MICRO-LEARNING ACTIVITIES TO SUPPORT COGNITIVE TRANSFER IN HIGH-LOAD LEARNING CONDITIONS

Authors

Rǎzvan Bǎrbulescu
Bucharest University of Economic Studies image/svg+xml
Author
Vladimir Aurelian Enǎchescu
Bucharest University of Economic Studies image/svg+xml
Author

DOI:

https://doi.org/10.65222/VIRAL.2026.8.49.69

Keywords:

Retrieval practice Instructional design Knowledge retention Spaced practice Learner engagement

Abstract

As higher education increasingly addresses complex and interdisciplinary knowledge, students are frequently required to process substantial amounts of information within limited timeframes. Such high-load learning conditions may constrain knowledge retention and the transfer of learning to new contexts. This paper examines micro-learning as an instructional strategy for managing cognitive demands while strengthening retrieval, application, and transfer. Rather than replacing comprehensive instruction, micro-learning is conceptualized as a sequence of short, focused interventions strategically inserted before, during, and after complex learning episodes.
The study adopts a structured conceptual analysis informed by recent literature on cognitive load theory, retrieval practice, active learning, spacing, and instructional design. The analysis examines how established cognitive and pedagogical principles can inform the timing, duration, purpose, and sequencing of micro-learning interventions. Concepts were comparatively synthesized to identify design principles that reduce unnecessary processing demands while maintaining opportunities for active retrieval, reflection, and application. As a conceptual study, the paper does not test intervention effectiveness empirically but translates theoretical mechanisms into an actionable instructional framework.
The analysis results in a Micro-Learning for Cognitive Transfer Framework organized around four design components: activation, consolidation, application, and transfer. Activation occurs immediately before complex instruction through 2–3-minute prior-knowledge prompts, prediction questions, or concept-recall tasks. Consolidation is inserted during instruction at natural transition points through 3–5-minute retrieval questions, concept summaries, or misconception checks. Application follows major learning segments and uses 5–7-minute worked-example completion, short problem-solving tasks, or scenario-based decisions requiring learners to apply newly acquired knowledge. Transfer occurs after instruction, typically through 5–10-minute delayed activities in which students apply principles to unfamiliar cases, compare alternative solutions, or explain how knowledge can be used in a different context. Immediate or brief corrective feedback accompanies each stage where appropriate.
The framework suggests that the effectiveness of micro-learning depends less on simply shortening content than on where, when, and why short activities are embedded within the learning sequence. It guides educators in selecting intervention timing, cognitive purpose, activity type, feedback, and task complexity across face-to-face, blended, and online environments. The paper contributes an operational approach to learner-centred instructional design by connecting cognitive principles with concrete micro-level teaching decisions. Future empirical research should test the proposed sequence across disciplines and compare its effects on retention, transfer, cognitive load, and learner engagement.

Downloads

Download data is not yet available.

References

1. R. P. Díaz Redondo, M. Caeiro Rodríguez, J. J. López Escobar, and A. Fernández Vilas, “Integrating micro-learning content in traditional e-learning platforms,” Multimedia Tools and Applications, vol. 80, no. 2, pp. 3121–3151, 2021. https://doi.org/10.1007/s11042-020-09523-z

2. R. K. Dixit, P. S. Yalagi, and M. A. Nirgude, “Breaking the walls of classroom through micro learning: Short burst of learning,” Journal of Physics: Conference Series, vol. 1854, no. 1, p. 012018, 2021. https://doi.org/10.1088/1742-6596/1854/1/012018

3. C. Kossen and C. Y. Ooi, “Trialling micro-learning design to increase engagement in online courses,” Asian Association of Open Universities Journal, vol. 16, no. 3, pp. 299–310, 2021. https://doi.org/10.1108/AAOUJ-09-2021-0107

4. K. Boumalek, A. Bakki, A. El Mezouary, B. Hmedna, and M. Eddahibi, “Micro-learning design and micro-course structuring: A systematic literature review,” Interactive Learning Environments, vol. 34, no. 4, pp. 2411–2437, 2026. https://doi.org/10.1080/10494820.2025.2545955

5. W. K. Monib, A. Qazi, and R. A. Apong, “Microlearning beyond boundaries: A systematic review and a novel framework for improving learning outcomes,” Heliyon, vol. 11, no. 2, 2025.

6. M. P. Ananta, M. S. U. Qolby, and H. Miarto, “Unpacking micro-learning effectiveness: An integrative systematic review of design-oriented dimensions,” Galaxy: Jurnal Pendidikan MIPA dan Teknologi, vol. 3, no. 1, pp. 1–8, 2026.

