Machine Learning for Automated Assessment and Improvement of English Proficiency
Zuo Dan, Yunbo Yuan · 2024
We explored the role of ML (ML) to improve English proficiency. With more people interested in English skills, the importance of learners‘ diversified approaches has been emphasized. ML algorithms are used to automate the assessment process and individualize learning. Thus, we explored various ML methods with natural language processing (NLP) algorithms. Case studies were conducted for the implementation of the methods to show the benefits such as effectiveness and efficiency. Ethical considerations, the role of human governing power, and the application of ML were studied to enhance English proficiency.