Aplicación de los principios de la teoría cognitiva del aprendizaje multimedia al diseño de situaciones de aprendizaje y escenarios de formación
Revisión sistemática de literatura
Resumen La teoría cognitiva del aprendizaje multimedia (TCAM) ha impulsado el desarrollo de múltiples estudios en torno a cómo diseñar materiales y escenarios que logren un verdadero aprendizaje. Teniendo en cuenta estas características, el artículo realiza una revisión de la literatura para identificar las áreas de conocimiento en las que se vienen realizando estudios basados en la TCAM, así como los principales hallazgos a los que han llegado. Para esto, se utiliza una metodología de revisión sistemática de la literatura basada en el estudio de artículos de investigación entre 2018 y 2021 seleccionados a través de Scopus y Web of Science. Se concluye que las áreas donde más se ha explorado el uso de la TCAM ha sido la enseñanza de idiomas (inglés y mandarín), la medicina (combina especialidades médicas y enfermería), la ingeniería (civil, de sistemas, eléctrica) y la geografía. Entre los principales hallazgos se identifican los principios más utilizados, como el de redundancia, señalización y coherencia; se valida la importancia de aplicar los principios de la TCAM en el diseño de materiales y situaciones de aprendizaje para lograr efectos asociados a la reducción de la carga cognitiva. Los estudios resaltan la importancia de su manejo por parte de docentes y diseñadores instruccionales, la relevancia de considerar su aplicación en el diseño de videos educativos y la necesidad de tener en cuenta las condiciones de los estudiantes a los que se dirige la formación.
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Aysolmaz, B., & Reijers, H. A. (2021). Animation as a dynamic visualization technique for improving process model comprehension. Information & Management, 58(5), 103478. 10.1016/j.im.2021.103478
Berardi, S. (2021). Creating an Online Russian as a Foreign Language Course during the COVID-19 Epidemic. Rusistika (Moskva. Online), 19(1), 7–20. 10.22363/2618-8163-2021-19-1-7-20
Berntsen, H., & Kristiansen, E. (2019). Successful coach learning: Digital workbook informed by pedagogical principles. International Journal of Sports Science & Coaching, 14(3), 310–323. 10.1177/1747954119835439
Burkhart, C., Lachner, A., & Nückles, M. (2021). Using spatial contiguity and signaling to optimize visual feedback on students’ written explanations. Journal of Educational Psychology, 113(5), 998–1023. 10.1037/edu0000607
Castro-Alonso, J. C., de Koning, B. B., Fiorella, L., & Paas, F. (2021). Five Strategies for Optimizing Instructional Materials: Instructor- and Learner-Managed Cognitive Load. Educational Psychology Review, 33(4), 1379–1407. 10.1007/s10648-021-09606-9
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Groshans, G., Mikhailova, E., Post, C., Schlautman, M., Carbajales-Dale, P., & Payne, K. (2019). Digital Story Map Learning for STEM Disciplines. Education Sciences, 9(2), 75. 10.3390/educsci9020075
Hadie, S. N. H., Tan, V. P. S., Omar, N., Nik Mohd Alwi, N. A., Lim, H. L., & Ku Marsilla, K. I. (2021). COVID-19 Disruptions in Health Professional Education: Use of Cognitive Load Theory on Students’ Comprehension, Cognitive Load, Engagement, and Motivation. Frontiers in Medicine, 8, 739238. 10.3389/fmed.2021.739238
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Kutbay, E., & Akpınar, Y. (2020). Investigating Modality, Redundancy and Signaling Principles with Abstract and Concrete Representation. International Journal of Education in Mathematics, Science and Technology, 8(2), 131–145. 10.46328/ijemst.v8i2.710
Lai, A.-F., Chen, C.-H., & Lee, G.-Y. (2019). An augmented reality-based learning approach to enhancing students’ science reading performances from the perspective of the cognitive load theory. British Journal of Educational Technology, 50(1), 232–247. 10.1111/bjet.12716
Lin, H.-Y., & Tsai, S.-C. (2021). Student perceptions towards the usage of AR-supported STEMUP application in mobile courses development and its implementation into English learning. Australasian Journal of Educational Technology, 37(3), 88–103. 10.14742/ajet.6125
Liu, Y., Jang, B. G., & Roy-Campbell, Z. (2018). Optimum input mode in the modality and redundancy principles for university ESL students’ multimedia learning. Computers & Education, 127, 190–200. 10.1016/j.compedu.2018.08.025
Lotero, L. A. A. (2012). Teoría de la carga cognitiva, diseño multimedia y aprendizaje: un estado del arte. Magis, Revista Internacional de Investigación en Educación, 5(10).