7. R. P. D. Redondo, A. Ktena, N. Kunicina, A. Zabasta, A. Patlins, and D. E. Mele, “Advanced practices: Micro learning, practice oriented teaching and gamified learning,” in 2020 IEEE 61st International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), 2020, pp. 1–7. https://doi.org/10.1109/RTUCON51174.2020.9316555

8. D. Salleh, M. Ibrahim, and N. Khairudin, “Micro learning: A creative technological move to boost study interest,” in The 2nd International Recent Trends in Engineering, Advanced Computing and Technology Conference (RETREAT 2021), AIP Conference Proceedings, vol. 2608, no. 1, p. 020056, 2023. https://doi.org/10.1063/5.0128602

9. B. Göschlberger, F. Dopler, and G. Kotsis, “Social micro-learning and student performance,” in 2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA), 2022, pp. 184–189. https://doi.org/10.1109/ICETA57911.2022.9974766.

10. A. Samant, “Social contributory micro-learning activities motivate learners to pursue higher order learning outcomes,” in Proceedings of the International Conference on Best Innovative Teaching Strategies (ICON-BITS 2021), 2022.

11. S. L. Wamba-Taguimdje and P. K. Bashengezi, “From FoMO to learning: How social media characteristics drive explorative and exploitative use and sustainable social relationships in micro-learning activities,” Computers in Human Behavior, p. 108993, 2026.

12. B. Costache, “From TikTok attention spans to virtual campuses: How AI, microlearning, and emotional intelligence are reshaping education,” International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society, vol. 7, pp. 79–98, 2026. https://doi.org/10.65222/VIRAL.2026.4.27.47

13. M.-A. Matei, A. R. Mihaila, and M.-I. Vulpe, “Public administration and life-long learning: Rethinking skills development for the digital state,” International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society, vol. 5, no. 1, pp. 153–163, 2026.

14. A. Suvandy, P. Chatwattana, and P. Nilsook, “Development of digital literacy and digital empathy with micro-learning via activities on Metaverse,” Higher Education Studies, vol. 14, no. 2, pp. 79–87, 2024.

15. M. A. Bulut, T. Adıgüzel, and M. H. Kaya, “Exploring views and experiences of faculty members’ participation in an asynchronous online program: Using a micro-learning format and CoP framework,” Innovations in Education and Teaching International, vol. 63, no. 2, pp. 649–665, 2026. https://doi.org/10.1080/14703297.2025.2532056

16. C. Petcu and B. Costache, “Functional fixedness and organizational inertia: A microfoundational perspective on leadership failure,” International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society, vol. 5, no. 1, pp. 122–129, 2026. https://doi.org/10.65222/VIRAL.2026.2.14.34

17. T. D. Nguyen, T. Q. Le, G. T. Luong, D. T. Nguyen, and T. T. Nguyen, “A review of applying game-based learning and learning motivation: Game-based learning and learning motivation,” International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society, vol. 3, no. 3, pp. 67–74, 2025. https://doi.org/10.65222/VIRAL.2025.12.20

18. A. Kostas, G. Koutromanos, and D. Tsoumani, “Micro-learning in formal and informal education: A systematic review,” in Optimizing Education Through Micro-Lessons: Engaging and Adaptive Learning Strategies, pp. 1–19, 2024. https://doi.org/10.4018/979-8-3693-0195-1.ch001

19. B. Costache, “Rethinking the training of teaching staff through the development of internship and mentoring programs,” in ICERI2024 Proceedings, pp. 5846–5852, IATED, 2024. https://doi.org/10.21125/iceri.2024.1419

20. Costache, B. (2026). Educational Leadership in the Era of Emerging AI Adoption: An Exploratory Study of Human - AI Collaboration in Higher Education. International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society, 10, 169-191. https://doi.org/10.65222/VIRAL.2026.7.44.64

Downloads

Published

2026-08-31

How to Cite

Bǎrbulescu, R., & Enǎchescu, V. A. (2026). MICRO-LEARNING ACTIVITIES TO SUPPORT COGNITIVE TRANSFER IN HIGH-LOAD LEARNING CONDITIONS. International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society, 11, 77-88. https://doi.org/10.65222/VIRAL.2026.8.49.69

Most read articles by the same author(s)

<< < 1 2 3 > >> 
Published by VIRAL A* A

Welcome to VIRAL A* Journal

This is a professional academic journal header template with modern design and functionality. The interface is fully responsive and optimized for all devices.

Submit your cutting-edge research in AI, machine learning, and intelligent systems.

Explore our collection of peer-reviewed articles and research papers.

Read the latest articles from our current journal issue.