Autorregulación metacognitiva y transferencia del aprendizaje matemático en estudiantes universitarios de educación
DOI:
https://doi.org/10.70577/s.e.v4i3.69Palabras clave:
Aprendizaje matemático, autorregulación metacognitiva, formación docente, razonamiento matemático, transferencia del aprendizaje.Resumen
La transferencia del aprendizaje matemático es una competencia esencial en la formación de futuros docentes, debido a que exige comprender, adaptar y aplicar los conocimientos en situaciones diferentes de aquellas utilizadas durante la enseñanza. El estudio tuvo como objetivo analizar la relación entre la autorregulación metacognitiva y la transferencia del aprendizaje matemático en estudiantes universitarios de Educación, en articulación con el proyecto de vinculación “Alfabetización e Integración de TIC en prácticas pedagógicas de unidades educativas y comunidades del sur de Manabí-proyecto”, cuya orientación favorece el fortalecimiento de prácticas pedagógicas mediante la integración de recursos tecnológicos y estrategias de aprendizaje. Se adoptó un enfoque cuantitativo, no experimental, documental y retrospectivo, mediante la revisión de cinco investigaciones empíricas publicadas entre 2023 y 2025. El corpus integró a 1205 estudiantes, el procesamiento incluyó estadística descriptiva, correlación de Pearson, regresión múltiple, análisis de conglomerados, análisis discriminante, análisis de rutas y sensibilidad. Los resultados evidenciaron una asociación elevada entre metacognición y razonamiento matemático (r = 0.65; p < 0.01). La planificación se relacionó significativamente con la puntuación matemática (r = 0.269; p = 0.006), mientras que la evaluación presentó su mayor asociación con el cumplimiento de las actividades (r = 0.303; p = 0.002). La gestión de información, el conocimiento declarativo y la planificación explicaron conjuntamente el 41.4% de la variabilidad de la modelización. La metacognición influyó directamente sobre el razonamiento (β = 0.38; p = 0.001) y medió parcialmente la relación entre actitud y razonamiento. La evidencia respaldó principalmente la transferencia cercana, pero resultó insuficiente para demostrar su generalización hacia contextos profesionales o pedagógicos. Los hallazgos sustentan la incorporación de estrategias metacognitivas explícitas y diferenciadas, articuladas con el uso pedagógico de las TIC, para fortalecer la formación inicial docente y favorecer la transferencia del aprendizaje matemático hacia diversos contextos educativos.
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Alyani, F., & Ramadhina, A. L. (2022). The relation between self-regulated learning and mathematical problem-solving during COVID-19. Journal of Education Research and Evaluation, 6(4), 645–652. https://doi.org/10.23887/jere.v6i4.47593
Arianto, F., & Hanif, M. (2024). Evaluating metacognitive strategies and self-regulated learning to predict primary school students’ self-efficacy and problem-solving skills in science learning. Journal of Pedagogical Research, 8(3), 301–319. https://doi.org/10.33902/JPR.202428575
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, 1074371. https://doi.org/10.3389/fpsyg.2023.1074371
Chan, C. T., Leong, K. E., y Zulnaidi, H. (2023). Undergraduate students’ attitudes and mathematical reasoning during the pandemic: The mediating role of metacognitive awareness. European Journal of Mathematics and Science Education, 4(3), 169–180. https://doi.org/10.12973/ejmse.4.3.169
Chan, C. T., Zulnaidi, H., & Leong, K. E. (2022). Measurement model testing: Adaptation of metacognitive awareness toward mathematical reasoning among undergraduate education students. Contemporary Mathematics and Science Education, 3(2), ep22021. https://doi.org/10.30935/conmaths/12510
Dörrenbächer-Ulrich, L., Weißenfels, M., Russer, L., & Perels, F. (2024). Investigating the relationship between self-regulated learning, metacognition, and executive functions by focusing on academic transition phases: A systematic review. Current Psychology, 43, 22503–22523. https://doi.org/10.1007/s12144-023-05551-8
