A domain knowledge modeling and knowledge level estimation method in an adaptive learning system

Abstract

The invention discloses a domain knowledge modeling and knowledge level estimation method in an adaptive learning system, and particularly relates to the field of adaptive learning. The problem that class education services in the existing education field are difficult to meet personalized education requirements is solved. The method specifically comprises two aspects of domain knowledge modelingbased on a knowledge graph and knowledge level estimation based on a deep learning technology. The domain knowledge modeling based on the knowledge graph comprises the steps of determining a subject knowledge graph framework; Collecting digital teaching resources, analyzing structural characteristics and language characteristics of texts of the digital teaching resources, and constructing an education corpus used for extracting subject knowledge graphs, wherein the education corpus comprises four corpora of word segmentation and part-of-speech tagging, syntactic analysis, named entities and entity relations; Subject knowledge graph construction. Knowledge level estimation based on a deep learning technology comprises the steps of domain data preprocessing and vectorization, automatic extraction of domain features by adopting a CNN, feature vector dimension reduction, and deep knowledge tracking based on an LSTM model.

Description

technical field [0001] The invention relates to the field of adaptive learning, in particular to a domain knowledge modeling and knowledge level estimation method in an adaptive learning system. Background technique [0002] Confucius, a great thinker and educator in ancient my country, put forward the educational idea of ​​"teaching students according to their aptitude" in BC. Howard Gardner, a professor of psychology at Harvard University in the United States, also repeatedly emphasized that school education reform must pay attention to "individual differences among students." However, in traditional teaching, due to the large number of students in the class, it is difficult for teachers to "teach students in accordance with their aptitude" based on their individual abilities. Practice has shown that under the traditional large-scale and assembly-line teaching mode, teachers are the imparters of knowledge, and students are the objects of knowledge indoctrination. Students'...

AI Technical Summary

Problems solved by technology

However, in traditional teaching, due to the large number of students in the class, it is difficult for teachers to "teach students in accordance with their aptitude" based on their individual abilities.

Practice has shown that under the traditional large-scale and assembly-line teaching mode, teachers are the imparters of knowledge, and students are the objects of knowledge indoctrination. Students' learning initiative and creativity are greatly restricted, which is not conducive to cultivating personalized , innovative talents

Images