Design of a Mobile Interactive Distance Education Platform with Student Engagement Assessment

Abstract

The continuity of interaction and the reliability of learning analytics in mobile distance education are substantially constrained by dynamically fluctuating network conditions and the challenges associated with heterogeneous device adaptation. Existing educational systems are often limited by inadequate transmission stability under weak-network environments, privacy risks arising from cloud-centric learning analytics, and inefficient synchronization across multiple terminal devices. To address these limitations, a hierarchical end–edge–cloud microservice architecture for distance education was proposed. An adaptive transmission degradation mechanism based on a dual-protocol stack and integrated bandwidth time-series prediction was developed. In addition, a lightweight on-device engagement assessment model was established using multidimensional implicit interaction features, while a collaborative whiteboard synchronization algorithm optimized for heterogeneous mobile devices was designed. The proposed framework effectively addresses the challenges of dynamic adaptation and real-time learning-state perception in mobile learning environments. Technical support is thereby provided for the development of high-performance, privacy-preserving intelligent mobile education systems.