Automated Written Corrective Feedback (AWCF) in English L2 Classes: A Case Study on Challenges, Opportunities and Ethics in Students’ Perception

As AI technology advances rapidly, teachers and learners alike must prioritise the development of AI literacy to interact with it effectively (Casal-Otero et al., IJ STEM Ed 10: 29, 2023; UNESCOs, Recommendation on the ethics of artificial intelligence, 2021; Zhai et al., Complexity 1–18, 2021). For example, AI-based writing assistants are praised for giving teachers more time to focus on higher-level concerns of teaching writing (e.g. content, organisation) rather than lower-level concerns (e.g. grammar, spelling and punctuation). However, it is important to note that neither teachers nor students know how to make the best use of automated written corrective feedback (AWCF) and need guidance (Ranalli and Yamashita. Language Learning & Technology 26(1): 1–25, 2022). This mixed methods study explores the potential pedagogical applications of digitally enhanced corrective feedback to improve students’ writing skills through Grammarly®. Students’ responses indicate that the use of the AI-powered tool was of significant help to them as they could obtain personalised feedback featuring their various types of mistakes highlighted in different ways and suggestions for improvements. They specified that this kind of feedback is richer and clearer compared to what teachers’ feedback would look like whenever provided (e.g. just some very brief comments or sometimes just underlining without a specific mention of the exact type of mistake). Based on these results we could argue that teachers of English as a Foreign Language can and should integrate AWCF in their teaching not only for their students’ sake but also for their own. AWCF could be introduced in the classroom as an effective teaching tool that could result in considerable classroom time management.