Investigating metacognitive planning in collaborative problem-solving among undergraduate mathematics education students
Keywords:
Collaboration, Metacognition, Metacognitive Regulation, PlanningAbstract
Planning is one of the crucial components of metacognitive regulation. However, metacognitive planning is less studied empirically. This case study aims to explore the metacognitive planning activities of students when collaboratively solving mathematical problems. Proof problems in geometry were given to eight groups willing to participate in the research. Each group consisted of two undergraduate mathematics education students. Group discussion activities in solving problems were recorded using video-audio recorders. Interviews were also conducted with the groups to obtain more data on the metacognitive planning activities, thus achieving the research objectives. This study identified three different characteristics of metacognitive planning. We labelled these three planning characteristics as high, middle, and low levels of metacognitive planning. The low-level planning entails the formulation of a single problem-solving plan. Middle-level planning involves the formulation of two problem-solving plans, albeit the selection of the appropriate plan occurs through trial and error. Conversely, the formulation of more than two problem-solving plans and the ability to select the most effective plan characterize high-level planning. These findings can be utilized by educators to assess the efficacy of their students' metacognitive planning activities as a learning outcome.
References
Bell, E. T., & Polya, G. (1945). How to Solve It. A New Aspect of Mathematical Method. The American Mathematical Monthly, 52(10). https://doi.org/10.2307/2306109
Castillo-Diaz, M. A., Gomes, C. M. A., & Jelihovschi, E. G. (2022). Rethinking the Components of Regulation of Cognition through the Structural Validity of the Meta-Text Test. International Journal of Educational Methodology, 8(4). https://doi.org/10.12973/ijem.8.4.687
Çini, A., Järvelä, S., Dindar, M., & Malmberg, J. (2023). How multiple levels of metacognitive awareness operate in collaborative problem solving. In Metacognition and Learning (Vol. 18, Issue 3). Springer US. https://doi.org/10.1007/s11409-023-09358-7
Cirillo, M., & Hummer, J. (2021). Competencies and behaviors observed when students solve geometry proof problems: an interview study with smartpen technology. ZDM - Mathematics Education, 53(4). https://doi.org/10.1007/s11858-021-01221-w
De Backer, L., Van Keer, H., & Valcke, M. (2022). The functions of shared metacognitive regulation and their differential relation with collaborative learners’ understanding of the learning content. Learning and Instruction, 77(July 2020), 101527. https://doi.org/10.1016/j.learninstruc.2021.101527
Drozdick, L. W., Singer, J. K., Lichtenberger, E. O., Kaufman, J. C., Kaufman, A. S., & Kaufman, N. L. (2018). The Kaufman Assessment Battery for Children—Second Edition and KABC‑II Normative Update. In Contemporary intellectual assessment: Theories, tests, and issues, 4th ed.
Escorcia, D., & Gimenes, M. (2020). Metacognitive components of writing: Construction and validation of the Metacognitive Components of Planning Writing Self-inventory (MCPW-I). Revue Europeenne de Psychologie Appliquee, 70(1). https://doi.org/10.1016/j.erap.2019.100515
Fatmanissa, N., Jamil, A. F., Siswono, T. Y. E., & Lukito, A. (2025). Collaborative Problem Solving With and Without Access to Technology: Emphasis on Mathematical Justifications. Mathematics Teaching-Research Journal, 17(3), 178-200.
He, R., Jain, Y. R., & Lieder, F. (2022). Have I done enough planning or should I plan more? NeurIPS, 1–19. http://arxiv.org/abs/2201.00764
Liskala, T., Volet, S., Jones, C., Koretsky, M., & Vauras, M. (2021). Significance of forms and foci of metacognitive regulation in collaborative science learning of less and more successful outcome groups in diverse contexts. In Instructional Science (Vol. 49, Issue 5). Springer Netherlands. https://doi.org/10.1007/s11251-021-09558-1
Jamil, A. F., Siswono, T. Y. E., & Setianingsih, R. (2023a). Metacognitive Regulation in Collaborative Problem-Solving: A Bibliometric Analysis and Systematic Literature Review. In H. Polat, A. A. Khan, & M. D. Kaya (Eds.), Studies on Education, Science, and Technology 2023 (pp. 32–62). ISTES Organization.
Jamil, A. F., Siswono, T. Y. E., & Setianingsih, R. (2023b). The Emergence and Form of Metacognitive Regulation : Case Study of More and Less Successful Outcome Groups in Solving Geometry Problems Collaboratively. Mathematics Teaching-Research Journal, 15(1), 25–43.
