Conceptual model for preparing students of technical specialties to use machine learning technologies
DOI:
https://doi.org/10.52754/16948610_2026_1_10Keywords:
machine learning, artificial intelligence, technical specialties, conceptual model, educational technologiesAbstract
Relevance. This article presents a conceptual model for preparing students of technical specialties to apply machine learning technologies in professional activities. The model is based on a synthesis of systemic, competency-based, and activity-based approaches and includes target, content, procedural, and result-evaluative components. The target component defines the strategic direction, while the content component integrates four modules (theoretical foundations, data processing, algorithm implementation, professional application). The procedural component combines interactive lectures, laboratory work, and project-based activities. The result-evaluative component establishes a multi-level assessment system incorporating cognitive, practical, and reflective criteria. A pilot experiment conducted at the Department of Information Systems and Programming of Osh State University with students of specialty 710100 «Computer Science and Engineering» within the «Programming» course (56 students) confirmed the model's effectiveness. Experimental group students significantly improved their theoretical knowledge (82.4%), practical skills (85.7%), and motivation (89%).
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