Carga cognitiva en el aprendizaje colaborativo: Una revisión sistemática

Palabras clave: Aprendizaje colaborativo, carga cognitiva, estrategias metacognitivas, herramientas visuales, entornos virtuales

Resumen

El aprendizaje colaborativo se ha convertido en una estrategia educativa ampliamente utilizada, pero persisten inconsistencias sobre cómo impacta en la carga cognitiva de los estudiantes. El objetivo de la investigación fue analizar la carga cognitiva en el aprendizaje colaborativo, haciendo una revisión sistemática de 24 estudios experimentales y cuasiexperimentales publicados en los últimos 5 años que analizan mediciones de carga cognitiva en distintas formas de aprendizaje colaborativo, con el fin de clarificar esta relación. Los resultados sugieren que el aprendizaje colaborativo reduce la carga cognitiva al distribuirla entre los miembros del grupo, pero también incrementa la carga cognitiva pertinente, conduciendo a un mejor aprendizaje. La adecuada estructuración y regulación pedagógica de las actividades colaborativas por parte del docente reduce la carga cognitiva de los estudiantes. El uso de estrategias metacognitivas compartidas y de herramientas visuales en el trabajo grupal también ayuda a gestionar la carga cognitiva. En conclusión, una gestión adecuada de la carga cognitiva mediante distintas estrategias optimiza los beneficios del aprendizaje colaborativo, aunque se requiere más investigación al respecto.

Descargas

La descarga de datos todavía no está disponible.

Biografía del autor/a

Luis Orbegoso-Dávila

Doctor en Educación con mención en Ciencias de la Educación. Docente en la Universidad Nacional de Trujillo, Trujillo, Perú. E-mail: lorbegosod@unitru.edu.pe  ORCID: https://orcid.org/0000-0002-4089-6513

Iris Liliana Vásquez Alburqueque

Doctora en Educación con mención en Ciencias de la Educación. Docente categoría Auxiliar en la Universidad Nacional de Trujillo, Trujillo, Perú. E-mail: ialburqueque@unitru.edu.pe ORCID: https://orcid.org/0000-0001-9831-3213

Fernando Ledesma-Pérez

Doctor en Educación. Docente en la Universidad César Vallejo, Lima, Perú. E-mail: fledesma@ucv.edu.pe ORCID: https://orcid.org/0000-0003-4572-1381

Wilson Hugo Chunga Amaya

Maestro en Derecho con mención en Derecho Civil y Comercial. Docente en la Universidad Antenor Orrego, sede Piura, Piura, Perú. E-mail: wchungaa1@upao.edu.pe ORCID: https://orcid.org/0000-0003-4600-4886

Citas

Arellano, F. J., Moreno, G. F., Culqui, C. O., y Tamayo, V. R. (2021). Procesamiento cerebral del lenguaje desde la perspectiva de la neurociencia y la psicolingüística. Revista de Ciencias Sociales (Ve), XXVII(4), 292-308. https://doi.org/10.31876/rcs.v27i4.37256

Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 50(2), 248-287. https://doi.org/10.1016/0749-5978(91)90022-L

Bolatli, Z., y Korucu, A. T. (2020). Determining the academic achievement of students who use flipped classroom method supported by a mobile application and their views on collaborative learning. Bartin Üniversitesi Egitim Fakültesi Dergisi, 9(2), 229-251. https://doi.org/10.14686/buefad.631835

Brown, J. S., Collins, A., y Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42. https://doi.org/10.3102/0013189X018001032

Cai, H., y Gu, X. (2019). Supporting collaborative learning using a diagram‐based visible thinking tool based on cognitive load theory. British Journal of Educational Technology, 50(5), 2329-2345. https://doi.org/10.1111/bjet.12818

Cavus, N., Sani, A. S., Haruna, Y., y Lawan, A. A. (2021). Efficacy of social networking sites for sustainable education in the era of COVID-19: A systematic review. Sustainability, 13(2), 808. https://doi.org/10.3390/su13020808

Chi, M. T. H. (2009). Active-constructive-interactive: A conceptual framework for differentiating learning activities. Topics in Cognitive Science, 1(1), 73-105. https://doi.org/10.1111/j.1756-8765.2008.01005.x

Collazos, C. A., Guerrero, L. A., Pino, J. A., y Ochoa, S. F. (2002). Evaluating collaborative learning processes. In J. M. Haake y J. A. Pino (Eds.), Groupware: Design, implementation, and use. CRIWG, 2002. Lecture Notes in Computer Science (Vol. 2440, pp. 203-221). Springer. https://doi.org/10.1007/3-540-46124-8_14