Mahajan, R., Gupta, K., Gupta, P., Kukreja, S., & Singh, T. (2020). Multimedia Instructional Design Principles: Moving from Theoretical Rationale to Practical Applications. Indian Pediatrics, 57(6), 555–560. 10.1007/s13312-020-1854-2
Mayer, R.E. (2011). Applying the science of learning. Pearson. 10.1016/B978-0-12-387691-1.00003-X
Mirkovski, K., Gaskin, J. E., Hull, D. M., & Lowry, P. B. (2019). Visual storytelling for improving the comprehension and utility in disseminating information systems research: Evidence from a quasi-experiment. Information Systems Journal, 29(6), 1153–1177. 10.1111/isj.12240
Noetel, M., Griffith, S., Delaney, O., Harris, N. R., Sanders, T., Parker, P., del Pozo Cruz, B., & Lonsdale, C. (2022). Multimedia Design for Learning: An Overview of Reviews With Meta-Meta-Analysis. Review of Educational Research, 92(3), 413–454. 10.3102/00346543211052329
Noyes, J. A., Carbonneau, K. J., Gotch, C. M., & Matthew, S. M. (2020). Is a Picture Worth a Thousand Words? Evaluating the Design of Instructional Animations in Veterinary Education. Journal of Veterinary Medical Education, 47(1), 69–77. 10.3138/jvme.0118-002r
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Ramezanali, N., & Faez, F. (2019). Vocabulary learning and retention through multimedia glossing. Language Learning & Technology, 23(2), 105–124. 10125/44685
Rat, A.-C., Ricci, L., Guillemin, F., Ricatte, C., Pongy, M., Vieux, R., Spitz, E., & Muller, L. (2018). Development of a Web-Based Formative Self-Assessment Tool for Physicians to Practice Breaking Bad News (BRADNET). JMIR Medical Education, 4(2), e9551. 10.2196/mededu.9551
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Soicher, R. N., & Becker-Blease, K. A. (2020). Testing the segmentation effect of multimedia learning in a biological system. Journal of Computer Assisted Learning, 36(6), 825–837. 10.1111/jcal.12485
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Tin, T. G., Atan, N. A., Mohamad Said, M. N. H., Ali, M. F., Mohd, S., & Abd Hamid, M. Z. (2018). Integrating Animations in Chinese Character Writing Based on Cognitive Theory of Multimedia Learning to Promote Students’ Writing Skills. International Journal of Interactive Mobile Technologies, 12(7), 97–111. 10.3991/ijim.v12i7.9671
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Wang, T.-K., Huang, J., Liao, P.-C., & Piao, Y. (2018). Does Augmented Reality Effectively Foster Visual Learning Process in Construction? An Eye-Tracking Study in Steel Installation. Advances in Civil Engineering, 2018, e2472167. 10.1155/2018/2472167
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Aravind, B. R., & Rajasekaran, V. (2021). Exploring dysphasia learners’ vocabulary acquisition through the cognitive theory of multimedia learning: an experimental study. International Journal of Emerging Technologies in Learning (IJET), 16(12), 263–275. 10.3991/ijet.v16i12.22173
Aysolmaz, B., & Reijers, H. A. (2021). Animation as a dynamic visualization technique for improving process model comprehension. Information & Management, 58(5), 103478. 10.1016/j.im.2021.103478
