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February 8, 2026Scientific ReportsOpen Access

A deep learning approach to emotionally intelligent AI for improved learning outcomes

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Authors

XWXiaoyu WuZhengzhou University of Light IndustryTLTienTien LeeSultan Idris Education UniversityULUmesh Kumar LilhoreGalgotias University

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Implication

Demonstrates improved learning outcomes through an emotion-aware AI framework for learners, suggesting its potential impact on educational systems.

Key Points

  • The research aims to integrate emotional intelligence into AI educational systems to enhance learner engagement and outcomes.
  • Proposed a multimodal deep learning framework that utilizes facial expressions, speech characteristics, and textual responses.
  • Analyzed emotional states through a graph-based fusion mechanism.
  • Evaluated the framework using benchmark datasets like AffectNet and IEMOCAP to assess emotion recognition and support adaptive feedback.
  • Experimental results indicate substantial improvements in learner engagement and emotional regulation.
  • The framework achieved high emotion recognition performance, especially for positive and neutral states.
  • User study findings suggest that learners found the system supportive and responsive due to its emotional adaptability.

Cite This Study

Wu et al. (2026) studied this question.

synapsesocial.com/papers/698828990fc35cd7a8848417https://doi.org/10.1038/s41598-026-37750-1
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