The Effectiveness Analysis of Computational Thinking Patterns and Levels of Students’ Meta-Cognitive Awareness in Solving Learning Problems

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Sudadi Sudadi
Enos Lolang
Joko Ariawan
Iwan Henri Kusnadi
Misbahul Munir

Abstract

The goal of this study is to characterize students' computational thinking skills in problem-solving in terms of their degree of metacognition awareness. The study is descriptive and qualitative in nature. The participants were selected using purposive sampling, comprising of two students with reflective metacognitive awareness, two students with strategic metacognitive awareness, two students with aware metacognitive awareness, and two students with tacit metacognitive awareness. The data was collected through written tests and interviews and analyzed based on the computational thinking indicators. The findings reveal that the computational thinking abilities of students who use metacognitive awareness in problem-solving are abstraction, pattern recognition, and decomposition. Furthermore, students with strategic metacognitive awareness exhibit proficiency in abstraction and pattern recognition. Additionally, students who use metacognition awareness through abstraction or decomposition exhibit computational thinking abilities when solving problems. However, students with tacit metacognitive awareness do not meet the computational thinking indicators while solving problems.

Article Details

How to Cite
Sudadi, S., Lolang, E., Ariawan, J., Kusnadi, I., & Munir, M. (2023). The Effectiveness Analysis of Computational Thinking Patterns and Levels of Students’ Meta-Cognitive Awareness in Solving Learning Problems. Journal on Education, 6(1), 2166- 2171. https://doi.org/10.31004/joe.v6i1.3217
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Articles

References

Cahdriyana, R. A. & Richardo, R. (2020). Computational Thinking in Mathematics Learning. Literasi, 9(1), 50-56.
Chairani, Z. (2016). Student Metacognition in Mathematical Problem Solving. Yogyakarta: Deepublisher.
Ramli, A., Sudadi, S., & Afendi, A. R. (2023). Evaluation implementation curriculum in productive SMK Negeri 1 Samarinda. Jurnal Pendidikan dan Pengajaran, 2(1), 1-16.
Danoebroto, S. W. & Listiani, C. (2020). Analysis of Elementary School Teachers' Computational Thinking in Solving Scale-Related Problems. Jurnal Edukasi Matematika, 11 (1), 1-11.
Hartarto, A. (2018). Making Indonesia 4.0. Jakarta.
Dianto, A., Sultan, L. P., Hidayah, M., & Sudadi, S. (2023). Penerapan Program Tahfidzul Qur’an di SMP Islamic Center Samarinda. Borneo Journal of Islamic Education, 3(1), 89-100.
Kuzle, A. (2013). Patterns of Metacognitive During Problem Solving in Dynamic Geometry Environment. International Electronic Journal of Mathematics Education, 8(1), 20-39.
Madaling, M., Lasino, L., Munir, M., Nainggolan, H., Ulimaz, A., & Weraman, P. (2023). Efektivitas Penggunaan Google Classroom terhadap Hasil Belajar. Jurnal Pendidikan Dan Kewirausahaan, 11(2), 672 - 684.
Maharani, S. et al. (2019). Problem Solving in the Context of Computational thinking. Infinity, 8(2), 109-116.
Ningrum, R. K. (2021). Validity and Reliability of Motivated Strategies for Learning Questionnaire (MSLQ) in Medical Students. Pendipa Journal of Science Education, 5(3), 421-425.
Wing, J. M. (2006). Computational Thinking. Communications of the ACM, 49(3), 33-35.

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