Research On The Individualized Learning Path Of Junior High School English Based On The Knowledge Graph

With the rapid development of society,in the education industry,the needs of teachers and students for personalized learning are increasing,and the educational concept of "teaching students according to their aptitude" has been repeatedly mentioned.At the same time,with the rapid development of computer technology,the computer technology that we have now provides a new way for the realization of personalized learning.In the past traditional teaching methods,due to limited time and energy,teachers could not provide different teaching methods for different students in the teaching process.They could only conduct teaching activities according to the average situation of students in the class,and could not take into account the individual needs of students.The introduction of personalized education into teaching can not only improve the work efficiency of teachers,but also improve the learning interest of students.In the past,in order to achieve personalized education,a large number of educational technology researchers turned their attention to the development of online learning platforms.It has to be said that these online learning platforms have,to a certain extent,addressed the needs of personalized learning for teachers and students.There are still some problems in the learning platform,which can not provide students with deep-level personalized services.These learning platforms roughly divide students into several levels,provide personalized services for students at different levels,and do not segment students.Based on these shortcomings of online learning platforms,this article takes junior high school English as an example,and studies the generation of personalized learning paths based on knowledge maps,in order to provide students with deep-level personalized services.The main work of this article is as follows:1.Evaluate the difficulty of the exercise.This article analyzes exercises on the Internet that are difficult or difficult to distinguish,summarizes the difficulty evaluation methods from three aspects:super-vocabulary,examining the number of knowledge points,and similarity of options,and quantifies the evaluation results.Difficulty value of the exercise,and then apply the difficulty value of the exercise to the generation of personalized learning paths,making the personalized learning path more reasonable.2.Provide more accurate and personalized services to students by generating personalized junior high school English knowledge maps for different students.This article provides students with the current situation by providing exercises,marking some nodes in the junior high school English knowledge map according to the students' problem situations,and then using a graph convolution neural network to classify all nodes in the junior high school English knowledge map.Generate personalized knowledge graphs.3.Generate personalized learning paths.After the personalized junior middle school English knowledge map is established,the personalized learning path is generated according to the students' current problem-solving situation and the difficulty level of the exercises,and then the personalized learning path is continuously modified according to the changes in the learning situation of the students.