Last year HEPI reported 95% of students were using gen AI, but recent research from Stephen Gow and Sam Illingworth cast doubt on this figure. Today I’m joined by Stephen to talk through some of the key finding of his Leverhume Trust funded study that draws data from over 7,000 participants. What do students really think about gen AI in higher education, and how should this shape the way we treat it in the curriculum?

Dr Stephen Gow was the Leverhulme Research Fellow at the Department of Learning and Teaching Enhancement (DLTE) at Edinburgh Napier University. During this role he led the Student Experiences on Generative AI Project (StudentXGenAI), this project carried out the StudentXGenAI Survey with a response rate of over 7000 students at UK institutions and interviews with students across the UK in addition to integrating GenAI into the research process. He is an expert on academic integrity, assessment and GenAI, and the Chair of the Northern Academic Integrity Forum. He is now associate staff with Department of Education, University of York and available for consultation and research projects related to GenAI in education. He can be contacted at stephen.gow@york.ac.uk or via Linkedin: Stephen Gow | LinkedIn

Chung, J., Henderson, M., Slade, C., Liang, Y., Pepperell, N., Corbin, T., Walton, J., Yu, AS., Bearman, M., Buckingham Shum, S., Fawns, T., McCluskey, T., McLean, J., Oberg, G., Seligmann, A., Shibani, A., Bakharia, A., Lim, LA., Matthews, KE. (2026). The use and usefulness of GenAI in higher education: Student experience and perspectives. Computers and Education Open, Available at: doi: 10.1016/j.caeo.2026.100347.

Gow S, Illingworth S (2026), "Dynamic tensions: an AI-assisted critical scoping review of university students' qualitative experiences of GenAI". Artificial Intelligence in Education, Vol. 2 No. 1 pp. 67–89, Available at: doi: 10.1108/AIIE-06-2025-0151

Gow, S. and Illingworth, S. (2026) “It is a temptation to get it to do the work…” – student experiences of GenAI in UK universities. 09 Apr 2026. Advance HE. [Online]. Available at: https://www.advance-he.ac.uk/news-and-views/it-temptation-get-it-do-work-student-experiences-genai-uk-universities [Accessed 20 April 2026].

The Castlereagh Statement is available at: https://castlereagh.ai/

00:00 Welcome and guest intro

01:12 Duolingo streak talk

06:20 Tech backlash and attention

10:46 Generative AI literacy risks

19:23 Introducing StudentXGenAI

22:31 Survey design and access

24:54 Who uses GenAI and why

27:23 Productivity versus learning

31:42 Massification and student pressures

34:26 Research goals and policy impact

34:48 Survey design choices

35:52 UK vs Australia findings

36:47 Why usage rates differ

38:15 Regulation and risk

39:07 Learning tool doubts

41:11 Assessment scales explained

45:42 Trust and honesty data

49:44 Fairness and incentives

56:55 Exams after COVID

01:03:59 Data privacy and costs

01:07:31 Future research

Language students using machine translation has certainly raised lots of questions for those of us teaching English for Academic Purposes over the past few years. But most of the conversation has been around its impact on written compositions. A new study by Lamont and Cirocki looks at how and why it's changing the way international students interact verbally with each other and their teachers.

We're joined today by James Lamont, the lead author of the study, to dig into the data and talk about the implications for the language classroom. What steps do teachers need to take to enable learning to actually take place?

Jiaoyue Chen is an Academic Practice Adviser at the University of York, where she supports colleagues’ professional journey through the PGCAP programme, York Professional and Academic Development scheme recognition, and the York SoTL network. With a background in Applied Linguistics, she worked as a Lecturer in English Language and Education at Huazhong University of Science and Technology in China. She still returns to this area of research with great interest, but also seeks to disentangle the nuanced relationship between SoTL and formal pedagogical research to better support student learning.

James Lamont is an Associate Lecturer at the University of York in the Department of Education and the School of Business and Society, where he supports student skills development. His research interests are student use of technology and developing working relationships across student cohorts.

Lamont, J., & Cirocki, A. (2025). Talking to algorithms, not students: Students’ and lecturers’ perceptions of machine translation in academic discussion. The JALT CALL Journal, 21(3), 103256. https://doi.org/10.29140/jaltcall.v21n3.103256

00:00 Intro to MT in the classroom 01:19 James Lamont and Jiaoyue Chen 03:08 Talking to algorithms 04:58 Groves and Mund’s previous work on MT 04:58 Real time translation in class 07:36 Language acquisition concerns 12:19 Tasks versus learning goals 16:15 The impact of MT on non-language learning 20:42 Overreliance and false confidence 26:00 Accuracy culture and dependency 29:48 Policy gaps and overreliance 31:04 Setting classroom expectations 32:57 Phone boundaries and culture 34:15 Structured tech use phases 35:23 Proficiency gaps and support 38:06 Accents, idioms and listening load 43:24 Anxiety comfort and safe seminars 48:50 Privacy, recording and shame 51:48 Student buy-in and agency 54:56 Ideal classroom and future research 58:03 Final Takeaways And Paper Credit

Are smartphones and laptops enabling or impeding students’ progress in class? On the plus side they give access to a wealth of resources, but they can also kill interaction and provide any number of distractions. Today we dig into the research on devices in class with educational psychologist Paul Kirschner.

Paul also clears up the confusion around cognitive offloading, what it really means and what’s actually happening when we use AI. Is it really just another tool like a calculator?

We talk about these and a range of other learning tech topics, including future research directions for multimedia assessment, and what we can reasonably ask of practitioner research.

Check out Paul's Substack via the link below, and the posts for today's conversation on phones in the classroom and cognitive offloading vs outsourcing.

https://substack.com/@paulkirschner173727

Paul Kirschner is one of the most influential voices in the national and international education debate. For decades, he has done research on and has been translating scientific insights about learning, memory and teaching into clear applications for education.

Paul is professor emeritus at the Open University of the Netherlands, honorary doctor (Doctor Honoris Causa) at the University of Oulu (Finland), visiting professor at the Thomas More University of Applied Sciences in Flanders and owner of the educational consultancy kirschner-ED. Previously, he worked as a teacher of Science, Chemistry and Mathematics in secondary education and was active in school boards and participation councils of both secondary and secondary education.

He is regarded worldwide as a leading expert in his field and has published approximately 450 scientific articles, in addition to several hundred popular science contributions and blogs for teachers and school leaders. In addition, he is the first or co-author of several influential and widely read books, including Instructional Illusions, How Learning Happens, How Teaching Happens, Evidence-Informed Learning Design, Ten Steps to Complex Learning, Developing Curriculum for Deep Thinking and Urban Legends about Learning and Education.

Sungu, A., Choudhury, P. K., & Bjerre-Nielsen, A. (2025). Removing phones from classrooms improves academic performance. Available at SSRN: ssrn.com/abstract=5370727 or dx.doi.org/10.2139/ssrn.5370727