Eberhart, J., Burkart, J. M., & Savelsbergh, E. R. (2025). Are metacognition interventions in young children effective? A systematic review and meta-analysis. Metacognition and Learning, 20, 299–341. https://doi.org/10.1007/s11409-024-09405-x
Fernández Ortube, A., Panadero, E., & Dignath, C. (2024). Self-regulated learning interventions for pre-service teachers: A systematic review. Educational Psychology Review, 36, 113. https://doi.org/10.1007/s10648-024-09919-5
He, G., Chen, S., Lin, H., & Su, A. (2024). The association between initial metacognition and subsequent academic achievement: A meta-analysis of longitudinal studies. Educational Psychology Review, 36, 81. https://doi.org/10.1007/s10648-024-09922-w
Hidayat, R., Zulnaidi, H., Syed Zamri, S. N. A., & Abdullah, M. F. N. L. (2025). A meta-analysis of the effect of metacognitive instruction on mathematics achievement. Cogent Education, 12(1), 2517510. https://doi.org/10.1080/2331186X.2025.2517510
Karagiannopoulou, E., Desatnik, A., Rentzios, C., & Ntritsos, G. (2022). The exploration of a model for understanding the contribution of emotion regulation to students’ learning: The role of academic emotions and sense of coherence. Current Psychology, 42, 26491–26503. https://doi.org/10.1007/s12144-022-03722-7
Karlen, Y., Hirt, C. N., Jud, J., Rosenthal, A., & Eberli, T. D. (2023). Teachers as learners and agents of self-regulated learning: The importance of different teachers’ competence aspects for promoting metacognition. Teaching and Teacher Education, 125, 104055. https://doi.org/10.1016/j.tate.2023.104055
Kholid, M. N., Pradana, L. N., Maharani, S., & Swastika, A. (2025). Classifying self-regulated learning in mathematical problem-solving using machine learning approaches. Educational Process: International Journal, 17, e2025390. https://doi.org/10.22521/edupij.2025.17.390
Landa, J., Berciano, A., y Marbán, J. M. (2024). Self-regulation profiles of pre-service mathematics teachers for primary education in mathematical problem-solving contexts. Education Sciences, 14(9), 1018. https://doi.org/10.3390/educsci14091018
Lee, Y. J., Davis, R., & Li, Y. (2022). Implementing synchronous online flipped learning for pre-service teachers during COVID-19. European Journal of Educational Research, 11(2), 653–661. https://doi.org/10.12973/eu-jer.11.2.653
Lestari, K. E., Utami, M. R., & Yudhanegara, M. R. (2022). Exploratory analysis on adaptive reasoning of undergraduate students in statistical inference. International Journal of Instruction, 15(4), 535–554. https://doi.org/10.29333/iji.2022.15429a
Oficiar, J. R. G., Ibañez, E. D., y Pentang, J. T. (2024). Metacognitive awareness as a predictor of mathematical modeling competency among preservice elementary teachers. International Journal of Educational Methodology, 10(2), 279–292. https://doi.org/10.12973/ijem.10.1.1079
Orón, J. V., Ales, J. M., & Blasco, M. (2023). Achieving transfer from mathematics learning. Education Sciences, 13(2), 161. https://doi.org/10.3390/educsci13020161
Pham, P. T., Lien, D. T. H., Kien, H. C., Chi, N. H., Tinh, P. T., Do, T., Nguyen, L. C., & Nguyen, T.-T. (2022). Learning management systems in developing countries: A bibliometric analysis between 2005 and 2020. European Journal of Educational Research, 11(3), 1363–1377. https://doi.org/10.12973/eu-jer.11.3.1363
Phan, T. T., Do, T. T., Trinh, T. H., Tran, T., Duong, H. T., Trinh, T. P. T., Do, B. C., & Nguyen, T.-T. (2022). A bibliometric review on realistic mathematics education in the Scopus database between 1972 and 2019. European Journal of Educational Research, 11(2), 1133–1149. https://doi.org/10.12973/eu-jer.11.2.1133
Ruhl, J., Wäschle, K., & Dresel, M. (2025). Multimethod assessment of self-regulated learning in higher education: Convergence and predictive validity of self-report, trace, and performance measures. Learning and Individual Differences, 118, 102760. https://doi.org/10.1016/j.lindif.2025.102760
Shi, Y., Jia, K., Cao, C., Wei, Y., & Yang, H. H. (2024). Study on the influencing factors of primary school students’ self-regulated learning in the smart classroom: An environmental perspective. In Communications in Computer and Information Science (Vol. 1974, pp. 218–228). Springer. https://doi.org/10.1007/978-981-99-8255-4_19
