How we got from English to Ed Tech. With Andrea Flores and Ben Naismith

How we got from English to Ed Tech. With Andrea Flores and Ben Naismith

All of us started our careers somewhere, and today I'm talking to two old friends and former colleagues about how our years teaching English as a foreign language shaped our view of education and the world. We talk about the resilience and adaptability that those early classroom days taught us, the overwrought lesson plans, learning humility from failure, and how these experiences inform our work now in higher education management, instructional design and ed-tech.  We go on to discuss the direction of education, the resurgence of interest in humanities subjects in the face of AI, staying up to date with knowledge and skills in an ever-changing jobs market, and the general chaos of those unique times in our lives. Guest Bios Ben Naismith, PhD is a Staff Assessment Scientist at Duolingo where he works on research and development of the Duolingo English Test. Prior to joining Duolingo, Ben worked extensively in the field of English language teaching in numerous contexts as a teacher, teacher trainer, materials developer, assessment specialist, and researcher. His current work and research into the assessment of L2 English proficiency focuses on vocabulary assessment and automated scoring of speaking and writing. His work has been published in journals including Language Testing, Studies in Second Language Acquisition, Language Teaching Research, Language Learning, and Assessing Writing, amongst others. He is the lead editor of the forthcoming Routledge Handbook of Digital Language Assessment: Innovations and Insights from the Duolingo English Test. Andrea Flores is Senior Instructional Designer at MIT Sloan School of Management and Founding member of the Boston AI2030 Chapter. She’s an AI lead and human-centered design practitioner with a diverse background in education, public health, workforce development, and technology. She has worked across non-profits, higher education, and global health, and focuses on human impact and sustainable solutions.

Staying Human in the Age of AI. With Peter Davidson

I'm joined by Peter Davidson from Zayed University to discuss the 2023 article by David Brooks [https://www.nytimes.com/2023/02/02/opinion/ai-human-education.html]: [https://www.nytimes.com/2023/02/02/opinion/ai-human-education.html] In the Age of AI, Major in Being Human, which claims: "AI will force us humans to double down on those talents and skills that only humans possess. The most important thing about Al may be that it shows us what it can't do, and so reveals who we are and what we have to offer." What might these ‘human’ skills and attributes be that we will need in the age of AI? In this podcast we will try to identify these human skills and attributes (what might be termed ‘capacities’) that have become more essential to us as humans, as AI becomes embedded in teaching and learning, and in the workplace. It is these human capacities, Peter argues, that will become increasingly important for our us and our students as the impact of AI grows. See the full list of Essential Human Skills [https://drive.google.com/file/d/1wxkigiThOQ-zYc8fl2bdmw1UQYetbtJL/view?usp=drive_link]. Guest bio Peter Davidson teaches Business Communication and Technical Communication at Zayed University in Dubai, having previously taught in New Zealand, Japan, the UK, and Turkey. He is currently interested in exploring how Generative AI is impacting language teaching and assessment practices, and how it can be leveraged to improve the educational experiences of students. Peter is presenting at the upcoming BALEAP PIM [https://www.baleap.org/events/upcoming-events/profile/online-pim-eap-and-the-academy-in-the-age-of-genai-implications-for-practices-and-practitioners] at Leeds on June 19th. Further Reading The framing of autonomy, mastery and purpose that's referred to in the discussion was popularised by Daniel Pink in his 2012 book Drive: the surprising truth about what motivates us. This draws on the work of Richard Ryan and Edward Deci, and Self-Determination Theory. Anderson, D.J., Rainie, L, & Anderson, J. (2026). Human Wisdom for the Age of AI: A Field Guide to Cultivating Essential Skills. Elon University and AAC&U. Anderson, J. & Rainie, L. (2025). Being Human in 2035: How Are We Changing in the Age of AI? Imagining the Digital Future Center. Gerlich, M. A. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), 6. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf Pink, D. H. (2012). Drive: the surprising truth about what motivates us. Edinburgh: Canongate. Postman, N., & Weingartner, C. (1969). Teaching as a Subversive Activity. New York: Delacorte Press. Raman, A. (2024). Investing in Human Skills in the Age of AI. LinkedinLearning, California, USA. Ryan, R and Deci, E. (2000). Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychological Association. 55 (1). Available at: DOI: 10.1037110003-066X.55.1.68

Lead us not into temptation: notes from the StudentXGenAI Project. With Stephen Gow

Last year HEPI reported 95% of students were using gen AI, but recent research from Stephen Gow and Sam Illingworth casts 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? Guest Bio 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 [https://www.studentxgenai.co.uk/]), 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 [stephen.gow@york.ac.uk] or via Linkedin: Stephen Gow | LinkedIn [https://www.linkedin.com/in/stephen-gow-77556a73/]  Further reading 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 [https://doi.org/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 [https://doi.org/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 [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/ Timecodes 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

Has machine translation killed conversation? With James Lamont and Jiaoyue Chen

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? Speaker bios 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.  Further reading 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 [https://doi.org/10.29140/jaltcall.v21n3.103256]  Timecodes 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

When does offloading become outsourcing? With Paul Kirschner

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 [https://www.kirschnered.nl/2025/11/01/when-phones-go-out-the-window-learning-comes-in-the-door/] and cognitive offloading vs outsourcing [https://paulkirschner173727.substack.com/p/offloading-no-outsourcing]. https://substack.com/@paulkirschner173727 [https://substack.com/@paulkirschner173727]  Guest bio 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. Further reading  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