An English Flipped Classroom Teaching Model Based on Big Data Analysis

Comput Intell Neurosci. 2022 Aug 31:2022:7391258. doi: 10.1155/2022/7391258. eCollection 2022.

Abstract

In order to improve the defect that the quality of English flipped classroom teaching cannot be quantitatively evaluated, an English flipped classroom teaching model based on big data learning analysis is proposed. In the English flipped classroom teaching mode, which applies the flipped classroom teaching mode, the classroom teaching links are changed, the preview feedback, joint answer and question between teachers and students, classroom teaching, and teachers' questions are taken as the key links of classroom teaching, and the teacher education and school management system are improved, so as to complete the reform of English flipped classroom teaching mode. The convolution neural network is used to extract the evaluation text features, mine the association rules of massive evaluation text data through the Apriori algorithm, determine the evaluation index of English flipped classroom teaching quality, and complete the evaluation of English flipped classroom teaching quality by using the decision tree method in big data analysis. The experimental results show that the proposed method can quantitatively evaluate the quality of English flipped classroom teaching by using the evaluation text, and the evaluation accuracy and recall rate are higher than 98%, which can realize the objective evaluation of English flipped classroom teaching quality.

MeSH terms

  • Big Data*
  • Data Analysis*
  • Humans
  • Learning
  • Students