Method for constructing hierarchical learning space

Abstract

The invention discloses a method for constructing a hierarchical learning space, which comprises the following steps of: classifying subject skills, and identifying parallel or inclusion relations among the skills; Layering correspondingly according to different types, and calling a'plane learning space generation function 'to generate learning spaces of a plurality of planes one by one from the first layer according to the micro-skill relationship layer by layer; And calling the function combination of the'combined plane learning space component layer multi-dimensional learning space 'to generate a multi-dimensional layered stereo learning space. According to the method for constructing the hierarchical learning space provided by the invention, knowledge points related to subjects are constructed to form a learning space, and progressive learning is realized according to different mastery degrees of the knowledge points. And the mastered knowledge points can be objectively evaluated,the mastering degree of the knowledge points is known, and targeted learning is realized.

Description

technical field [0001] The invention relates to a method for formulating a learning plan, in particular to a method for constructing knowledge points involved in a subject (such as mathematics) to form a learning space, and realizing gradual and targeted learning according to different mastery levels of the knowledge points. Background technique [0002] KS-CAT is a computerized adaptive test based on learning space theory. The learning space first analyzes the knowledge in a field into a set of questions, each question has a correct answer, and secondly uses a set of questions that a student can answer correctly in the field under ideal conditions to present his "knowledge status" , the collection of all possible (according to subject logic, determined by experts) knowledge states is called learning space. The computerized adaptive test (CAT) is proposed to solve the shortcomings of the "peak shape" and "rectangular" paper-and-pencil tests that all students use the same to...

AI Technical Summary

Problems solved by technology

[0004] However, QUERY has a very big problem in practical application. On the one hand, a learning space with four or five hundred knowledge points is very common, but when QUERY has 50 knowledge points, it needs to ask experts more times. tens of thousands, so it cannot be used for large-scale learning space generation; on the other hand, the lea

Images