Adaptive Learning Path Recommendation Based On Knowledge Map

As the Internet and smart phones boom,the online environment has been greatly developed and improved.In China,Online education services not only are the fastest growing areas of educational informationization,but also has set off a wave of learning for all people.Professional users can choose courses and study at any time and place.At the same time,higher education also takes the quality courses issued by major universities as auxiliary courses to help learners broaden their knowledge.Learners can arbitrarily choose the course resources of interest for sequential learning,so as to consolidate the basic knowledge and further research.However,because the various courses lack index and association,learners face a large amount of learning resources,it takes a lot of time to choose suitable and high-quality courses.Moreover,these resources even cause cognitive overload,lost and other issues.How to effectively help learners to accurately locate high-quality and suitable curriculum resources is the main problem studied in this paper.This paper proposes a new method of personalized curriculum resource recommendation.Based on the Educoder online training platform,the knowledge points and their relationships in each section are extracted from training course published in the platform,thus generating the platform-specific knowledge map.First of all,the PageRank algorithm is used to calculate the initial weight of the knowledge points according to the knowledge map.Then,the behavior data of the user’s online learning,such as the learner’s click data,the history course information,and the evaluation data in the programming,are statistically analyzed.The personal knowledge map and knowledge weight are updated with the number of error evaluations,and the new weighted Top3 knowledge points are presented to the user as recommended results.Finally,the Dijkstra algorithm is used to recommend the shortest path between courses to users,thus helping users to learn the course accurately and efficiently.The research in this paper finds that the existing personalized curriculum resource system recommendation ignores the connection between knowledge points and cannot meet the individual needs of learners.The curriculum knowledge map construction proposed in this paper demonstrates the connection between knowledge points and constructs a complete knowledge system,which vividly and succinctly depicts the important knowledge points in the curriculum.At the same time,the courses recommended according to the learner’s personal behavior data are more targeted,greatly improving the efficiency and satisfaction of the learners in the learning process.