ARTIFICIAL INTELLIGENCE-BASED ADAPTIVE LEARNING AND INTELLIGENT DIAGNOSTIC TECHNOLOGIES
- Authors
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Ilbayev Shukhrat Oktamovich
Head of Cycle, Military Security and Defense University of the Republic of Uzbekistan
Author
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- Keywords:
- Adaptive learning, artificial intelligence, digital learning environment, intelligent diagnostics, Learning Analytics, Educational Data Mining, cognitive load, military pedagogy, cadet, individualized learning trajectory, ITS frameworks, stress resilience, hyper-personalization, military educational technologies.
- Abstract
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This article analyzes the theoretical and conceptual foundations, architectural design, and strategic role of artificial intelligence-based adaptive learning and intelligent diagnostic technologies within the contemporary educational ecosystem. Adaptive learning systems are characterized as intelligent pedagogical frameworks that compute a learner's distinct cognitive attributes, knowledge baseline, mastery velocity, and psychological state in real-time to automatically calibrate the instructional cycle. The paper elucidates the critical roles of Learning Analytics, Educational Data Mining, Machine Learning, and Deep Learning technologies in optimizing adaptive instruction. Furthermore, it scientifically substantiates the pedagogical and psychological capacities of intelligent diagnostic architectures, highlighting the prospective horizons of their deployment within higher education and specialized military training institutions.
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- Published
- 2026-05-24
- Issue
- Vol. 2 No. 5 (2026)
- Section
- Articles
- License
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This work is licensed under a Creative Commons Attribution 4.0 International License.
