Enhancing Students’ Self-Regulation and Autonomous Learning in Higher Education through Interactive Mobile Technologies

Abstract

With the rapid advancement of information technology, the application of interactive mobile technologies in higher education has garnered increasing attention, particularly for their potential in enhancing students’ self-regulation and autonomous learning capabilities. Traditional instructional models often rely on fixed classroom settings and predetermined teaching schedules, making it difficult to adapt to individual differences and diverse learning needs. In contrast, interactive mobile technologies offer personalized learning resources and real-time feedback, thereby improving the flexibility and efficiency of self-directed learning. As a result, exploring how to leverage these technologies to foster students’ self-regulation and autonomy has become a critical issue in the field of educational technology. Existing studies primarily focus on the cultivation of autonomous learning and self-regulation, as well as the design of personalized learning path recommendation systems. However, many of these systems are based on static data and fail to adapt in real time to the dynamic changes in students’ learning behaviors, limiting their practical effectiveness in educational settings. Therefore, a pressing challenge is to develop a system that can dynamically adjust learning paths in response to changes in student behavior and learning needs. This study proposes a dynamic personalized learning path recommendation model based on latent association information and dynamic graph neural networks. By conducting real-time analysis of student learning behaviors and continuously updating the model, the system aims to construct more intelligent and individualized learning paths. This, in turn, enhances students’ self-regulation and autonomous learning abilities. The findings provide new technological support for teaching practices in higher education and offer theoretical and methodological contributions to the advancement of personalized education.