Personalized Learning Path Recommendation based on Knowledge Graph

Abstract

Due to the arrival of educational information age, the amounts of learning activities and digital learning resources in online education are growing rapidly accompanying with the produce of the big data in education. The paper explores the technology to find the personalized learning path based on the educational big data. It proposes to utilize the knowledge graph to make semantic integration of educational data from various online learning environments. The knowledge representation of the learning activities and resources are generated based on the dynamic harvested data. The individual leaning needs are derived from the representation and the personalized learning path is identified based on the articulated leaning needs. The identification method includes capturing the learner’s evolving knowledge status and learning activities from various learning environments. It recommends the learning path which more precisely matches the learning goals and promotes intentional learning.