A Study of Generative Artificial Intelligence on Mobile Learning Adoption Based on SEM Models

Abstract

With the rapid development of information technology, the application of generative artificial intelligence (GAI) in the field of education is becoming more and more extensive, especially on contemporary college students’ mobile learning, which has a profound impact. However, the attitudes of contemporary college students towards using GAI for mobile learning are characterized by complexity and diversity, so it is necessary to explore the factors affecting college students’ willingness to use GAI. In view of this, this paper conducted a questionnaire survey with 1028 college students in China and adopted the structural equation modeling (SEM) model to identify and analyze the factors affecting college students’ behavior of using GAI for mobile learning. The results show that performance expectation, effort expectation, social influence, convenience conditions, and perceived fun of GAI significantly affect college students’ willingness to use GAI, while perceived risk and perceived learning resources have no significant direct influence effect on willingness to use. Based on the empirical results, future strategies for the advancement of GAI education are proposed to further optimize the application of GAI in m-learning.