The Role of Metacognitive Strategies in Blended LearningStudy Habits and Reading Comprehension

  1. Beatriz Ortega-Ruipérez 1
  1. 1 Universidad Internacional de La Rioja, España
Revista:
RIED: revista iberoamericana de educación a distancia

ISSN: 1138-2783

Ano de publicación: 2022

Volume: 25

Número: 2

Páxinas: 219-238

Tipo: Artigo

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Outras publicacións en: RIED: revista iberoamericana de educación a distancia

Resumo

Las estrategias metacognitivas son fundamentales, ya que permiten gestionar el proceso de aprendizaje propio. Esto es especialmente importante en la educación superior y en la enseñanza semipresencial porque requiere una mayor independencia. Este estudio pretende determinar la importancia de las estrategias metacognitivas tanto en los hábitos de estudio como en la comprensión lectora en la enseñanza semipresencial. Para ello, se utilizan estrategias metacognitivas a través de una herramienta digital en un contexto de aprendizaje semipresencial. Se utilizó el test SRSI-SR para evaluar los hábitos de estudio y el ARATEX-R para evaluar la lectura de textos antes y después de un curso de maestría. La muestra del estudio incluyó a 112 estudiantes de diversas disciplinas; la mitad de ellos utilizó la herramienta como parte del grupo de investigación, y la otra mitad no la utilizó como parte del grupo de control. Los resultados muestran que el uso de las estrategias metacognitivas ha facilitado especialmente la organización de la tarea en cuanto a los hábitos de estudio. En la comprensión lectora, las estrategias metacognitivas favorecieron especialmente la gestión de la motivación, la evaluación de la comprensión y la planificación. Se concluye que el uso de estrategias metacognitivas tiene un peso significativo, por lo que estos hallazgos sugieren la inclusión de estrategias metacognitivas en la enseñanza semipresencial para mejorar los hábitos de estudio y la comprensión lectora en los estudiantes y, así, mejoran sus resultados de aprendizaje. Las conclusiones obtenidas permiten profundizar el conocimiento científico sobre cómo influyen estas estrategias en el aprendizaje.

