A New Machine Learning Framework for Effective Evaluation of English Education

Abstract

With the rapid development of information technology, English education has attracted the interest of scholars for its ability to rely on computers to analyze and understand human language. Taking machine learning (ML) as the core, this paper tries to develop an evaluation system for ML-based English education. Specifically, a basic ML model was established with four stages: environment, knowledge base, learning process, and implementation process. The entire ML system was divided from top to bottom into a user layer, a business layer, and a data layer. Application results show that, during the ML, even users with similar personal data and the same goal have vastly different suitable learning materials, due to their gap in personal capabilities. The research provides an effective way to evaluate English education in the context of computer science and artificial intelligence.