Bibliometrically and systematically analyzing automated writing evaluation for English learning

Abstract

Automated writing evaluation is highly discussed in artificial intelligence for English learning. It is necessary to explore the effect of automated writing evaluation on learning English as a second language. This study combined bibliometric analysis and systematic review to explore the use of automated writing evaluation for learning English as a second language. VOSviewer was used to identify the highly discussed topics, the top ten cited authors, organizations, countries, references, and sources in the studies on automated writing evaluation. Fifty-six peer-reviewed articles were selected according to the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols. The analysis revealed that automated writing evaluation is helpful, but its effectiveness varies according to the types of feedback, and it cannot replace the role of human feedback yet. Teachers' roles are significant in integrating automated writing evaluation into the classroom. Future research could focus on the specific ways to integrate automated writing evaluation into the classroom better.