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The study analyzes the impact of artificial intelligence on the assessment system in IT education, identifies its potential and risks, and provides recommendations for modernizing evaluation practices. Key areas of transformation have been specified: automation of code verification and personalization of learning through the generation of diagnostic materials; analysis of Git history and code; a methodology for documenting interaction with artificial intelligence in course and final qualification works. A hybrid knowledge assessment model has been proposed and tested.
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N. Yu. Dobrovolskaia (2026) studied this question.
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