With the rapid popularization of artificial intelligence (AI) technology in the field of education, personalized learning will become the core direction of digital transformation in education. Learning emotions directly affect learning efficiency, learning motivation, and learning outcomes. In traditional learning systems, only knowledge acquisition is focused on, lacking perception and intervention of learners' emotional states. AI technologies such as computer vision, facial expression recognition, speech emotion recognition, and behavior recognition are becoming increasingly mature, providing the possibility for real-time capture and learning of emotions. Building a personalized learning system that combines emotional perception, intelligent recommendation, and dynamic intervention is an important research gap in the current field of educational technology.
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Dengke Wang (2026) studied this question.
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