Microlearning, Sustained Attention, and Working Memory in Students: A Systematic Review from a Neuroeducational Perspective

Authors

DOI:

https://doi.org/10.63688/ed701327

Keywords:

microlearning, sustained attention, working memory, neuroeducation

Abstract

The aim of this study was to analyze the scientific evidence regarding the effect of microlearning strategies on sustained attention and working memory in students from a neuroeducational perspective. A systematic literature review was conducted following PRISMA guidelines. The search was carried out in Scopus, ScienceDirect, SpringerLink, Google Scholar, and SciELO databases, considering publications from 2015 to 2025. After applying the inclusion and exclusion criteria, 16 scientific articles were selected for analysis. The findings showed that microlearning enhances sustained attention by presenting content in brief and structured learning units that reduce cognitive overload. Likewise, this strategy was found to strengthen working memory through improved organization and processing of information. From a neuroeducational perspective, the results suggest that microlearning is an effective methodology for optimizing cognitive processes related to learning and improving academic performance in different educational settings. It is concluded that microlearning represents an innovative pedagogical alternative with significant potential to meet the demands of contemporary learning environments.

References

Baddeley, A. D. (2012). Working memory: Theories, models, and controversies. Annual Review of Psychology, 63(1), 1–29. DOI: https://doi.org/10.1146/annurev-psych-120710-100422

Cowan, N. (2014). Working memory underpins cognitive development, learning, and education. Educational Psychology Review, 26(2), 197–223. DOI: https://doi.org/10.1007/s10648-013-9246-y

Adele Diamond (2013). Executive functions. Annual Review of Psychology, 64, 135–168. DOI: https://doi.org/10.1146/annurev-psych-113011-143750

Gathercole, S. E., & Alloway, T. P. (2008). Working memory and learning: A practical guide for teachers. SAGE Publications.

Giurgiu, L. (2017). Microlearning an evolving elearning trend. Scientific Bulletin, 22(1), 18–23.

Howard-Jones, P. A. (2014). Neuroscience and education: Myths and messages. Nature Reviews Neuroscience, 15(12), 817–824. DOI: https://doi.org/10.1038/nrn3817

Immordino-Yang, M. H., & Antonio Damasio (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education, 1(1), 3–10. DOI: https://doi.org/10.1111/j.1751-228X.2007.00004.x

Jahnke, I., Lee, Y. M., Pham, M., He, H., & Austin, L. (2020). Unpacking the inherent design principles of mobile microlearning. Technology, Knowledge and Learning, 25(3), 585–619. DOI: https://doi.org/10.1007/s10758-019-09413-w

Jensen, E. (2008). Brain-based learning: The new paradigm of teaching (2nd ed.). Corwin Press.

Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Keele University.

Leong, K., Sung, A., Au, D., & Blanchard, C. (2021). A review of the trend of microlearning. Sustainability, 13(6), 3250. DOI: https://doi.org/10.3390/su13063250

Okoli, C. (2015). A guide to conducting a standalone systematic literature review. Communications of the Association for Information Systems, 37(1), 879–910. DOI: https://doi.org/10.17705/1CAIS.03743

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., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. DOI: https://doi.org/10.1136/bmj.n71

Posner, M. I., & Rothbart, M. K. (2007). Research on attention networks as a model for the integration of psychological science. Annual Review of Psychology, 58, 1–23. DOI: https://doi.org/10.1146/annurev.psych.58.110405.085516

Ratey, J. J. (2008). Spark: The revolutionary new science of exercise and the brain. Little, Brown and Company.

Shail, M. S. (2019). Using micro-learning on mobile applications to increase knowledge retention and work performance: A review of literature. International Journal of Interactive Mobile Technologies, 13(8), 150–168. DOI: https://doi.org/10.3991/ijim.v13i08.10792

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. DOI: https://doi.org/10.1016/j.jbusres.2019.07.039

Sohlberg, M. M., & Mateer, C. A. (2001). Cognitive rehabilitation: An integrative neuropsychological approach. Guilford Press.

John Sweller (2011). Cognitive load theory. En J. P. Mestre & B. H. Ross (Eds.), The psychology of learning and motivation (Vol. 55, pp. 37–76). Academic Press. DOI: https://doi.org/10.1016/B978-0-12-387691-1.00002-8

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. DOI: https://doi.org/10.1111/1467-8551.00375

Zull, J. E. (2002). The art of changing the brain: Enriching the practice of teaching by exploring the biology of learning. Stylus Publishing.

Published

2026-06-11

How to Cite

Soledispa Aguilar, J. A., Suárez Castro, S. G., Guevara Masqui, M. V., Quishpe Peña, E. J., & Rodríguez Yepez, C. A. (2026). Microlearning, Sustained Attention, and Working Memory in Students: A Systematic Review from a Neuroeducational Perspective. Sage Sphere of Technology, Sciences, Discoveries And Society, 4(1), 1-16. https://doi.org/10.63688/ed701327