Cognitive diagnostic models (CDMs) have received much interest within the field of language testing over the last decade due to their great potential to provide diagnostic feedback to all stakeholders and ultimately improve language teaching and learning. A large number of studies have demonstrated the application of CDMs on advanced large-scale…

This innovations in practice article introduces a chatbot that was developed to support and motivate second language learners during the COVID-19 pandemic. The chatbot was designed to facilitate active, out-of-class language learning to supplement in-class input. It can adapt to learners' abilities and pace by chatting with them, thus providing…

When viewed through a generic, one-size-fits-all perspective, use of input enhancement does not appear effective. Through analysis of individual grammatical features and different learner proficiency levels, a significant impact may be revealed. To study the impact of input enhancement on diverse grammatical features, 16 short reading texts and…

This study used eye-tracking, in combination with stimulated recalls and reflective journals, to investigate L2 learners' engagement with automated feedback and the impact of feedback explicitness and accuracy on their engagement. Twenty-four Chinese EFL learners revised their writing through Write & Improve with Cambridge, a new automated…