Open AccessResearch on the application of personalized teaching mode based on big data in Computer teaching
Author(s) -
Ming Cai,
Wei Wei Zhang,
Chen Xiao,
Yanan Sun,
Honglin Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032089
Subject(s) - computer science , hyperlink , web crawler , classifier (uml) , personalization , reinforcement learning , artificial intelligence , multimedia , machine learning , world wide web , web page
In order to improve the efficiency of teaching and learning, it has become an inevitable trend to explore a new teaching mode based on the analysis technology of big data in view of the disadvantages of learners’ passive acceptance of knowledge under the traditional teaching mode. For mining online learning behavior, In order to learn the optimal strategy behavior better, a new strategy based on reinforcement learning is proposed based on focused crawler. Using Bayesian classifier, hyperlinks are classified according to the whole web page text and link text, and the importance of each link is calculated, so as to determine the access order of links. Targeted mining of learner interests to predict learner preferences and make personalized guided recommendations. Through the analysis results show that, in the same experiment platform, enhance learning algorithm to get the optimal strategy for online learning behavior training, so that teaching staff can quickly and efficiently make the decision of teaching content recommendation to learners based on learning platform.