Mass adoption of neural machine translation (NMT) tools in the translation workflow has exerted a significant impact on the language services industry over the last decade. There are claims that with the advent of NMT, automated translation has reached human parity for translating news (see, e.g. Popel et al. 2020). Moreover, some machine…

Despite the growing interest in investigating the pedagogical application of Automated Writing Evaluation (AWE) systems, studies on the process of AWE-supported writing are still scant. Adopting activity theory as the framework, this qualitative study aims to examine how students incorporated AWE feedback into their writing in an English as a…

Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…

This study investigated the potential of comprehensive corrective feedback forms as editing and learning tools and examined their effect on learners' cognitive and attitudinal engagement. Low-intermediate second language writers (N = 139) were randomly assigned to four experimental conditions (direct corrections of grammatical errors,…

During the process of translation, students need to learn how to detect and correct errors in their translation drafts, and collaboration among themselves is one possible way to do this. As Pym (2003) has explained, translation is a process of problem-solving; translators must be able to decide which choices are more or less appropriate for the…