Learning path planning method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a learning path planning method and device, equipment and a storage medium. The learning path planning method comprises the steps of obtaining a knowledge point set of a to-be-planned path, learning behavior data of a to-be-planned student and mastering degree data of the to-be-planned student at each knowledge point of the knowledge point set; according to the learning behavior data and the mastering degree data of each knowledge point, obtaining at least one of a learning duration prediction vector and a learning interest prediction vector, and a mastering degree variation prediction vector; carrying out vector fusion on at least one of the learning duration prediction vector and the learning interest prediction vector and the mastering degree variable quantity prediction vector to obtain a comprehensive knowledge point evaluation vector; and sorting the knowledge points according to the size of each dimension of the comprehensive knowledge point evaluation vector to obtain a learning planning path of each knowledge point, so that the accuracy and comprehensiveness of path planning can be improved, and the learning efficiency and learning interest of students can be better improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of information technology, and in particular, to a learning path planning method, device, device and storage medium. Background technique [0002] In smart education, learning planning is the key to how to truly teach students in accordance with their aptitude. That is, for each different student, it is necessary to plan a personalized learning path that can comprehensively consider all factors of learning based on his own learning situation, learning ability and learning preferences, so as to improve students' learning efficiency and learning interest. [0003] However, a comprehensive investigation found that the existing technologies have shortcomings such as low comprehensiveness and weak model generalization ability in path planning, which lead to inaccurate planning results of learning path planning. [0004] Therefore, there are great challenges and difficulties in how to improve the ...

AI Technical Summary

Problems solved by technology

[0003] However, a comprehensive survey found that existing technologies have deficiencies such as low comprehensiveness in path planning and weak model generalization capabilities, resulting in inaccurate planning results for learning path planning

[0004] Therefore, there are great challenges and difficulties in how to improve the accuracy of learning path planning results.

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