Jamil, A. F., Siswono, T. Y. E., Setianingsih, R., Lukito, A., & Ismail. (2023c). The potential problem to explore metacognitive regulation in collaborative problem-solving. Ricerche Di Pedagogia e Didattica – Journal of Theories and Research in Education, 18(1), 57–71. https://doi.org/10.6092/issn.1970-2221/16086
Li, J., Zhang, B., Du, H., Zhu, Z., & Li, Y. M. (2015). Metacognitive planning: Development and validation of an online measure. Psychological Assessment, 27(1), 260–271. https://doi.org/10.1037/pas0000019
MacKewn, A., Depriest, T., & Donavant, B. (2022). Metacognitive Knowledge, Regulation, and Study Habits. Psychology, 13(12), 1811–1821. https://doi.org/10.4236/psych.2022.1312112
Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative Data Analysis: A Methods Sourcebook. SAGE Publications, Inc.
Naglieri, J. A., & Kaufman, J. C. (2001). Understanding intelligence, giftedness and creativity using the pass theory. Roeper Review, 23(3). https://doi.org/10.1080/02783190109554087
Nelson, T. O. (1997). The meta-level versus object-level distinction (and other issues) in formulations of metacognition. American Psychologist, 52(2). https://doi.org/10.1037/0003-066x.52.2.179
Özreçberoğlu, N., & Çağanağa, Ç. K. (2018). Making it count: Strategies for improving problem-solving skills in mathematics for students and teachers’ classroom management. Eurasia Journal of Mathematics, Science and Technology Education, 14(4). https://doi.org/10.29333/ejmste/82536
Panahandeh, E., & Asl, S. E. (2014). The Effect of Planning and Monitoring as Metacognitive Strategies on Iranian EFL Learners’ Argumentative Writing Accuracy. Procedia - Social and Behavioral Sciences, 98, 1409–1416. https://doi.org/10.1016/j.sbspro.2014.03.559
Powell, S., Ding, Y., Wang, Q., Craven, J., & Chen, E. (2019). Exploring strategy use for multiplication problem solving in college students. International Journal of Research in Education and Science, 5(1).
Roberts, J. S. (2021). Integrating Metacognitive Regulation into the Online Classroom Using Student-Developed Learning Plans. Journal of Microbiology & Biology Education, 22(1). https://doi.org/10.1128/jmbe.v22i1.2409
Rocha, H., & Babo, A. (2024). Problem-solving and mathematical competence: A look to the relation during the study of Linear Programming. Thinking Skills and Creativity, 51. https://doi.org/10.1016/j.tsc.2023.101461
Rott, B., Specht, B., & Knipping, C. (2021). A descriptive phase model of problem-solving processes. ZDM - Mathematics Education, 53(4). https://doi.org/10.1007/s11858-021-01244-3
Salminen-Saari, J. F. A., Garcia Moreno-Esteva, E., Haataja, E., Toivanen, M., Hannula, M. S., & Laine, A. (2021). Phases of collaborative mathematical problem solving and joint attention: a case study utilizing mobile gaze tracking. ZDM - Mathematics Education, 53(4), 771–784. https://doi.org/10.1007/s11858-021-01280-z
Srimuliati, S., & Wahyuni, W. (2020). Kemampuan Berfikir Intuitif Mahasiswa Calon Guru Dalam Penyelesaian Masalah Matematika. Jurnal Ilmiah Pendidikan Matematika Al Qalasadi, 4(2). https://doi.org/10.32505/qalasadi.v4i2.2186
Stanton, J. D., Neider, X. N., Gallegos, I. J., & Clark, N. C. (2015). Differences in metacognitive regulation in introductory biology students: When prompts are not enough. CBE Life Sciences Education, 14(2), 1–12. https://doi.org/10.1187/cbe.14-08-0135
Sugiharto, B., Corebima, A., Susilo, H., & Ibrohim, M. (2017). Cognition Regulation of Biology Education Students. Proceedings of the International Conference on Teacher Training and Education 2017 (ICTTE 2017). https://doi.org/10.2991/ictte-17.2017.38
Téllez, A., & Sánchez, T. de J. (2016). Luria’s model of the functional units of the brain and the neuropsychology of dreaming. Psychology in Russia: State of the Art, 9(4). https://doi.org/10.11621/pir.2016.0407
Young, A., & Fry, J. D. (2008). Metacognitive awareness and academic achievement in college students. Journal of the Scholarship of Teaching and Learning, 8(2).
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Anis Farida Jamil, Namirah Fatmanissa

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Abstract views: 1
,
PDF Downloads: 0
