Learning Path Planning Based On The Knowledge Graph On The MOOC Platform

As a new educational model,MOOC constantly impacts the traditional concepts and plays an important role in modern education.With the continuous development of the MOOC platform,the massive educational resources on the platform provide important support for learners' self-learning and life-long learning.However,there are still problems such as the fuzzy relationship between educational resources,the knowledge structure of educational resources that is not closer to the actual situation,the lack of learning feedback,and so on.These problems can't provide correct guidance for learners' online learning.The knowledge base and learning goals of each learner are different.They need a professional and scientific learning path that meets their individual needs to achieve their personalized learning goals.Therefore,the learning path planning based on knowledge graph on MOOC platform has become an important research topicThe study of learning path planning based on knowledge graph on the MOOC platform is divided into the learning path planning between courses and the learning path planning within the coursesThe research plans the learning path between courses by drawing a knowledge graph for the MOOC platform course.The planning of the learning path between courses focuses on the "prerequisite course" relationship between the courses in the knowledge graph.Based on this,the course planning sequence is planned scientifically The RippleNet algorithm is introduced when planning the learning path between courses,making the planned learning path more diversifiedThe learning path planning in the course is divided into three steps:First,build a knowledge graph of curriculum knowledge points based on the dependencies between knowledge points in relevant course materials and expert experience.Then plan the learning path for the learners by linking the knowledge graph of curriculum knowledge points with the learning resources on the edX platform.Finally,the learning path is updated based on the answers to the exercises marked with knowledge pointsThe research explores the open edX architecture and extension methods,analyzes the important components of the edX platform and how to configure PyCharm to develop the edX platform.Extends the edX platform by adding XBlocksResearch the knowledge graph technology,design a knowledge graph model through a hybrid method combining expert and reference method,and select Neo4j to store the knowledge graph;Research the visualization technology,discuss the visualization tools of Neo4j Select Echarts as a tool to find and display knowledge points on the edX platform visually,and give feedback and learning path to learners based on their learning situation.When designing the learning path through a designed knowledge graph,the RippleNet algorithm is introduced into the learning path between courses to enrich the diversity of courses.Provide professional learning path planning for learners and improve their learning efficiency of online learning.