Integration of Computer-Assisted Teaching Technology in English Online Education Platforms

Abstract

This study proposes an English online education platform centered on the English teaching resource management module and the teaching resources personalized recommendation module on how to closely integrate computer-aided technology into English teaching. In the English teaching resource management module, the fuzzy comprehensive evaluation method is utilized to evaluate teaching resources. An improved placement algorithm, ERRPA, based on the rating of educational resources, is proposed to improve the insufficiency of HDFS files and achieve allocation node modeling. In the English teaching resources personalized recommendation module, then a collaborative filtering algorithm for user clusters is proposed to filter some noisy users using the UCC algorithm, and mix the predicted ratings with the actual ratings through the rating mapping to obtain good recommendation prediction results. In the teaching application of the English online teaching platform, the passing rate of the subject students was improved by 13.79%, the average learning tasks were completed by 59.1% in the online learning behaviors, and the average learning video viewing time reached 89.2 minutes. Learning interest, learning attitude, and sense of independent learning in learning status were improved by 3.2, 4.38, and 4.28, respectively, compared with the pre-experiment, showing highly significant differences (P<0.01).

Keywords

• errpa
• hdfs
• collaborative filtering algorithm
• ucc algorithm
• english online education platform
• 97m50