Online education-oriented learner abnormal learning state prediction method

A technology of abnormal learning and prediction method, which is applied in the field of abnormal learning state prediction of learners for online education, which can solve the problems of lack, a large number of manual labeling costs, and less interaction between teachers and students, and achieve the effect of reducing the impact.
CN114881331APending Publication Date: 2022-08-09XI AN JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
XI AN JIAOTONG UNIV
Publication Date
2022-08-09

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Abstract

The invention discloses an online education-oriented learner abnormal learning state prediction method. The method comprises the steps of preprocessing high-dimensional online education platform log information and learner registration information, and coding and constructing learner portrait features based on a self-supervised learning method; constructing state features of the learner, further constructing a state feature sequence based on a generation time sequence of the state features, and constructing a state feature graph based on cosine similarity among the state features; constructing a long-short term memory-graph attention deep network conforming to learning badness degree prediction of online education, and determining the number of layers of the network, the number of neurons of each layer and the dimensions of input and output; constructing a pseudo tag based on the noise tag to perform iterative training on the network; and predicting the abnormal learning state and degree of the learner in the to-be-predicted learning stage by using the trained network. According to the method, the state abnormity degree of the learner is predicted by using the learner registration information and the learner log information, and a reference is provided for a teacher to carry out targeted guidance and help on the learner.
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Description

technical field

[0001] The invention relates to the technical field of online education, in particular to an online education-oriented method for predicting abnormal learning states of learners. Background technique

[0002] With the widespread popularity of modern computer networks and the rapid development of home electronic equipment terminals, online education using modern technologies such as computer networks and artificial intelligence has become an important part of family education. In 2020, the market size of the online education industry will increase by 35.5% year-on-year. However, as a means of distance education, the characteristics of online education with less interaction between teachers and students and difficult learning supervision have caused a negative impact on the teaching effect that cannot be ignored. In recent years, the number of online education participants and online courses have increased year by year, and a large amount of online education le...

Claims

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