Students' Metacognitive Ability in Solving Mathematical Problems Based on Information Processing Theory in Discrete Mathematics Course
DOI:
https://doi.org/10.22437/edumatica.v15i2.44689Keywords:
information processing theory, mathematical problem solving, metacognitive abilitiesAbstract
This study aims to analyze students' metacognitive abilities in solving mathematical problems based on information processing theory in Discrete Mathematics courses. The study used a qualitative descriptive approach with a purposive sampling technique, involving two Mathematics Education students selected to represent the respondents' answer patterns. Data were collected through problem-solving tests using the think-aloud technique and unstructured interviews, then analyzed qualitatively with source triangulation. The results showed that both subjects were able to achieve the reflective use level on the first problem by going through all three stages of information processing. However, on the second problem, both only reached the strategy use level, with one subject experiencing pseudo in the thinking process. This finding confirms that students' metacognitive abilities vary depending on the complexity of the problem and the stages of information processing they go through. The implications of this study are the importance of developing learning strategies that encourage more consistent metacognitive regulation, as well as the opportunity to utilize technology such as eye-tracking or digital think-aloud tools to reveal students' thinking processes more objectively in future research.
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Astriani, D., Susilo, H., Suwono, H., Lukiati, B., & Purnomo, A. R. (2020). Mind mapping in learning models: A tool to improve student metacognitive skills. International Journal of Emerging Technologies in Learning, 15(6). https://doi.org/10.3991/IJET.V15I06.12657
Betul Kaya, Z., & Kepceoglu, I. (2022). Metacognitive Failures of Preservice Mathematics Teachers ın Problem Solving. Athens Journal of Sciences, 9(4). https://doi.org/10.30958/ajs.9-4-4
Braithwaite, D. W., & Sprague, L. (2021). Conceptual Knowledge, Procedural Knowledge, and Metacognition in Routine and Nonroutine Problem Solving. Cognitive Science, 45(10). https://doi.org/10.1111/cogs.13048
Celikoz, N., Erisen, Y., & Sahin, M. (2019). Cognitive Learning Theories with Emphasis on Latent Learning, Gestalt, and Information Processing Theories. Journal of Educational and Instructional Studies in the World, 9(3). Retrieved from https://eric.ed.gov/?id=ED598366
Dweck, C. S. (2008). Mindsets and Math / Science Achievement. The Opportunity Equation: Transforming Mathematics and Science Education for Citizenship and the Global Economy.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10). https://doi.org/10.1037/0003-066X.34.10.906
Fraser, K. L., Ayres, P., & Sweller, J. (2015). Cognitive load theory for the design of medical simulations. Simulation in Healthcare, Vol. 10. https://doi.org/10.1097/SIH.0000000000000097
Güner, P., & Erbay, H. N. (2021a). Metacognitive Skills and Problem-Solving. International Journal of Research in Education and Science. https://doi.org/10.46328/ijres.1594
Güner, P., & Erbay, H. N. (2021b). Prospective mathematics teachers’ thinking styles and problem-solving skills. Thinking Skills and Creativity, 40. https://doi.org/10.1016/j.tsc.2021.100827
Gustiningsi, T., Putri, R. I. I., Zulkardi, & Hapizah. (2023). Designing Hypothetical learning Trajectory for rectangular area using patchwork. AIP Conference Proceedings, 2811(1). https://doi.org/https://doi.org/10.1063/5.0142279
Gustiningsi, T., Putri, R. I. I., Zulkardi, & Hapizah. (2024). LEPscO: Mathematical Literacy Learning Environment for the Guru Penggerak Program. Journal on Mathematics Education, 15(2), 661–682. https://doi.org/https://doi.org/10.22342/jme.v15i2.pp661-682
Gustiningsi, T., Putri, R. I. I., Zulkardi, Sari, D. K., Marlina, L., Rawani, D., … Lisnani. (2022). Designing Student Worksheet on Relation and Function Material for Mathematics Learning: Jumping Task. Mathematics Teaching-Research Journal, 14(4). Retrieved from https://files.eric.ed.gov/fulltext/EJ1361679.pdf
