Metacognitive Strategy-Based Instruction, Mathematical Conceptual Understanding, and Metacognitive Awareness among Prospective Elementary School Teachers

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Muhammad Munir
Muhammad Najib

Abstract

Prospective elementary teachers need conceptual understanding of mathematics and the ability to monitor their own learning. Yet evidence remains limited on how explicit metacognitive strategy instruction relates to conceptual understanding and metacognitive awareness during teacher preparation. This study aims to compare mathematical conceptual understanding under metacognitive strategy-based and conventional instruction and examine its association with metacognitive awareness. The study employed a quasi-experimental nonequivalent control-group pretest–posttest design involving 68 prospective elementary teachers (34 per group) across eight instructional sessions. Data were obtained from open-ended mathematics tests, a 30-item Metacognitive Awareness Inventory, classroom observations, and reflective journals, and analyzed using t-tests, analysis of covariance, standardized mean differences, and Pearson correlations. The results showed higher posttest conceptual understanding in the strategy-based group (M = 82.35, SD = 6.78) than in the comparison group (M = 72.14, SD = 7.25), with a significant pretest-adjusted difference, F(1, 65) = 34.87, p < .001. Reported increases in metacognitive awareness were 13.21 and 3.32 points, respectively, and awareness was positively correlated with conceptual understanding (r = .67, p < .001). Classroom records also documented more planning, monitoring, and evaluation activities during strategy-based instruction. These findings contribute evidence for integrating metacognitive strategies into elementary mathematics teacher preparation, while implications for classroom teaching and pupils’ learning require further investigation.

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Munir, M. M., & Najib, M. (2026). Metacognitive Strategy-Based Instruction, Mathematical Conceptual Understanding, and Metacognitive Awareness among Prospective Elementary School Teachers. Journal of Integrated Elementary Education, 6(2), 655–674. https://doi.org/10.21580/jieed.v6i2.29216
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References

Bednorz, D., & Bruhn, S. (2023). Influence of primary students’ self-regulated learning profiles on their rating of a technology-enhanced learning environment for mathematics. Frontiers in Psychology, 14, Article 1074371. https://doi.org/10.3389/fpsyg.2023.1074371

Breit, M., Schneider, M., & Preckel, F. (2025). Mathematics achievement and learner characteristics: A systematic review of meta-analyses. Learning and Individual Differences, 118, Article 102621. https://doi.org/10.1016/j.lindif.2024.102621

Çini, A., Järvelä, S., Dindar, M., & Malmberg, J. (2023). How multiple levels of metacognitive awareness operate in collaborative problem solving. Metacognition and Learning, 18(3), 891–922. https://doi.org/10.1007/s11409-023-09358-7

DiNapoli, J., & Miller, E. K. (2022). Recognizing, supporting, and improving student perseverance in mathematical problem-solving: The role of conceptual thinking scaffolds. The Journal of Mathematical Behavior, 66, Article 100965. https://doi.org/10.1016/j.jmathb.2022.100965

Ernst, H. M., Prinz-Weiß, A., Wittwer, J., & Voss, T. (2025). Discrepancy between performance and feedback affects mathematics student teachers’ self-efficacy but not their self-assessment accuracy. Frontiers in Psychology, 15, Article 1391093. https://doi.org/10.3389/fpsyg.2024.1391093

Fono, D., & Zohar, A. (2025). Metacognitive instruction: Central aspects of pre-service and novice in-service teachers’ knowledge and professional development. Professional Development in Education, 51(8), 1766–1789. https://doi.org/10.1080/19415257.2024.2409779

Heikkinen, S., Saqr, M., Malmberg, J., & Tedre, M. (2023). Supporting self-regulated learning with learning analytics interventions: A systematic literature review. Education and Information Technologies, 28, 3059–3088. https://doi.org/10.1007/s10639-022-11281-4

Hidayat, R., Mohd Saad, M. R., & Wewe, M. (2025). A meta-analysis of the effect of metacognitive instruction on mathematics achievement. Cogent Education, 12(1), Article 2517510. https://doi.org/10.1080/2331186X.2025.2517510

Huang, J., Cai, Y., Lv, Z., Huang, Y., & Zheng, X.-L. (2024). Toward self-regulated learning: Effects of different types of data-driven feedback on pupils’ mathematics word problem-solving performance. Frontiers in Psychology, 15, Article 1356852. https://doi.org/10.3389/fpsyg.2024.1356852

Lamon, S. J. (2020). Teaching fractions and ratios for understanding: Essential content knowledge and instructional strategies for teachers (4th ed.). Routledge. https://doi.org/10.4324/9780429464288

Mohamed, M., Rashid, R. A., & Alqaryouti, M. H. (2022). Conceptualizing the complexity of reflective practice in education. Frontiers in Psychology, 13, Article 1008234. https://doi.org/10.3389/fpsyg.2022.1008234

Muijs, D., & Bokhove, C. (2020). Metacognition and self-regulation: Evidence review. Education Endowment Foundation.

