Russian Federation
The article proposes a model for assessing a reader’s digital footprint in a gamified educational environment. The framework integrates active and passive data and includes performance, behavioral, and psycho-emotional indicators to construct a dynamic learner profile and enable adaptive personalization. Methodological limitations, algorithmic bias, and ethical considerations are discussed. The study emphasizes the need for empirical validation and explainable models.
digital footprint, adaptive learning, learning analytics, gamification, personalization, algorithmic bias
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