GENESIS OF ADAPTIVE SYSTEMS AND PERSONALIZED TEACHING STRATEGIES IN EDUCATION
- Authors
-
-
Eshpulatov Inoyat Saparovich
PhD in Philosophical Sciences, Senior Lecturer, Military Security and Defense of University of the Republic of Uzbekistan
Author
-
- Keywords:
- Adaptive learning, personalized teaching, genesis, programmed instruction, artificial intelligence, Intelligent Tutoring Systems (ITS), Learner Model, Cognitive Load Theory, Educational Data Mining.
- Abstract
-
This article analyzes the origins (genesis), developmental stages, and conceptual foundations of adaptive learning systems (Adaptive Learning) and personalized teaching strategies, which are among the most relevant directions of contemporary digital education. The study scientifically examines the evolution from behaviorist programmed instruction to modern models based on artificial intelligence and Educational Data Mining. In addition, the fundamental components of adaptive learning architecture—namely the Expert Model, Learner Model, and Adaptation Model—are analyzed, and their pedagogical significance in enhancing learning effectiveness is substantiated.
- References
-
1.O‘zbekiston Respublikasining “Ta’lim to‘g‘risida”gi Qonuni. – Toshkent: O‘zbekiston, 2020. – 74 b.
2.Robert, I. V. Sovremennie informatsionnie texnologii v obrazovanii: didakticheskie problemi; perspektivi ispolzovaniya / I. V. Robert. – Moskva: Shkola-Press, 2014. – 205 s.
3.Sweller, J. Cognitive Load Theory / J. Sweller, J. J. G. van Merriënboer, F. Paas. – New York: Routledge, 2019. – 284 p.
4.Miller, G. A. The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information / G. A. Miller // Psychological Review. – 1956. – Vol. 63, No. 2. – P. 81–97.
5.Skinner, B. F. Teaching Machines / B. F. Skinner // Science. – 1958. – Vol. 128, No. 3330. – P. 969–977.
6.Crowder, N. A. Automatic Tutoring by Intrinsic Programming / N. A. Crowder // Teaching Machines and Programmed Learning. – Washington: National Education Association, 1960. – P. 286–298.
7.Brusilovsky, P. Adaptive Hypermedia: From Systems to Frameworks / P. Brusilovsky // Lecture Notes in Computer Science. – 2016. – Vol. 4321. – P. 24–33.
8.Siemens, G. Learning Analytics: Envisioning a Data-Driven Educational System / G. Siemens // Journal of Educational Technology & Society. – 2012. – Vol. 15, No. 3. – P. 133–145.
9.Romero, C. Educational Data Mining: A Review of the State of the Art / C. Romero, S. Ventura // IEEE Transactions on Systems, Man, and Cybernetics. – 2020. – Vol. 40, No. 6. – P. 601–618.
10.Begimkulov, U. Sh. Oliy pedagogik ta’limda zamonaviy axborot texnologiyalarini joriy etishning ilmiy-pedagogik asoslari: Ped. fan. dok. ... diss. avtoref. / U. Sh. Begimkulov. – Toshkent: TDPU, 2007. – 42 b.
11.Xalilova, Sh. S. Raqamli ta’lim muhitida talabalarning mustaqil ta’lim faoliyatini intellektual boshqarish // Zamonaviy ta’lim jurnali. – Toshkent, 2024. – № 5. – B. 38–44.
12.Advanced Distributed Learning (ADL) Initiative. Personalized Assistant for Learning (PAL) Project [Elektronniy resurs]. – URL: https://www.adlnet.gov/projects/pal/ (data obrasheniya: 12.05.2026).
13.Knewton Adaptive Learning Platform. White Paper: Open Adaptive Learning Engine [Elektronniy resurs]. – URL: https://www.knewton.com/resources/ (data obrasheniya: 18.04.2026).
- Downloads
- Published
- 2026-05-24
- Issue
- Vol. 2 No. 5 (2026)
- Section
- Articles
- License
-
This work is licensed under a Creative Commons Attribution 4.0 International License.
