Exploring the Teaching Mode of Secondary English Education Based on Big Data Technology

Abstract

With the rapid development of information technology represented by big data, all walks of life are facing the inevitable trend of transformation in the direction of informationization. English education teaching, as an important part of secondary education, naturally needs to utilize big data technology to carry out in-depth reform. This paper proposes a teaching model for secondary English education that is based on big data technology. For the teaching evaluation stage of this model, we created the DKVMN-FMF teaching effect assessment model, which incorporates the forgetting mechanism. By incorporating a dynamic key-value memory network, the assessment model can predict students’ answers’ accuracy, taking into account the forgetting phenomenon in the learning process. Through comparative experiments, this model’s AUC and accuracy are higher than other models on different data sets, indicating that the DKVMN-FMF model can accurately assess students’ learning effects. During the teaching experiment, the mean English score increased to 77.014 points after implementing the big data technology-based English teaching model, marking a significant difference from the pre-experiment mean score of 65.532. The paired samples test revealed a significant difference with a Sig value of 0.001, less than 0.05. The English teaching model that utilizes big data technology can enhance students’ English performance, as demonstrated.

Keywords

• dynamic key-value memory network
• dkvmn-fmf model
• forgetting mechanism
• teaching mode investigation
• 62-07