Influence of Artificial Intelligence in Education on Adolescents' Social Adaptability: A Machine Learning Study.

Journal: International journal of environmental research and public health
PMID:

Abstract

This study aimed to investigate the influence of artificial intelligence in education (AIEd) on adolescents' social adaptability, as well as to identify the relevant psychosocial factors that can predict adolescents' social adaptability. A total of 1328 participants (mean = , SD = ) completed the survey. A machine-learning algorithm was used to find out whether AIEd may influence adolescents' social adaptability as well as the relevant psychosocial variables, such as teacher-student relations, peer relations, interparental relations, and loneliness that may be significantly related to social adaptability. Results showed that it has a positive influence of AIEd on adolescents' social adaptability. In addition, the four most important factors in the prediction of social adaptability among group students are interpersonal relationships, peer relations, academic emotion, and loneliness. A high level of interpersonal relationships and peer relations can predict a high level of social adaptability among the AI group students, while a high level of academic emotion and loneliness can predict a low level of social adaptability. Overall, the findings highlight the need to focus interventions according to the relation between these psychosocial factors and social adaptability in order to increase the positive influence of AIEd and promote the development of social adaptability.

Authors

  • Chuyin Xie
    School of Education, Guangzhou University, Guangzhou 510006, China.
  • Minhua Ruan
    School of Education, Guangzhou University, Guangzhou 510006, China.
  • Ping Lin
    Department of Geriatrics, The Third Hospital of Hangzhou, Hangzhou, Zhejiang, China.
  • Zheng Wang
    Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan 430060, China.
  • Tinghong Lai
    School of Education, Guangzhou University, Guangzhou 510006, China.
  • Ying Xie
    Department of Sociology, School of Public Administration, Guangzhou University, Guangzhou, 510006, China. xysoc@gzhu.edu.cn.
  • Shimin Fu
    School of Education, Guangzhou University, Guangzhou 510006, China.
  • Hong Lu