University of East Anglia, United Kingdom
About the Speaker
Professor Ken Hyland is an Honorary Professor at the University of East Anglia and was previously Director of the Centre for Applied English Studies (CAES) and Chair Professor of Applied Linguistics at The University of Hong Kong (HKU) from 2009-2017. He has published 320 articles and 30 books on writing and academic discourse with over 110,000 citations on Google Scholar. A fifth edition of his Teaching and Researching Writing and a second edition of the Routledge Handbook of EAP (edited with Paul Thompson) will be published by Routledge in 2026. According to the Stanford/Elsevier analysis of the Scopus database, he has been the world’s most influential scholar in languages and linguistics (1st of the Top 2% Most-Cited Scientists Worldwide) for the last five years (2021-2025). A collection of his work, The Essential Hyland, was published in 2018 by Bloomsbury. He is the Editor of two book series with Routledge and Bloomsbury and a Foundation Fellow of the Hong Kong Academy of the Humanities. He was founding co-editor of the Journal of English for Academic Purposes and co-editor of Applied Linguistics.
About the Talk
Feedback Fatigue: Can AI Save Us from Ever More Marking?
With research showing the benefits of corrective feedback to both student writing and student writers, teachers have come under increasing pressure to provide more, including more personalised, and more detailed responses to students. This often places heavy demands on teachers and with ever-larger class sizes and heavier workloads, teacher fatigue and burn out are common. New digital resources have already proven to be valuable in supporting L2 writing and teaching, offering automatic translation, error correction, automated scoring systems, and other benefits. In this paper I look at what they bring to feedback. Beginning with an overview of what feedback offers students, I explore the contribution of Automated Writing Evaluation (AWE) programmes and Generative Artificial Intelligence (GenAI) to feedback. The ability to provide instant corrective feedback across multiple drafts targeted to student needs and in greater quantities promises to increase learner motivation and autonomy while relieving teachers of hours of marking. But are these empty claims raising expectations? What is the role of teachers in all this and can AI really improve writers and not just texts?