Intelligent Interaction Platform for Personalized Digital Tutor: Advancing Empathetic and Adaptive Learning Experiences
The rapid advancement of artificial intelligence and virtual digital human technologies is ushering in transformative changes in education. Virtual digital humans, empowered by multimodal information fusion and natural language processing capabilities, offer a more engaging and humanized interaction experience for online learning. However, general-purpose AI models for digital teaching often face notable challenges: 1) They often lack deep understanding of users, overlooking personalized learning needs; 2) they may struggle with knowledge reasoning, leading to unreliable and outdated content; 3) their human-machine interactions can feel unnatural, lacking emotional resonance and empathetic support.
Authors
- Junyu Lu (ORCID: https://orcid.org/0009-0008-0574-9519)
- Enhong Chen (ORCID: https://orcid.org/0000-0002-4835-4102)
- Linbo Zhu (ORCID: https://orcid.org/0009-0003-6036-5095)
- Meikai Bao (ORCID: https://orcid.org/0000-0002-8628-3683)
- Kai Zhang (ORCID: https://orcid.org/0000-0001-5335-2470)
- Qi Liu (ORCID: https://orcid.org/0000-0001-6956-5550)
- Weiyin Gong
- Xukai Liu
Institutions
- University of Science and Technology of China (CN)
Publication Details
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1145/3701716.3715182
- Citations
- 1
- Primary Topic
- Intelligent Tutoring Systems and Adaptive Learning
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Anhui Province
- Fundamental Research Funds for the Central Universities