Adaptive learning path recommendation method based on knowledge graph

Abstract

The invention discloses an adaptive learning path recommendation method based on a knowledge graph. The adaptive learning path recommendation method is specifically implemented according to the following steps: step 1, constructing the knowledge graph of a corresponding field; step 2, establishing a learner model, wherein the learner model comprises basic information, cognitive level, learning style and learning ability of a learner; 3, performing system expansion on the knowledge graph established in the step 1, and adding node centrality and probability distribution; and step 4, positioning in the expanded knowledge graph according to the cognitive level of the learner in the learner model, and recommending corresponding knowledge points to the learner. According to the adaptive learning path recommendation method based on the knowledge graph, the learning ability of the learner is quantified, and the learning path can be recommended to the learner in combination with the cognitive level of the learner.

Description

technical field [0001] The invention belongs to the technical field of computer education methods, and relates to a knowledge map-based adaptive learning path recommendation method. Background technique [0002] Educational informatization is the basic technical approach for building a learning society and a lifelong learning system in the information age. my country's education informatization has gone through the stages of digitization and networking. With the rapid development of mobile Internet, cloud computing, big data, artificial intelligence and other technologies, education informatization has entered the stage of intelligence, showing a new, personalized, collaborative and adaptive trend. In 2018, the implementation of the "Education Informatization 2.0 Action Plan" formulated by the Ministry of Education proposed intelligent education, and realized refined teaching management, adaptive teaching resources, and differentiated teaching in the "platform + education" ...

AI Technical Summary

Problems solved by technology

At this stage, researchers mainly divide learner modeling into cognitive level and learning style. Although the model can reflect the learner's learning effect to a certain extent, it does not reflect the learner's learning ability and learning ability in the learning process. It is the basic ability for students to transform and use knowledge, so learning ability is of great significance in the study of learners

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