Referencias bibliográficas

  • Adams, A. M., Wilson, H., Money, J., Palmer-Conn, S., & Fearn, J. (2019). Student engagement with feedback and attainment: the role of academic self-efficacy. Assessment & Evaluation in Higher Education, 45(2), 317-329. https://doi.org/10.1080/02602938.2019.1640184
  • Akamatsu, D., Nakaya, M., & Koizumi, R. (2019). Effects of metacognitive strategies on the self-regulated learning process: The mediating effects of self-efficacy. Behavioral Sciences, 9(12), 128. https://doi.org/10.3390/bs9120128
  • Alzaid, M., & Hsiao, S. (2019). Utilising problem-solving: from self-assessment to self-regulating. New Review of Hypermedia and Multimedia, 25(3), 222-244. https://doi.org/10.1080/13614568.2019.1705922
  • Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-Regulated learning strategies and non-academic outcomes in higher education blended learning environments: a one decade review. Education and Information Technologies, 25, 3677-3704. https://doi.org/10.1007/s10639-020-10134-2
  • Bahri, A., Idris, I. S., Muis, H., Arifuddin, M., & Fikri, M., J., N. (2021). Blended Learning Integrated with Innovative Learning Strategy to Improve Self-Regulated Learning. International. Journal of Instruction, 14(1), 779-794. https://doi.org/10.29333/iji.2021.14147a
  • Blau, I., & Shamir-Inbal, T. (2017). Re-designed flipped learning model in an academic course: The role of co-creation and co-regulation. Computers & Education, 115, 69-81. https://doi.org/10.1016/j.compedu.2017.07.014
  • Broadbent, J. (2017). Comparing online and blended learner's self-regulated learning strategies and academic performance. The Internet and Higher Education, 33, 24-32. https://doi.org/10.1016/j.iheduc.2017.01.004
  • Broadbent, J., & Fuller-Tyszkiewicz, M. (2018). Profiles in self-regulated learning and their correlates for online and blended learning students. Educational technology research and development, 66(6), 1435-1455. https://doi.org/10.1007/s11423-018-9595-9
  • Bull, S., & Kay, J. (2010). Open Learner Models. In R. Nkambou, J. Bourdeau y R. Mizoguchi (Eds.), Advances in Intelligent Tutoring Systems. Studies in Computational Intelligence, 308. Springer. https://doi.org/10.1007/978-3-642-14363-2_15
  • Carroll, D. (2020). Observations of student accuracy in criteria-based self-assessment. Assessment & Evaluation in Higher Education, 45(8), 1088-1105. https://doi.org/10.1080/02602938.2020.1727411
  • Chen, P. P., & Bonner, S. M. (2020). A framework for classroom assessment, learning, and self-regulation. Assessment in Education: Principles, Policy & Practice, 27(4), 373-393. https://doi.org/10.1080/0969594X.2019.1619515
  • Chou, C. Y., & Zou, N. B. (2020). An analysis of internal and external feedback in self-regulated learning activities mediated by self-regulated learning tools and open learner models. International Journal of Educational Technology in Higher Education, 17(1), 1-27. https://doi.org/10.1186/s41239-020-00233-y
  • Cleary, T. J. (2006). The development and validation of the Self-Regulation Strategy Inventory—Self-Report. Journal of School Psychology, 44(4), 307-322. https://doi.org/10.1016/j.jsp.2006.05.002
  • Colthorpe, K., Sharifirad, T., Ainscough, L., Anderson, S., & Zimbardi, K. (2018). Prompting undergraduate students’ metacognition of learning: implementing ‘meta-learning’assessment tasks in the biomedical sciences. Assessment & Evaluation in Higher Education, 43(2), 272-285. https://doi.org/10.1080/02602938.2017.1334872
  • Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
  • Dixon, H., Hawe, E., & Hamilton, R. (2020). The case for using exemplars to develop academic self-efficacy. Assessment & Evaluation in Higher Education, 45(3), 460-471. https://doi.org/10.1080/02602938.2019.1666084
  • Fokkens-Bruinsma, M., Vermue, C., Deinum, J. F., & van Rooij, E. (2020). First-year academic achievement: the role of academic self-efficacy, self-regulated learning and beyond classroom engagement. Assessment & Evaluation in Higher Education, 46(7), 1115-1126. https://doi.org/10.1080/02602938.2020.1845606
  • Fraile, J., Gil-Izquierdo, M., Zamorano-Sande, D., & Sánchez-Iglesias, I. (2020). Self-regulated learning and formative assessment process on group work. Relieve: Revista Electrónica de Investigación y Evaluación Educativa, 26(1), 7. https://doi.org/10.7203/relieve.26.1.17402
  • Hawe, E., & Dixon, H. (2017). Assessment for learning: a catalyst for student self-regulation. Assessment & Evaluation in Higher Education, 42(8), 1181-1192. https://doi.org/10.1080/02602938.2016.1236360
  • Hernández, A., & Camargo, Á. (2017). Adaptación y validación del Inventario de Estrategias de Autorregulación en estudiantes universitarios. Suma Psicológica, 24(1), 9-16. https://doi.org/10.1016/j.sumpsi.2017.02.001
  • Hooshyar, D., Kori, K., Pedaste, M., & Bardone, E. (2019). The potential of open learner models to promote active thinking by enhancing self‐regulated learning in online higher education learning environments. British Journal of Educational Technology, 50(5), 2365-2386. https://doi.org/10.1111/bjet.12826
  • Kay, J., Halin, Z., Ottomann, T., & Razak, Z. (1997). Learner know thyself: Student models to give learner control and responsibility. In Proceedings of International Conference on Computers in Education (pp. 17-24).
  • Kickert, R., Meeuwisse, M., M. Stegers-Jager, K., V. Koppenol-Gonzalez, G., R. Arends, L., & Prinzie, P. (2019). Assessment policies and academic performance within a single course: the role of motivation and self-regulation. Assessment & Evaluation in Higher Education, 44(8), 1177-1190. https://doi.org/10.1080/02602938.2019.1580674
  • Lluch, L., & Portillo, M. C. (2018). La competencia de aprender a aprender en el marco de la educación superior. Revista Iberoamericana de Educación, 78(2), 59-76. https://doi.org/10.35362/rie7823183