Compte, M., y Sánchez, M. (2019). Aprendizaje colaborativo en el sistema de educación superior ecuatoriano. Revista de Ciencias Sociales (Ve), XXV(2), 131-140. https://produccioncientificaluz.org/index.php/rcs/article/view/27342

Costley, J. (2019). The relationship between social presence and cognitive load. Interactive Technology and Smart Education, 16(2), 172-182. https://doi.org/10.1108/ITSE-12-2018-0107

Costley, J. (2021). How role-taking in a group-work setting affects the relationship between the amount of collaboration and germane cognitive load. International Journal of Educational Technology in Higher Education, 18(1), 24. https://doi.org/10.1186/s41239-021-00259-w

Costley, J., y Fanguy, M. (2021). Collaborative note-taking affects cognitive load: The interplay of completeness and interaction. Educational Technology Research and Development, 69(2), 655-671. https://doi.org/10.1007/s11423-021-09979-2

Costley, J., y Lange, C. (2018). The moderating effects of group work on the relationship between motivation and cognitive load. International Review of Research in Open and Distance Learning, 19(1), 68-90. https://doi.org/10.19173/irrodl.v19i1.3325

De Leng, B., y Pawelka, F. (2021). The cognitive load of the in-class phase of a flipped classroom course on radiology: Could computer support be of help? Medical Teacher, 43(2), 216-222. https://doi.org/10.1080/0142159X.2020.1841890

Fischer, F., Kollar, I., Mandl, H., y Haake, J. M. (Eds.) (2007). Scripting computer-supported collaborative learning: Cognitive, computational and educational perspectives. Springer.

Graneheim, U. H., y Lundman, B. (2004). Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105-112. https://doi.org/10.1016/j.nedt.2003.10.001

Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., Gagnon, M.‑P., Griffiths, F., Nicolau, B., O’Cathain, A., Rousseau, M.‑C., Vedel, I., y Pluye, P. (2018). The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Education for Information, 34(4), 285-291. https://doi.org/10.3233/EFI-180221

Hutchins, E. (2001). Cognition, distributed. In N. J. Smelser y P. B. Baltes (Eds.), International Encyclopedia of the Social & Behavioral Sciences (pp. 2068-2072). Elsevier. https://doi.org/10.1016/B0-08-043076-7/01636-3

Iiskala, T., Vauras, M., Lehtinen, E., y Salonen, P. (2011). Socially shared metacognition of dyads of pupils in collaborative mathematical problem-solving processes. Learning and Instruction, 21(3), 379-393. https://doi.org/10.1016/j.learninstruc.2010.05.002

Janssen, J., Kirschner, F., Erkens, G., Kirschner, P. A., y Paas, F. (2010). Making the black box of collaborative learning transparent: Combining process-oriented and cognitive load approaches. Educational Psychology Review, 22(2), 139-154. https://doi.org/10.1007/s10648-010-9131-x

Janssen, J., y Kirschner, P. A. (2020). Applying collaborative cognitive load theory to computer-supported collaborative learning: Towards a research agenda. Educational Technology Research and Development, 68(2), 783-805. https://doi.org/10.1007/s11423-019-09729-5

Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J., y Sobocinski, M. (2016). How do types of interaction and phases of self-regulated learning set a stage for collaborative engagement? Learning and Instruction, 43, 39-51. https://doi.org/10.1016/j.learninstruc.2016.01.005

Johnson, D. W., y Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38(5), 365-379. https://doi.org/10.3102/0013189X09339057

Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need? Educational Psychology Review, 23(1), 1-19. https://doi.org/10.1007/s10648-010-9150-7

Kalyuga, S., y Singh, A.‑M. (2016). Rethinking the boundaries of cognitive load theory in complex learning. Educational Psychology Review, 28(4), 831-852. https://doi.org/10.1007/s10648-015-9352-0

Kennelly, J. (2011). Methodological approach to assessing the evidence. In A. Handler, J. Kennelly y N. Peacock (Eds.), Reducing racial/ethnic disparities in reproductive and perinatal outcomes (pp. 7-19). Springer. https://doi.org/10.1007/978-1-4419-1499-6_2

Kiewra, K. A. (1987). Notetaking and review: The research and its implications. Instructional Science, 16(3), 233-249. https://doi.org/10.1007/BF00120252

