, 1–44.
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(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5
Wing, J. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
Yang, Y., Hu, L., Zhang, R., Zhu, X., & Wang, M. (2021). Investigation of students’ short-term memory performance and thermal sensation with heart rate variability under different environments in summer. Building and Environment, 195(February), 107765. https://doi.org/10.1016/j.buildenv.2021.107765
Yeo, J., Lim, E., Tan, K. C. D., & Ong, Y. S. (2021). The efficacy of an image-to-writing approach to learning abstract scientific concepts: temperature and heat. International Journal of Science and Mathematics Education, 19(1), 21–44. https://doi.org/10.1007/s10763-019-10026-z
Zhang, Y., & Savard, A. (2023). Defining computational thinking as an evident tool in problem-solving: comparative research on chinese and canadian mathematics textbooks. ECNU Review of Education. https://doi.org/10.1177/20965311231158393
Authors
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. https://doi.org/10.21067/mpej.v8i2.9575
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