SyncRec: A Synchronized Online Learning Recommendation System

With the rapid development of digitalization and big data technology, numerous online learning materials have become available for self-regulated online learning. However, there is still a lack of a practical recommendation platform that can achieve synchronization between massive online learning materials and multiple users at different stages. To fill the gaps, we present a synchronized online learning recommendation system (SyncRec). The multi-source heterogeneous information fusion module integrates online learning materials from different digital platforms. The dynamic knowledge status tracing module tracks the real-time knowledge status and learning progress of online learners via dynamic mapping to a set of knowledge trees. Furthermore, the personalized recommendation module achieves adaptive recommendation of digital learning materials for each self-regulated online learner based on current knowledge status and learning needs as well as preferences. The demonstrated system helps improve learning outcomes and user experiences. An illustration video could be found here ( https://github.com/Edith-xuan/video/blob/main/demo.mp4 ).