Direct writing, translated writing, and machine-translated writing: A text level analysis with coh-metrix

Abstract

While learners may have access to reference tools during second language (L2) writing, the latest developments in machine translation (MT), such as Google Translate requires examination as to how using the tool may factor into the second language learners’ writing products. To this end, the purpose of this study was to examine how MT may have an effect on L2 learners’ writing products relative to when writers wrote directly in L2, or translated a text to English from Korean. EFL university learners were asked to write for prompts that were counterbalanced for three writing modes and three writing topics. The learners’ writing products were analyzed with Coh-Metrix to provide information on text characteristics at the multilevel. The results indicate that MT could facilitate the learners to improve fluency and cohesion, produce syntactically complex sentences, and write concrete words to express their target messages. Pedagogical implications are provided for how MT can be used to improve the quality of the L2 learners’ writing products. © 2020 The Korea Association of Teachers of English (KATE).