Berardi, S. (2021). Creating an Online Russian as a Foreign Language Course during the COVID-19 Epidemic. Rusistika (Moskva. Online), 19(1), 7–20. 10.22363/2618-8163-2021-19-1-7-20
Berntsen, H., & Kristiansen, E. (2019). Successful coach learning: Digital workbook informed by pedagogical principles. International Journal of Sports Science & Coaching, 14(3), 310–323. 10.1177/1747954119835439
Burkhart, C., Lachner, A., & Nückles, M. (2021). Using spatial contiguity and signaling to optimize visual feedback on students’ written explanations. Journal of Educational Psychology, 113(5), 998–1023. 10.1037/edu0000607
Castro-Alonso, J. C., de Koning, B. B., Fiorella, L., & Paas, F. (2021). Five Strategies for Optimizing Instructional Materials: Instructor- and Learner-Managed Cognitive Load. Educational Psychology Review, 33(4), 1379–1407. 10.1007/s10648-021-09606-9
Castro-Alonso, J. C., Wong, R. M., Adesope, O. O., & Paas, F. (2021). Effectiveness of Multimedia Pedagogical Agents Predicted by Diverse Theories: A Meta-Analysis. Educational Psychology Review, 33(3), 989–1015. 10.1007/s10648-020-09587-1
Çekiç, A., & Demirezen, M. (2021). Comparison of the impacts of different multimodalities on incidental L2 vocabulary learning. Moderna språk, 114(2), 109–138. 10.58221/mosp.v114i2.7405
Chan, K. Y., Lyons, C., Kon, L. L., Stine, K., Manley, M., & Crossley, A. (2020). Effect of on-screen text on multimedia learning with native and foreign-accented narration. Learning and Instruction, 67, 101305. 10.1016/j.learninstruc.2020.101305
Chang, C.-C., Warden, C. A., Liang, C., & Lin, G.-Y. (2018). Effects of digital game-based learning on achievement, flow and overall cognitive load. Australasian Journal of Educational Technology, 34(4), 4. 10.14742/ajet.2961
Clark, R. C., & Mayer, R. E. (Eds.). (2016). e-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning (4th ed.). John Wiley & Sons. 10.1002/9781119239086
Cojean, S., & Jamet, E. (2022). Does an interactive table of contents promote learning from videos? A study of consultation strategies and learning outcomes. British Journal of Educational Technology, 53(2), 269–285. 10.1111/bjet.13164
De Las Peñas, M., Verzosa, D. M., Aberin, M. A. Q., Garces, L. P. D. M., Francisco, F. F., Bautista, E. P., Tolentino, M. A. C., & Tabares, W. C. (2019). Digital Simulations for Grade 7 to 10 Mathematics. Philippine Journal of Science, 148(4), 735–749.
Dirkx, K. J. H., Skuballa, I., Manastirean-Zijlstra, C. S., & Jarodzka, H. (2021). Designing computer-based tests: Design guidelines from multimedia learning studied with eye tracking. Instructional Science, 49(5), 589–605. 10.1007/s11251-021-09542-9
Drees, C., Ghebremedhin, E., & Hansen, M. (2020). Development of an interactive e-learning software “Histologie für Mediziner” for medical histology courses and its overall impact on learning outcomes and motivation. GMS Journal for Medical Education, 37(3), Doc35. 10.3205/zma001328
Dulamă, M. E., & Ilovan, O.-R. (2020). Online university education during the COVID-19 pandemic. How efficient are the adapted instruction models? Journal of Educational Sciences & Psychology, 10(2), 92–111.
