College English classroom teaching method and practice based on big data technology

Abstract

English is an international language and a tool for extensive communication. Learning English is conducive to the mutual communication and exchange of ideas, culture, economy, and many other aspects between different countries and ethnic groups, and is conducive to peaceful coexistence and common development among countries. Countries are increasingly cooperating and exchanging ideas in several sectors due to the broad implementation of current information technology and the rapid speed of globalization. As an international language, English is changing the way of communication. The shift in the emphasis of English language instruction from rote memorization to developing students’ listening and speaking skills will inevitably result in a shift in classroom instruction techniques. Neural networks may be used to assess collegiate English classroom teaching (ECT) techniques and practices, finally completing the following work: (1) Introduces several domestically and internationally related theories and literature on the enhancement of ECT methods and the teaching quality assessment, which will be discussed later. A neural network-based teaching assessment framework is constructed to provide a theoretical basis. (2) Big data technology was employed to obtain appropriate data samples for experiments and verification, which included an ECT technique and practice assessment system tailored to the specific needs of the school. (3) The ECT technique assessment system relies on the BPNN technology. The assessment approach based on the BPNN predicted college ECT and practice extremely well and delivered excellent outcomes, according to the findings of the study.