MCM-based intelligent adaptive review resource push method

Abstract

The invention discloses an intelligent adaptive review resource pushing method based on MCM, which includes obtaining the historical knowledge point wrong question data of all students; obtaining multiple wrong cause labels of the current student, and screening out the first wrong cause label belonging to the intelligence factor; For each first error label of the current student, the error importance degree value P(E) is calculated; according to the MCM label corresponding to each first error label, the MCM learning corresponding to the MCM label is extracted from the preset content management system. The resources are sorted in descending order according to the P(E) value of the error cause, and some or all of the MCM learning resources are extracted and pushed to the students according to the order. The knowledge point corresponding to the MCM label is wrong. The invention solves the problems that the review can cure the symptoms but not the root cause, and the students' learning level is difficult to really improve.

Description

technical field [0001] The invention belongs to the technical field of online education, and in particular relates to an MCM-based intelligent adaptive review resource pushing method. Background technique [0002] MCM is a strategy that separates students' model of thinking (Model of thinking), learning ability (Capacity) and learning method (Methodology) by splitting each learning thinking. [0003] The existing error-prone questions or review questions push methods for knowledge points only judge students’ weak links in knowledge points from the test results (wrong / correct) of the test questions, and do not really consider the reasons for causing wrong questions about knowledge points other than the lack of mastery In addition to the content of knowledge points, there may be deeper problems such as model of thinking, learning ability (Capacity) and learning method (Methodology), as well as other non-intellectual factors such as students' psychological factors or habit of d...

AI Technical Summary

Problems solved by technology

[0003] The existing error-prone questions or review questions push methods for knowledge points only judge students’ weak links in knowledge points from the test results (wrong / correct) of the test questions, and do not really consider the reasons for causing wrong questions about knowledge points other than the lack of mastery In addition to the content of knowledge points, there may be deeper problems such as model of thinking, learning ability (Capacity) and learning method (Methodology), as well as other non-intellectual factors such as students' psychological factors or habit of doing questions.

[0004] This results in low review efficiency, resulting in a temporary solution to the review rather than the root cause, and it is difficult for students to really improve their learning level.

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