KGBL: A Study on the Design of a Knowledge Graph-based Blended Learning Framework

Le résumé fourni par la source

Blended learning has emerged as a significant trend in global higher education due to its flexible and personalized characteristics. From the literature, it can be observed that almost every case of blended teaching practice presents a blended teaching design model. This indicates a lack of a universal framework for blended learning. Additionally, the emergence of the Knowledge Graph has introduced new challenges to traditional blended learning scenarios. Faced with these challenges, this study aims to utilize knowledge graphs to develop a generic framework for blended learning through a literature research approach. A review of the literature revealed that knowledge graphs in the field of education are micro-classes with learning resources. Based on this, a general process for constructing knowledge graphs was proposed with the use of MOOC platform. The constructed knowledge graph serves as the foundation for the Knowledge Graph Blended Learning framework. The online component implements an adaptive learning cycle based on the knowledge graph, while the offline component facilitates students' deep learning. In future related research, the Knowledge Graph Blended Learning framework can be used to guide the practice of blended learning and further expand and deepen it in terms of personalized and accurate teaching decision-making and whole-process enhancement of process evaluation.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.