Ferreira González, I., Urrútia, G., & Alonso-Coello, P. (2011). Revisiones sistemáticas y metaanálisis: Bases conceptuales e interpretación. Revista Española de Cardiología, 64(8), 688–696. 10.1016/j.recesp.2011.03.029
Gansemer-Topf, A. M., Paepcke-Hjeltness, V., Russell, A. E., & Schiltz, J. (2021). “Drawing” your Own Conclusions: Sketchnoting as a Pedagogical Tool for Teaching Ecology. Innovative Higher Education, 46(3), 303–319. 10.1007/s10755-020-09542-6
García-Peñalvo, F. J. (2022). Developing robust state-of-the-art reports: Systematic Literature Reviews. Education in the Knowledge Society, 23, e28600. 10.14201/eks.28600
Greenberg, K., Zheng, R., Gardner, M., & Orr, M. (2021). Individual differences in visuospatial working memory capacity influence the modality effect. Journal of Computer Assisted Learning, 37(3), 735–744. 10.1111/jcal.12519
Groshans, G., Mikhailova, E., Post, C., Schlautman, M., Carbajales-Dale, P., & Payne, K. (2019). Digital Story Map Learning for STEM Disciplines. Education Sciences, 9(2), 75. 10.3390/educsci9020075
Hadie, S. N. H., Tan, V. P. S., Omar, N., Nik Mohd Alwi, N. A., Lim, H. L., & Ku Marsilla, K. I. (2021). COVID-19 Disruptions in Health Professional Education: Use of Cognitive Load Theory on Students’ Comprehension, Cognitive Load, Engagement, and Motivation. Frontiers in Medicine, 8, 739238. 10.3389/fmed.2021.739238
Kamal M. (2019) Effect of interactive video length within e-learning environments on cognitive load, cognitive achievement and retention of learning. Turkish Online Journal of Distance Education, 21(4), 68–89. 10.17718/tojde.803360
Kutbay, E., & Akpınar, Y. (2020). Investigating Modality, Redundancy and Signaling Principles with Abstract and Concrete Representation. International Journal of Education in Mathematics, Science and Technology, 8(2), 131–145. 10.46328/ijemst.v8i2.710
Lai, A.-F., Chen, C.-H., & Lee, G.-Y. (2019). An augmented reality-based learning approach to enhancing students’ science reading performances from the perspective of the cognitive load theory. British Journal of Educational Technology, 50(1), 232–247. 10.1111/bjet.12716
Lin, H.-Y., & Tsai, S.-C. (2021). Student perceptions towards the usage of AR-supported STEMUP application in mobile courses development and its implementation into English learning. Australasian Journal of Educational Technology, 37(3), 88–103. 10.14742/ajet.6125
Liu, Y., Jang, B. G., & Roy-Campbell, Z. (2018). Optimum input mode in the modality and redundancy principles for university ESL students’ multimedia learning. Computers & Education, 127, 190–200. 10.1016/j.compedu.2018.08.025
Lotero, L. A. A. (2012). Teoría de la carga cognitiva, diseño multimedia y aprendizaje: un estado del arte. Magis, Revista Internacional de Investigación en Educación, 5(10).
Mahajan, R., Gupta, K., Gupta, P., Kukreja, S., & Singh, T. (2020). Multimedia Instructional Design Principles: Moving from Theoretical Rationale to Practical Applications. Indian Pediatrics, 57(6), 555–560. 10.1007/s13312-020-1854-2
Mayer, R.E. (2011). Applying the science of learning. Pearson. 10.1016/B978-0-12-387691-1.00003-X
Mirkovski, K., Gaskin, J. E., Hull, D. M., & Lowry, P. B. (2019). Visual storytelling for improving the comprehension and utility in disseminating information systems research: Evidence from a quasi-experiment. Information Systems Journal, 29(6), 1153–1177. 10.1111/isj.12240
Noetel, M., Griffith, S., Delaney, O., Harris, N. R., Sanders, T., Parker, P., del Pozo Cruz, B., & Lonsdale, C. (2022). Multimedia Design for Learning: An Overview of Reviews With Meta-Meta-Analysis. Review of Educational Research, 92(3), 413–454. 10.3102/00346543211052329