  • Muijs, D., & Bokhove, C. (2020). Metacognition and Self-Regulation: Evidence Review. London: Education Endowment Foundation. https://educationendowmentfoundation.org.uk/evidence-summaries/evidence-reviews/metacognition-and-self-regulation-review/
  • Ng, E. M. (2018). Integrating self-regulation principles with flipped classroom pedagogy for first year university students. Computers & Education, 126, 65-74. https://doi.org/10.1016/j.compedu.2018.07.002
  • Nieminen, J. H., & Tuohilampi, L. (2020). ‘Finally studying for myself’–examining student agency in summative and formative self-assessment models. Assessment & Evaluation in Higher Education, 45(7), 1031-1045. https://doi.org/10.1080/02602938.2020.1720595
  • Núñez, J. C., Amieiro, N., Álvarez, D., García, T., & Dobarro, A. (2015). Escala de Evaluación de la Autorregulación del Aprendizaje a partir de Textos (ARATEX-R). European Journal of Education and Psychology, 8(1), 9-22. https://doi.org/10.1016/j.ejeps.2015.10.002
  • Onah, D. F., Pang, E. L., & Sinclair, J. E. (2020). Cognitive optimism of distinctive initiatives to foster self-directed and self-regulated learning skills: A comparative analysis of conventional and blended-learning in undergraduate studies. Education and Information Technologies, 25(5), 4365-4380. https://doi.org/10.1007/s10639-020-10172-w
  • Ortega-Ruipérez, B., & Castellanos, A. (2021). Design and development of a digital tool for metacognitive strategies in self-regulated learning. In EDULEARN21 Proceedings. https://doi.org/10.21125/edulearn.2021
  • Panadero, E., Broadbent, J., Boud, D., & Lodge, J. M. (2018). Using formative assessment to influence self- and co-regulated learning: The role of evaluative judgement. European Journal of Psychology of Education, 34(3), 535-557. https://doi.org/10.1007/s10212-018-0407-8
  • Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self-efficacy: Four meta-analyses. Educational Research Review, 22, 74-98. https://doi.org/10.1016/j.edurev.2017.08.004
  • Pardo, A., Han, F., & Ellis, R. A. (2016). Combining university student self-regulated learning indicators and engagement with online learning events to predict academic performance. IEEE Transactions on Learning Technologies, 10(1), 82-92. https://doi.org/10.1109/TLT.2016.2639508
  • Pintrich, P. (2004). A conceptual framework for assessing motivation and SRL in college students. Educational Psychology Review, 16(4), 385-407. https://doi.org/10.1007/s10648-004-0006-x
  • Sáiz, M. C., García-Osorio, C. I., & Díez-Pastor, J. F. (2019). Differential efficacy of the resources used in B-learning environments, Psicothema, 31(2), 170-178. https://doi.org/10.7334/psicothema2018.330
  • Sáiz, M. C., Marticorena, R., García-Osorio, C. I., & Díez-Pastor, J. F. (2017). How Do B-Learning and Learning Patterns Influence Learning Outcomes? Frontiers in Psychology, 8, 745. https://doi.org/10.3389/fpsyg.2017.00745
  • Schumacher, C., & Ifenthaler, D. (2018). Features students really expect from learning analytics. Computers in human behavior, 78, 397-407. https://doi.org/10.1016/j.chb.2017.06.030
  • Schwam, D., Greenberg, D., & Li, H. (2020). Individual Differences in Self-regulated Learning of College Students Enrolled in Online College Courses. American Journal of Distance Education, 35(2), 133-151. https://doi.org/10.1080/08923647.2020.1829255
  • Tai, J., Ajjawi, R., Boud, D., Dawson, P., & Panadero, E. (2018). Developing evaluative judgement: enabling students to make decisions about the quality of work. Higher Education, 76(3), 467-481. https://doi.org/10.1007/s10734-017-0220-3
  • Vanslambrouck, S., Zhu, C., Pynoo, B., Lombaerts, K., Tondeur, J., & Scherer, R. (2019). A latent profile analysis of adult students’ online self-regulation in blended learning environments. Computers in Human Behavior, 99, 126-136. https://doi.org/10.1016/j.chb.2019.05.021
  • Vasu, K. A. P., Mei Fung, Y., Nimehchisalem, V., & Md Rashid, S. (2020). Self-Regulated Learning Development in Undergraduate ESL Writing Classrooms: Teacher Feedback Versus Self-Assessment. RELC Journal, 0033688220957782. https://doi.org/10.1177/0033688220957782
  • Wang, F. H. (2019). On the relationships between behaviors and achievement in technology-mediated flipped classrooms: A two-phase online behavioral PLS-SEM model. Computers & Education, 142, 103653. https://doi.org/10.1016/j.compedu.2019.103653
  • Winne, P. H. (1996). A metacognitive view of individual differences in self-regulated learning. Learning and Individual Differences, 8(4), 327-353. https://doi.org/10.1016/S1041-6080(96)90022-9
  • Wong, T. L., Xie, H., Zou, D., Wang, F. L., Tang, J. K. T., Kong, A., & Kwan, R. (2019). How to facilitate self-regulated learning? A case study on open educational resources. Journal of Computers in Education, 7(1), 51-77. https://doi.org/10.1007/s40692-019-00138-4
  • Yan, Z. (2020). Self-assessment in the process of self-regulated learning and its relationship with academic achievement. Assessment & Evaluation in Higher Education, 45(2), 224-238. https://doi.org/10.1080/02602938.2019.1629390
  • Zamora, Á., Suárez, J. M., & Ardura, D. (2018). Error detection and self-assessment as mechanisms to promote self-regulation of learning among secondary education students. The Journal of Educational Research, 111(2), 175-185. https://doi.org/10.1080/00220671.2016.1225657
  • Zhu, Y., Zhang, J. H., Au, W., & Yates, G. (2020). University students’ online learning attitudes and continuous intention to undertake online courses: a self-regulated learning perspective. Educational Technology Research and Development, 68, 1485–1519. https://doi.org/10.1007/s11423-020-09753-w
  • 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
Fonte de datos: Dialnet