Kirschner, F., Paas, F., y Kirschner, P. (2009). A cognitive load approach to collaborative learning: United brains for complex tasks. Educational Psychology Review, 21(1), 31-42. https://doi.org/10.1007/s10648-008-9095-2

Kirschner, F., Paas, F., y Kirschner, P. A. (2011). Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect. Applied Cognitive Psychology, 25(4), 615-624. https://doi.org/10.1002/acp.1730

Kirschner, P. A., Kirschner, F., y Janssen, J. (2014). The collaboration principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (pp. 547-575). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.027

Kirschner, P. A., Sweller, J., Kirschner, F., y Zambrano, J. (2018). From cognitive load theory to collaborative cognitive load theory. International Journal of Computer-Supported Collaborative Learning, 13(2), 213-233. https://doi.org/10.1007/s11412-018-9277-y

Kolić-Vehovec, S., Pahljina-Reinić, R., y Rončević, B. (2022). Effects of collaboration and informing students about overconfidence on metacognitive judgment in conceptual learning. Metacognition and Learning, 17(1), 87-116. https://doi.org/10.1007/s11409-021-09275-7

Lange, C. H., Costley, J., y Fanguy, M. (2021). Collaborative group work and the different types of cognitive load. Innovations in Education and Teaching International, 58, 377-386. https://doi.org/10.1080/14703297.2020.1788970

Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., y Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Journal of Clinical Epidemiology, 62(10), e1-e34. https://doi.org/10.1016/j.jclinepi.2009.06.006

Lindgren, B.‑M., Lundman, B., y Graneheim, U. H. (2020). Abstraction and interpretation during the qualitative content analysis process. International Journal of Nursing Studies, 108, 103632. https://doi.org/10.1016/j.ijnurstu.2020.103632

Lu, J., Chen, X., Wang, X., Zhong, R., y Wang, H. (2022). Research on the influence of socially regulated learning on online collaborative knowledge building in the post COVID-19 period. Sustainability, 14(22), 15345. https://doi.org/10.3390/su142215345

Mayer, R. E. (2014). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (pp. 43-71). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.005

Moola, S., Munn, Z., Tufanaru, C., Aromataris, E., Sears, K., Sfetcu, R., Currie, M., Lisy, K., Qureshi, R., Mattis, P., y Mu, P. (2020). Systematic reviews of etiology and risk. In E. Aromataris, C. Lockwood, K. Porritt, B. Pilla y Z. Jordan (Eds.), JBI Manual for Evidence Synthesis. JBI. https://doi.org/10.46658/JBIMES-24-06

Novak, J. D., y Cañas, A. J. (2006). The theory underlying concept maps and how to construct them: Technical Report IHMC CmapTools 2006-01 Rev 01-2008. Institute for Human and Machine Cognition. https://cmap.ihmc.us/publications/researchpapers/theoryunderlyingconceptmaps.pdf

Olivares, G. F., Marquina, R. J., Delgado, L. A., y Haro, M. D. R. (2024). Aprendizaje cooperativo y rendimiento académico en la Escuela de Oficiales de la Policía Nacional del Perú. Revista de Ciencias Sociales (Ve), XXX(1), 398-409. https://doi.org/10.31876/rcs.v30i1.41663

Oluwajana, D., Adeshola, I., y Clement, S. (2023). Does the use of a web-based collaborative platform reduce cognitive load and influence project-based student engagement? Current Psychology, 42, 8265-8278. https://doi.org/10.1007/s12144-021-02145-0

Onrubia, J., y Engel, A. (2009). Strategies for collaborative writing and phases of knowledge construction in CSCL environments. Computers and Education, 53(4), 1256-1265. https://doi.org/10.1016/j.compedu.2009.06.008

Rabie-Ahmed, A., y Mohamed, A. (2022). Collaborative and individual vocabulary learning in the Arabic classroom: The role of engagement and task demands. Foreign Language Annals, 55(4), 1006-1024. https://doi.org/10.1111/flan.12636

Rogoff, B., y Mejía-Arauz, R. (2022). The key role of community in Learning by observing and pitching in to family and community endeavours. Journal for the Study of Education and Development, 45(3), 494-548. https://doi.org/10.1080/02103702.2022.2086770

Schnaubert, L., y Bodemer, D. (2019). Providing different types of group awareness information to guide collaborative learning. International Journal of Computer-Supported Collaborative Learning, 14(1), 7-51. https://doi.org/10.1007/s11412-018-9293-y

Schreier, M. (2012). Qualitative content analysis in practice. Sage.