Noyes, J. A., Carbonneau, K. J., Gotch, C. M., & Matthew, S. M. (2020). Is a Picture Worth a Thousand Words? Evaluating the Design of Instructional Animations in Veterinary Education. Journal of Veterinary Medical Education, 47(1), 69–77. 10.3138/jvme.0118-002r
Oakley, B. A., & Sejnowski, T. J. (2019). What we learned from creating one of the world’s most popular MOOCs. Npj Science of Learning, 4(1), 1–7. 10.1038/s41539-019-0046-0
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. 10.1136/bmj.n71
Parong, J., & Mayer, R. E. (2018). Learning Science in Immersive Virtual Reality. Journal of Educational Psychology, 110(6), 785–797. 10.1037/edu0000241
Ramezanali, N., & Faez, F. (2019). Vocabulary learning and retention through multimedia glossing. Language Learning & Technology, 23(2), 105–124. 10125/44685
Rat, A.-C., Ricci, L., Guillemin, F., Ricatte, C., Pongy, M., Vieux, R., Spitz, E., & Muller, L. (2018). Development of a Web-Based Formative Self-Assessment Tool for Physicians to Practice Breaking Bad News (BRADNET). JMIR Medical Education, 4(2), e9551. 10.2196/mededu.9551
Raviolo, A. (2019). Images and teaching of Chemistry. Contributions of the Cognitive Theory of Multimedia Learning. Educación química, 30(2), 114–128. 10.22201/fq.18708404e.2019.2.67174
Refat, N., Rahman, M. A., Asyhari, A. T., Kassim, H., Kurniawan, I. F., & Rahman, M. (2020). MATT: A Mobile Assisted Tense Tool for Flexible m-Grammar Learning Based on Cloud-Fog-Edge Collaborative Networking. IEEE Access, 8, 66074–66084. 10.1109/ACCESS.2020.2983310
Refat, N., Rahman, M. A., Asyhari, A. T., Kurniawan, I. F., Bhuiyan, M. Z. A., & Kassim, H. (2019). Interactive Learning Experience-Driven Smart Communications Networks for Cognitive Load Management in Grammar Learning Context. IEEE Access, 7, 64545–64557. 10.1109/ACCESS.2019.2915174
Rey, G. D., Beege, M., Nebel, S., Wirzberger, M., Schmitt, T. H., & Schneider, S. (2019). A Meta-analysis of the Segmenting Effect. Educational Psychology Review, 31(2), 389–419. 10.1007/s10648-018-9456-4
Shoufan, A. (2019). Estimating the cognitive value of YouTube’s educational videos: A learning analytics approach. Computers in Human Behavior, 92, 450–458. 10.1016/j.chb.2018.03.036
Soicher, R. N., & Becker-Blease, K. A. (2020). Testing the segmentation effect of multimedia learning in a biological system. Journal of Computer Assisted Learning, 36(6), 825–837. 10.1111/jcal.12485
Stull, A. T., Fiorella, L., Gainer, M. J., & Mayer, R. E. (2018). Using transparent whiteboards to boost learning from online STEM lectures. Computers & Education, 120, 146–159. 10.1016/j.compedu.2018.02.005
Tin, T. G., Atan, N. A., Mohamad Said, M. N. H., Ali, M. F., Mohd, S., & Abd Hamid, M. Z. (2018). Integrating Animations in Chinese Character Writing Based on Cognitive Theory of Multimedia Learning to Promote Students’ Writing Skills. International Journal of Interactive Mobile Technologies, 12(7), 97–111. 10.3991/ijim.v12i7.9671
Tomita, K. (2018). Does the Visual Appeal of Instructional Media Affect Learners’ Motivation Toward Learning? TechTrends, 62(1), 103–112. 10.1007/s11528-017-0213-1
Tufan, D. (2021). Multimedia design principles for microlearning. In J. R. Corbeil, B. H. Khan, & M. E.Corbeil (Eds.), Microlearning in the Digital Age: The Design and Delivery of Learning in Snippets (pp. 58–79). Routledge. 10.4324/9780367821623-6
Wang, T.-K., Huang, J., Liao, P.-C., & Piao, Y. (2018). Does Augmented Reality Effectively Foster Visual Learning Process in Construction? An Eye-Tracking Study in Steel Installation. Advances in Civil Engineering, 2018, e2472167. 10.1155/2018/2472167
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