ADAPTIVE AI IN LANGUAGE LEARNING: PRINCIPLES AND ASSESSMENT CRITERIA

This article examines principles for integrating adaptive artificial intelligence into language education and proposes assessment criteria aligned with competency-based outcomes. Using comparative analysis, pedagogical modeling, and expert review, it clarifies how personalization, transparency, and feedback loops affect learning. Scientific novelty lies in a unified criteria framework connecting adaptive AI decisions to valid, reliable language-skill measurement.

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