Design and Implementation of Online Teaching System under the Background of Big Data Based Teaching Ability Improvement

Authors

  • Yang Xianbi, Wang Shaoyong, Jin Guichao

Abstract

The key to the design and implementation of online teaching system lies in the hierarchical selection of educational resources. The traditional hierarchical screening method of educational resources has low accuracy and low efficiency when the amount of data is large. In this paper, Agent agent-based hierarchical model ERHMA for pre-selection of Web educational resources is proposed. The target resources are screened twice: (1) classified and screened by the filtering algorithm based on semantic similarity; (2) The filtering algorithm based on Q-learning is used to screen twice to reduce the scale of candidate services. The experimental results show that the proposed screening method based on education big data can improve the accuracy and efficiency of the screening results. This method has a certain reference value for the research on the design and implementation of online teaching system under the background of improving teaching ability.

Published

2020-12-01

Issue

Section

Articles