Simón-Grábalos, D., Fonseca-Pedrero, E., & Pérez-Albéniz, A. (2025). Systematic review of the literature on interventions to improve self-regulated learning in first-year undergraduate students. Education Sciences, 15(3), 372. https://doi.org/10.3390/educsci15030372
Stebner, F., Schuster, C., Weber, X.-L., Greiff, S., Leutner, D., y Wirth, J. (2022). Transfer of metacognitive skills in self-regulated learning: Effects on strategy application and content knowledge acquisition. Metacognition and Learning, 17(3), 715–744. https://doi.org/10.1007/s11409-022-09322-x
Sun, L., & Zhou, L. (2024). Does generative artificial intelligence improve the academic achievement of college students? A meta-analysis. Journal of Educational Computing Research, 62(7), 1896–1933. https://doi.org/10.1177/07356331241277937
Tabuyo, A. (2024). Metacognition and mathematical problem-solving performance of pre-service teachers. Pegem Journal of Education and Instruction, 14(4), 614–623. https://doi.org/10.47750/pegegog.14.04.46
Tak, C. C., Zulnaidi, H., & Leong, K. E. (2022). Measurement model testing: Adaptation of self-efficacy and metacognitive awareness among university students. Eurasia Journal of Mathematics, Science and Technology Education, 18(9), em2153. https://doi.org/10.29333/ejmste/12366
Tak, C. C., Zulnaidi, H., Leong, K. E., & Feng, S. P. (2023). Mediating role of metacognitive awareness between self-efficacy and mathematics reasoning among education undergraduate students during the pandemic. Journal of Higher Education Theory and Practice, 23(6), 36–46. https://doi.org/10.33423/jhetp.v23i6.5959
Tak, C. C., Zulnaidi, H., y 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
Thi-Nga, H., Thi-Binh, V., & Nguyen, T.-T. (2024). Metacognition in mathematics education: From academic chronicle to future research scenario—A bibliometric analysis with the Scopus database. Eurasia Journal of Mathematics, Science and Technology Education, 20(4), em2427. https://doi.org/10.29333/ejmste/14381
Toikka, S., Havu-Nuutinen, S., & Kärkkäinen, S. (2024). Combined conceptualisations of metacognitive knowledge in the context of mathematical problem-solving. Cogent Education, 11(1), 2357901. https://doi.org/10.1080/2331186X.2024.2357901
Urban, M., Děchtěrenko, F., Lukavský, J., Hrabalová, V., Svacha, F., Brom, C., & Urban, K. (2024). ChatGPT improves creative problem-solving performance in university students: An experimental study. Computers & Education, 215, 105031. https://doi.org/10.1016/j.compedu.2024.105031
van der Graaf, J., Taub, M., & Fan, Y. (2023). Facilitating self-regulated learning with scaffolds: Recent advances and future directions. Metacognition and Learning, 18(3), 623–629. https://doi.org/10.1007/s11409-023-09364-9
Vosniadou, S., Bodner, E., Stephenson, H., Jeffries, D., Lawson, M. J., Darmawan, I. G. N., Kang, S., Graham, L., & Dignath, C. (2024). The promotion of self-regulated learning in the classroom: A theoretical framework and an observation study. Metacognition and Learning, 19, 381–419. https://doi.org/10.1007/s11409-024-09374-1
Wafubwa, R. N., & Csíkos, C. (2022). Impact of formative assessment instructional approach on students’ mathematics achievement and their metacognitive awareness. International Journal of Instruction, 15(2), 119–138. https://doi.org/10.29333/iji.2022.1527a
Xie, Y., Zeng, F., y Yang, Y. (2024). A meta-analysis of the relationship between metacognition and academic achievement in mathematics: From preschool to university. Acta Psychologica, 249, 104486. https://doi.org/10.1016/j.actpsy.2024.104486
Xu, Z., Zhao, Y., Zhang, B., Liew, J., & Kogut, A. (2023). A meta-analysis of the efficacy of self-regulated learning interventions on academic achievement in online and blended learning environments. Behaviour & Information Technology, 43(13), 2911–2931. https://doi.org/10.1080/0144929X.2022.2151935
Zhang, J., Liu, Y., Shu, T., & Liu, M. (2024). Metacognition and mathematical modeling skills: The mediating role of creative thinking. Journal of Intelligence, 12(6), 55. https://doi.org/10.3390/jintelligence12060055
