THE ROLE AND IMPORTANCE OF AI-BASED MICRO-LEARNING EDUCATIONAL TECHNOLOGY IN REDUCING COGNITIVE LOAD IN PEDAGOGICAL ACTIVITIES
This article analytically describes the issue of cognitive load (intellectual and emotional overload) arising in the professional activities of
educators in the modern educational system, as well as methods for its optimization. Particular emphasis is placed on the integrated
capabilities of Artificial Intelligence (AI) technologies and the concept of micro-learning. The effectiveness of AI-based platforms in
eliminating factors such as teacher burnout syndrome, information overload, and time constraints is scientifically substantiated. The results
of the study show that the synergistic effectiveness of AI and micro-learning plays a crucial role in reducing lesson preparation time for
educators, enhancing methodical flexibility, and guaranteeing educational quality.
1. Adashboyev Sh. Pedagog kadrlarning raqamli kompetentligini baholash usullari va vositalari // Belorus-Oʻzbek ilmiy-metodik jurnali. –
Toshkent: 2023. – № 6. – B. 135-140 (13.00.00 №57)
2. Begimqulov H.Sh. Pedagog kadrlarning malaka oshirish jarayonida raqamli texnologiyalardan foydalanish muammolari // Fizika,
Matematika va Informatika Ilmiy-nazariy va metodik jurnal. – Toshkent, 2022. – № 3. – B. 194- 201
3. Adashboyev Sh. Pedagog kadrlarning raqamli kompetentligini baholash usullari va vositalari // Belorus-Oʻzbek ilmiy-metodik jurnali.
Toshkent: 2023. № 6. – B. 135-140 (13.00.00 №57)
4. Abduqodirov A.A. Taʼlim muassasalari professor-oʻqituvchilarining masofali malakalarini oshirish. // “Oʻzbekiston oliy taʼlim tizimida
kadrlar resurslarini boshqarish va rivojlantirish” mavzusidagi respublika ilmiy-amaliy anjuman materiallari. – Toshkent, 2014.
5. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285.
6. Mayer, R. E. (2009). Multimedia Learning, Cambridge University Press.
7. Hug, T. (2007). Didantics of Microlearning: Concepts, Discourses and Examples. Waxmann Verlag.
8. Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.).
9. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An argument for AI in Education. Pearson.
10. Clark, R. C., & Mayer, R. E. (2016). E-learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of
Multimedia Learning.
11. Taylor, J. C. (1995). Distance education technologies: The fourth generation. Australian Journal of Educational Technology, 11(2), 1-7.
12. Bates, A. W. (2005). Technology, e-learning and distance education. Routledge.
13. Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380-1400.
Copyright (c) 2026 «ACTA NUUz»

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.




.jpg)

1.png)