Shin, Y., y Jung, J. (2020). The effects of a visible-annotation tool for sequential knowledge construction on discourse patterns and collaborative outcomes. Australasian Journal of Educational Technology, 36(4), 57-71. https://doi.org/10.14742/ajet.4875

Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1). http://www.itdl.org/Journal/Jan_05/article01.htm

Sithole, S., Datt, R., De Lange, P., y Tharapos, M. (2021). Learning accounting through visual representations. Accounting Research Journal, 34(4), 365-384. https://doi.org/10.1108/ARJ-06-2018-0100

Sugiman, Retnowati, E., Ayres, P., y Murdanu (2019). Learning goal-free problems: Collaboratively or individually? Cakrawala Pendidikan, 38(3), 590-600. https://doi.org/10.21831/cp.v38i3.26914

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285. https://doi.org/10.1016/0364-0213(88)90023-7

Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295-312. https://doi.org/10.1016/0959-4752(94)90003-5

Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123-138. https://doi.org/10.1007/s10648-010-9128-5

Sweller, J., Ayres, P., y Kalyuga, S. (2011). Cognitive load theory. Springer. https://doi.org/10.1007/978-1-4419-8126-4

Sweller, J., Van Merrienboer, J. J. G., y Paas, F. G. W. C. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3), 251-296. https://doi.org/10.1023/A:1022193728205

Tan, E., De Weerd, J. G., y Stoyanov, S. (2021). Supporting interdisciplinary collaborative concept mapping with individual preparation phase. Educational Technology Research and Development, 69(2), 607-626. https://doi.org/10.1007/s11423-021-09963-w

Vygotski, L. S. (2012). El desarrollo de los procesos psicológicos superiores. Austral.

Vygotski, L. S., y Cole, M. (1978). Mind in society. Harvard University Press.

Wang, C., Fang, T., y Gu, Y. (2020). Learning performance and behavioral patterns of online collaborative learning: Impact of cognitive load and affordances of different multimedia. Computers & Education, 143, 103683. https://doi.org/10.1016/j.compedu.2019.103683

Webb, M., Tracey, M., Harwin, W., Tokatli, O., Hwang, F., Johnson, R., Barrett, N., y Jones, C. (2022). Haptic-enabled collaborative learning in virtual reality for schools. Education and Information Technologies, 27(2), 937-960. https://doi.org/10.1007/s10639-021-10639-4

Wood, D., Bruner, J. S., y Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 17(2), 89-100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x

Zambrano, J., Kirschner, F., Sweller, J., y Kirschner, P. A. (2019). Effects of group experience and information distribution on collaborative learning. Instructional Science, 47(5), 531-550. https://doi.org/10.1007/s11251-019-09495-0

Zhang, L., Wang, X., He, T., y Han, Z. (2022). A data-driven optimized mechanism for improving online collaborative learning: Taking cognitive load into account. International Journal of Environmental Research and Public Health, 19(12), 6984. https://doi.org/10.3390/ijerph19126984

Zheng, L., Li, X., Zhang, X., y Sun, W. (2019). The effects of group metacognitive scaffolding on group metacognitive behaviors, group performance, and cognitive load in computer-supported collaborative learning. The Internet and Higher Education, 42, 13-24. https://doi.org/10.1016/j.iheduc.2019.03.002

Zheng, L., Zhong, L., y Fan, Y. (2023). An immediate analysis of the interaction topic approach to promoting group performance, knowledge convergence, cognitive engagement, and coregulation in online collaborative learning. Education and Information Technologies, 28, 9913-9934. https://doi.org/10.1007/s10639-023-11588-w

Zhou, X., Chen, L.‑H., y Chen, C.‑L. (2019). Collaborative learning by teaching: A pedagogy between learner-centered and learner-driven. Sustainability, 11(4), 1174. https://doi.org/10.3390/su11041174
Publicado
2024-04-12
Cómo citar
Orbegoso-Dávila, L., Vásquez Alburqueque, I. L., Ledesma-Pérez, F., & Chunga Amaya, W. H. (2024). Carga cognitiva en el aprendizaje colaborativo: Una revisión sistemática. Revista De Ciencias Sociales, 30(2), 387-402. https://doi.org/10.31876/rcs.v30i2.41917
Sección
Artículos