Hastuti, I. D., Surahmat, Sutarto, & Dafik. (2020). The effect of guided inquiry learning in improving metacognitive skill of elementary school students. International Journal of Instruction, 13(4). https://doi.org/10.29333/iji.2020.13420a
Kartika, D. L., & Muhassanah, N. (2023). Profile of Student Metacognition in Solving Elementary Linear Algebra Problems Viewed from Tempo Conceptual Cognitive Style. Edumatica: Jurnal Pendidikan Matematika, 13, 234. https://doi.org/https://doi.org/10.22437/edumatica.v13i03.29693
Kholid, M. N., & Ahadiyati, A. (2022). Students’ metacognition in solving non-routine problems. Al-Jabar : Jurnal Pendidikan Matematika, 13(1). https://doi.org/10.24042/ajpm.v13i1.11776
Klang, N., Karlsson, N., Kilborn, W., Eriksson, P., & Karlberg, M. (2021). Mathematical Problem-Solving Through Cooperative Learning—The Importance of Peer Acceptance and Friendships. Frontiers in Education, 6. https://doi.org/10.3389/feduc.2021.710296
Magiera, M. T., & Zawojewski, J. S. (2011). Characterizations of Social-Based and Self-Based Contexts Associated With Students’ Awareness, Evaluation, and Regulation of Their Thinking During Small-Group Mathematical Modeling. Journal for Research in Mathematics Education, 42(5). Retrieved from https://eric.ed.gov/?id=EJ946347
Majeed, B. H., Jawad, L. F., & Alrikabi, H. T. S. (2021). Tactical Thinking and its Relationship with Solving Mathematical Problems Among Mathematics Department Students. International Journal of Emerging Technologies in Learning, 16(9). https://doi.org/10.3991/ijet.v16i09.22203
Mansyur, M. Z., & Sunendar, A. (2020). Improving Students’ Mathematical Problem Solving Ability through Metacognitive Guidance Approach. Edumatica: Jurnal Pendidikan Matematika, 10(2), 19. https://doi.org/https://doi.org/10.22437/edumatica.v10i2.10494
Matcha, W., Uzir, N. A., Gasevic, D., & Pardo, A. (2020). A Systematic Review of Empirical Studies on Learning Analytics Dashboards: A Self-Regulated Learning Perspective. IEEE Transactions on Learning Technologies, Vol. 13. https://doi.org/10.1109/TLT.2019.2916802
Matitaputty, C., Mataheru, W., & Talib, T. (2022). Analisis Kesalahan Mahasiswa dalam Menyelesaikan Masalah Permutasi dan Kombinasi. Jurnal Magister Pendidikan Matematika (JUMADIKA), 4(2). https://doi.org/10.30598/jumadikavol4iss2year2022page43-49
Nurhayati, N., Huda, N., & Suratno, S. (2020). Analisis Pemecahan Masalah Berdasarkan Teori Pemrosesan Informasi. Jurnal Ilmiah Dikdaya, 10(2). https://doi.org/10.33087/dikdaya.v10i2.169
Parwata, I. G. A. L., Jayanta, I. N. L., & Widiana, I. W. (2023). Improving Metacognitive Ability and Learning Outcomes with Problem-Based Revised Bloom’s Taxonomy Oriented Learning Activities. Emerging Science Journal, 7(2). https://doi.org/10.28991/ESJ-2023-07-02-019
Polya, G. (2019). How to Solve It. In How to Solve It. https://doi.org/10.2307/j.ctvc773pk
Rivas, S. F., Saiz, C., & Ossa, C. (2022). Metacognitive Strategies and Development of Critical Thinking in Higher Education. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.913219
Suliani, M., Juniati, D., & Lukito, A. (2022). Analysis of students’ metacognition in solving mathematics problem. AIP Conference Proceedings, 2577. https://doi.org/10.1063/5.0096032
Utami, D. D., Setyosari, P., Fajarianto, O., Kamdi, W., & Ulfa, S. (2023). The Correlation Between Metacognitive and Problem Solving Skills among Science Students. EduLine: Journal of Education and Learning Innovation, 3(1). https://doi.org/10.35877/454ri.eduline1702
Wijaya, T. T., Zhou, Y., Ware, A., & Hermita, N. (2021). Improving the Creative Thinking Skills of the Next Generation of Mathematics Teachers Using Dynamic Mathematics Software. International Journal of Emerging Technologies in Learning, 16(13). https://doi.org/10.3991/ijet.v16i13.21535
Yorulmaz, A., Uysal, H., & Çokçaliskan, H. (2021). Pre-service primary school teachers’ metacognitive awareness and beliefs about mathematical problem solving. JRAMathEdu (Journal of Research and Advances in Mathematics Education), 6(3). https://doi.org/10.23917/jramathedu.v6i3.14349
Yuniara, R., Saminan, S., Abidin, Z., & Johar, R. (2023). Students’ Mathematical Problem Solving Ability Based on The Steps of Ideal Problem Solving Viewed From Adversity Quotient (AQ). Al Khawarizmi: Jurnal Pendidikan Dan Pembelajaran Matematika, 7(1). https://doi.org/10.22373/jppm.v7i1.18211
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