Musullulu, H., Garcia-Orza, J., Gómez Vázquez, D., & Garcia-Sanz, S. (2025). Cognitive control and metacognitive awareness: Do they shape academic achievement in university students? Frontiers in Psychology, 16, Article 1633996. https://doi.org/10.3389/fpsyg.2025.1633996

National Research Council. (2001). Adding it up: Helping children learn mathematics. National Academies Press. https://doi.org/10.17226/9822

Ncube, M., & Luneta, K. (2025). Concept-based instruction: Improving learner performance in mathematics through conceptual understanding. Pythagoras, 46(1), Article a815. https://doi.org/10.4102/pythagoras.v46i1.815

Noviyana, H., Rahmawati, F., Kirana, A. R., & Tanod, M. J. (2025). Enhancing elementary students’ mathematical problem-solving skills through AI-assisted problem-based learning. Journal of Integrated Elementary Education, 5(2), 254–268. https://doi.org/10.21580/jieed.v5i2.27576

Olid-Luque, M., Ayllón-Salas, P., Arco-Tirado, J. L., & Fernández-Martín, F. D. (2025). Impact of self-regulated learning programs in primary education: A systematic review. Psychology in the Schools, 62(3), 734–755. https://doi.org/10.1002/pits.23352

Öztürk-Tavşan, N., & İşler-Baykal, I. (2025). Development of prospective elementary teachers’ knowledge to teach early algebra through case discussions. Journal of Mathematics Teacher Education, 28, 1341–1372. https://doi.org/10.1007/s10857-024-09642-6

Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, Article 422. https://doi.org/10.3389/fpsyg.2017.00422

Pijeira-Díaz, H. J., van de Pol, J., Channa, F., & de Bruin, A. (2023). Scaffolding self-regulated learning from causal-relations texts: Diagramming and self-assessment to improve metacomprehension accuracy? Metacognition and Learning, 18, 631–658. https://doi.org/10.1007/s11409-023-09343-0

Rivas, S. F., Saiz, C., & Ossa, C. (2022). Metacognitive strategies and development of critical thinking in higher education. Frontiers in Psychology, 13, Article 913219. https://doi.org/10.3389/fpsyg.2022.913219

Sapkota, B., & Hayes, A. H. (2024). Preservice teachers’ mathematical knowledge for teaching: Focus on lesson planning and reflection. School Science and Mathematics, 124(5), 323–339. https://doi.org/10.1111/ssm.12644

Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475. https://doi.org/10.1006/ceps.1994.1033

Schuster, C., Stebner, F., Leutner, D., & Wirth, J. (2020). Transfer of metacognitive skills in self-regulated learning: An experimental training study. Metacognition and Learning, 15, 455–477. https://doi.org/10.1007/s11409-020-09237-5

Sercenia, J. C., & Prudente, M. S. (2023). Effectiveness of the metacognitive-based pedagogical intervention on mathematics achievement: A meta-analysis. International Journal of Instruction, 16(4), 561–578. https://doi.org/10.29333/iji.2023.16432a

Smit, R., Hess, K., Taras, A., Bachmann, P., & Dober, H. (2023). The role of interactive dialogue in students’ learning of mathematical reasoning: A quantitative multi-method analysis of feedback episodes. Learning and Instruction, 86, Article 101777. https://doi.org/10.1016/j.learninstruc.2023.101777

Söderström, S., & Palm, T. (2026). Feedback in mathematics education research: A systematic literature review. Research in Mathematics Education, 28(1), 163–184. https://doi.org/10.1080/14794802.2024.2401488

Tak, C. C., Zulnaidi, H., & Eu, L. K. (2025). Mediating role of metacognitive awareness between attitude and mathematics reasoning in pre-service teachers. European Journal of Science and Mathematics Education, 13(2), 90–102. https://doi.org/10.30935/scimath/16116

Twohill, A., NicMhuirí, S., Harbison, L., & Karakolidis, A. (2023). Primary preservice teachers’ mathematics teaching efficacy beliefs: The role played by mathematics attainment, educational level, preparedness to teach, and gender. International Journal of Science and Mathematics Education, 21, 601–622. https://doi.org/10.1007/s10763-022-10259-5

Vergnaud, G. (1997). The nature of mathematical concepts. In T. Nunes & P. Bryant (Eds.), Learning and teaching mathematics: An international perspective (pp. 5–28). Psychology Press.

Vo, K., Sarkar, M., White, P. J., & Yuriev, E. (2024). Development of problem-solving skills supported by metacognitive scaffolding: Insights from students’ written work. Chemistry Education Research and Practice, 25(4), 1197–1209. https://doi.org/10.1039/D3RP00284E

Vosniadou, S., Darmawan, I., Lawson, M. J., Van Deur, P., Jeffries, D., & Wyra, M. (2021). Beliefs about the self-regulation of learning predict cognitive and metacognitive strategies and academic performance in pre-service teachers. Metacognition and Learning, 16, 523–554. https://doi.org/10.1007/s11409-020-09258-0

Wahyuningtyas, L., & Amir, M. F. (2025). Can metaphorical thinking learning model enhance students’ mathematical literacy in area conservation? Journal of Integrated Elementary Education, 5(1), 128–149. https://doi.org/10.21580/jieed.v5i1.25690

Wang, X.-M., Huang, X.-T., & Zhou, W.-Q. (2024). The effect of university students’ self-efficacy on problem-solving disposition: The chained dual mediating role of metacognition disposition and critical thinking disposition. Thinking Skills and Creativity, 54, Article 101658. https://doi.org/10.1016/j.tsc.2024.101658

Xie, Y., Zeng, F., & Yang, Y. (2024). A meta-analysis of the relationship between metacognition and academic achievement in mathematics: From preschool to university. Acta Psychologica, 249, Article 104486. https://doi.org/10.1016/j.actpsy.2024.104486

Xu, X., Broadbent, J., & Zhang, Q. (2024). Cultivating mathematical mindset via online video interventions: A mixed-methods investigation in Chinese higher education. Frontiers in Psychology, 15, Article 1494702. https://doi.org/10.3389/fpsyg.2024.1494702

Yu, M., Cui, J., Wang, L., Gao, X., Cui, Z., & Zhou, X. (2022). Spatial processing rather than logical reasoning was found to be critical for mathematical problem-solving. Learning and Individual Differences, 100, Article 102230. https://doi.org/10.1016/j.lindif.2022.102230

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2

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