Neural Machine Translation in Second Language Writing: a Systematic Review


Authors: Yucheng Mao, Fulan Liu

Abstract: The advent of artificial intelligence has led to the emergence of a novel form of machine translation (MT), namely neural machine translation (NMT), which has significant potential for application in the field of second language (L2) writing. This review aims to synthesize the various approaches to effectively integrating NMT into L2 writing pedagogy and practice. A comprehensive search was conducted in a well-established database based on specific criteria. The findings indicate that NMT is an effective tool for developing L2 writing skills and that it is particularly well-suited to advanced L2 writers, as higher proficiency levels result in more critical reflection on NMT output. Finally, this review demonstrates that NMT has significant pedagogical implications. It serves as an invaluable online reference tool for L2 writing, provided that teachers introduce students to its benefits and limitations by implementing various teaching approaches.

Pages: 143-153

DOI: 10.46300/9109.2024.18.14

International Journal of Education and Information Technologies, E-ISSN: 2074-1316, Volume 18, 2024, Art. #14

PDF DOI XML

Certification