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ARCHITECTURE OF AN OLYMPIAD PREPARATION SYSTEM BASED ON BIG DATA

Nuyakshin Mihail Gennadievich  (postgraduate Department of System Analysis and Management Dubna State University )

This article presents the architecture of an adaptive system for preparing students for mathematics Olympiads, which personalizes the educational process based on big data analysis and cognitive modeling methods. Using accumulated learning data for each student, the system dynamically adapts educational content by applying machine learning methods (clustering and classification) to segment students and select optimal learning trajectories. The integration of AI for solution verification, including NLP algorithms and the cognitive architecture ACT-R, enables personalized feedback. The article also explores the possibility of integrating this system with external educational platforms.

Keywords:adaptive learning, cognitive models, ACT-R, machine learning, personalized learning process, data analysis in education, feedback, class diagram.
 

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Citation link:
Nuyakshin M. G. ARCHITECTURE OF AN OLYMPIAD PREPARATION SYSTEM BASED ON BIG DATA // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2024. -№11. -С. 108-113 DOI 10.37882/2223-2966.2024.11.23
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