Driving the Integration of Mobile Learning and Blended Learning Models in Higher Education

Abstract

With the rapid advancement of information technology, particularly the widespread adoption of mobile internet, the integration of mobile learning and blended learning models in higher education has emerged as a significant innovation in educational practice. Vocational education, as an educational model that emphasizes practical skills and applied abilities, faces challenges in effectively combining these two approaches. The pervasive use of mobile devices enables learners to engage in learning at any time and location, yet it raises critical issues related to the construction of efficient interactive learning networks and the enhancement of learning outcomes. Consequently, study on “mobile device-to-mobile device” offline blended learning interaction networks has gained prominence. These networks not only prioritize interaction and collaboration among learners but also aim to provide personalized and precise learning support in multidimensional and dynamic learning environments. While existing studies have yielded insights into the integration of mobile learning and blended learning, as well as the design of learning interaction networks, they often lack in-depth exploration of complex learning interaction models and dynamic data relationships. Additionally, traditional learning network models frequently suffer from limited adaptability and insufficient accuracy in practical applications. In particular, as for the construction and optimization of “mobile device-to-mobile device” offline learning interaction networks, robust theoretical frameworks and practical solutions are lacking. Therefore, this study focuses on the definition and link prediction challenges of such networks. Through scientific model design and algorithmic optimization, the study seeks to enhance interaction efficiency and personalized support within learning networks, thereby advancing innovation and development in educational models.