Research on the Positive Empowerment of AI Virtual Humans on the Mental Health of Primary and Secondary School Students Under the Double Reduction Policy
- DOI
- 10.2991/978-2-38476-593-5_52How to use a DOI?
- Keywords
- Double Reduction Policy; virtual humans; primary and secondary school students; mental health; AI
- Abstract
Since the implementation of the Double Reduction Policy, students’ academic burden has been reduced, but mental health problems have become younger, more complex and concealed. Mental health education faces insufficient resources, weak personalized supply and poor school-family-society cooperation. Based on psychological theories and TAM, this paper analyzes students’ mental health needs, explores virtual humans’ positive effects on emotion, self-identity, communication and stress management, and assesses their application. Results show that virtual humans, with standardized, precise and inclusive advantages, can make up for traditional education shortages and provide a new digital path for mental health education.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Chenyu Liu AU - Lingjia Zhang AU - Ailing Long AU - Yuqi Zhang AU - Guoqiang Tang AU - Yimeng Lai PY - 2026 DA - 2026/06/30 TI - Research on the Positive Empowerment of AI Virtual Humans on the Mental Health of Primary and Secondary School Students Under the Double Reduction Policy BT - Proceedings of the 2026 5th International Conference on Humanities, Wisdom Education and Service Management (HWESM 2026) PB - Atlantis Press SP - 478 EP - 485 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-593-5_52 DO - 10.2991/978-2-38476-593-5_52 ID - Liu2026 ER -