Problem-Solving and Computational Thinking Practices: Lesson Learned from The Implementation of ExPRession Model

Natalya Limbong, Kartini Herlina, Hervin Maulina, Abdurrahman Abdurrahman

Abstract


Computational thinking ability is one of today's problem-solving methods that can be applied in physics learning. However, it is not yet known by most teachers so it has not been applied optimally in learning activities. This study aims to identify students' problem-solving and computational thinking abilities in solving well-structure physics problems. The subject of this study was the eleven grade majoring in natural science of SMAN 1 Bangunrejo. This type of research is descriptive research. The data used to analyze the students' problem-solving and computational thinking abilities were obtained from the essay test. Based on the results of descriptive analysis, it can be concluded that there is a relationship between students' problem-solving abilities and students' computational thinking abilities. In making a useful description, abstraction and decomposition abilities are needed, while to determine the physics approach and specific application of physics, generalization abiliy are needed. In solving mathematical procedures, algorithm ability are needed and to find out logical progressions, debugging ability are needed.

Keywords


Problem-Solving Ability; Computational Thinking Ability; Well-Structure Physics Problem; ExPRession Learning Model

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References


Trilling, B., & Fadel, C. (2009). 21st Century Skills_ Learning for Life in Our Times, 1st ed. San Francisco: Jossey-Bass A Wiley Imprint.

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community?. Acm Inroads, 2(1): 48-54.

Doleck, T., Bazelais, P., Lemay, D. J., Saxena, A., & Basnet, R. B. (2017). Algorithmic thinking, cooperativity, creativity, critical thinking, and problem solving: exploring the relationship between computational thinking skills and academic performance. Journal of Computers in Education, 4(4): 355-369.

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3): 33-35.

Wing, J. M. (2014). Computational thinking benefits society. 40th anniversary blog of social issues in computing, 2014, 26.

Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education (TOCE), 14(1): 1-16.

Labusch, A., Eickelmann, B., & Vennemann, M. (2019). Computational thinking processes and their congruence with problem-solving and information processing. In Computational thinking education (pp. 65-78). Springer, Singapore.

Ansori, M. (2020). Pemikiran Komputasi (Computational Thinking) dalam Pemecahan Masalah. Dirasah: Jurnal Studi Ilmu Dan Manajemen Pendidikan Islam, 3(1): 111-126.

Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking-A guide for teachers.

Prince, M., & Felder, R. (2007). The many faces of inductive teaching and learning. Journal of college science teaching, 36(5): 14-20.

Herlina, K. (2020). Model Pembelajaran ExPRession untuk Membangun Model Mental dan Kemampuan Problem Solving. Yogyakarta: Graha Ilmu.

Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and instruction, 16(3): 183-198.

Polya, G. (1957). How to Solve It: A new Aspect of Mathematical Method, Second edi. Princeton: Princeton University Press.

Docktor, J. L., Dornfeld, J., Frodermann, E., Heller, K., Hsu, L., Jackson, K. A., ... & Yang, J. (2016). Assessing student written problem solutions: A problem-solving rubric with application to introductory physics. Physical review physics education research, 12(1): 010130.

Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Journal of Educational Technology & Society, 19(3): 47-57.

Herlina, K., Nur, M., & Widodo, W. (2017, January). Development of Optics Learning Model to Build Mental Models and Problem Solving Ability. In International Conference on Mathematics and Science Education (pp. 53-59). Atlantis Press.

Herlina, K., Widodo, W., Nur, M., & Agustini, R. (2016). Penerapan Model Pembelajaran “ExPRession” untuk Meningkatkan Kemampuan Problem Solving: Secara Numerik dan Secara Eksperimen.

Gautam, A., Bortz, W., & Tatar, D. (2020, February). Abstraction through multiple representations in an integrated computational thinking environment. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (pp. 393-399).

Maharani, S., Kholid, M. N., Pradana, L. N., & Nusantara, T. (2019). Problem solving in the context of computational thinking. Infinity Journal, 8(2): 109-116.

Reiss, K., & Törner, G. (2007). Problem solving in the mathematics classroom: The German perspective. ZDM, 39(5): 431-441.

Opfermann, M., Schmeck, A., & Fischer, H. E. (2017). Multiple representations in physics and science education–why should we use them?. In Multiple representations in physics education (pp. 1-22). Springer, Cham.

Selby, C., & Woollard, J. (2013). Computational thinking: the developing definition.

Maulina, H., Abdurrahman, A., & Sukamto, I. (2021). How to Bring Computational Thinking Approach to The Non-Computer Science Student’s Class???. Jurnal Pembelajaran Fisika, 9(1): 101-112.




DOI: http://dx.doi.org/10.26737/jipf.v8i1.3042

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