Self-adaptation teaching interaction system and method

Abstract

The invention discloses a self-adaptation teaching interaction system and method. The self-adaptation teaching interaction system comprises a question questioning and answering module, a study track recording module connected with the question questioning and answering module, a knowledge graph drawing recording module connected with the study track recording module, a question characteristic value matrix mark recording module connected with the question questioning and answering module and the study track recording module, a visualization report generation module connected with the knowledge graph drawing recording module and a study plan generation module connected with the knowledge graph drawing recording module. The method includes the following steps: the question questioning and answering module is used for answering questions, study conditions of students are transmitted to the study track recording module to be recorded, a knowledge graph is formed, questions with appropriate characteristic values are selected, the knowledge graphs are updated, and the questions are optimized. By means of the self-adaptation teaching interaction system and method, valuable screening is carried out according to the characteristic values, the specific questions suitable for exercising the different students are recommended to the different students, and therefore academic records of the students are rapidly improved.

Description

technical field [0001] The invention relates to a learning system, in particular to an adaptive teaching interaction system and method, and belongs to the technical field of learning products. Background technique [0002] At present, there are a large number of topics for students to practice on the Internet for their learning tasks; however, each student has different knowledge and cannot quickly and accurately find the topics they should study; Students are positioned at a certain level, and then on this level, use templates to match questions, and will not comprehensively screen the knowledge points that students really need to master based on the actual situation of students; at the same time, the current selection of templates for matching questions has relatively Fixed, it will not dynamically adjust the characteristic values ​​of each dimension of the question according to the student's answering situation; it is all based on the template to generate questions, selec...

AI Technical Summary

Problems solved by technology

[0002] At present, there are a large number of topics for students to practice on the Internet for their learning tasks; however, each student has different knowledge and cannot quickly and accurately find the topics they should study; Students are positioned at a certain level, and then on this level, use templates to match questions, and will not comprehensively screen the knowledge points that students really need to master based on the actual situation of students; at the same time, the current selection of templates for matching questions has relatively Fixed, it will not dynamically adjust the characteristic values ​​of each dimension of the question according to the student's answering situation; it is all based on the template to generate questions, select a template, and the system will randomly select some questions from several types of questions to form The questions given by the template; the questions given in this way are relatively fixed and rely heavily on the artificial classification of the questions; the evaluation of students is to use limited questions to evaluate students at a certain point in time, and give the knowledge of the student union knowledge points and knowledge points that they do not know; this method is relatively one-sided for the evaluation of students, and can only be analyzed for relatively limited knowledge points

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