I’m joined by Dr Sophia Mavridi to talk about her doctoral research: Second language students’ experiences of AI-assisted writing in higher education: A phenomenographic perspective. Sophia identifies six broad categories that emerge when observing students’ use of AI assisted writing, and in this podcast we dive into these categories: achieving better grades, expressing ideas more clearly, managing time/workload, habituating academic writing norms (e.g., criticality/reflective writing), increasing interaction, and increasing sophistication.

We go over inferences and implications of GenAI in student writing, how talk to students about developing a voice, and how we do this ourselves in our own writing, the tension between making your writing distinctive while adhering to academic norms, where we should set expectations for undergrads versus PhD students. Plus: AI slop on Linkedin.

We also cover Sophia’s paper published last year in Technology in Language Teaching & Learning that critiques institutional responses to GenAI in education including prohibition, avoidance, teacher support, technological enthusiasm, and critical engagement. We discuss directions for language teacher education, including rethinking writing pedagogy, discernment, transparency, teacher educator development, and ethical dilemmas.

Dr Sophia Mavridi is a Senior Lecturer in Educational Technology and TESOL at De Montfort University (UK). She specialises in digital pedagogy, online learning, and AI in education. She has extensive experience in language teacher education, working with organisations such as the British Council, NILE, and Bell Foundation, and is committed to bridging research and practice.

https://sophiamavridi.com/

Watch Sophia’s keynote form the TELSIG symposium earlier this year: Behind the scenes: How students use AI (and what we can learn from it).

The survey Sophia alludes to at approximately 55 minutes in is the HEPI Student Generative AI Survey.

Mavridi, S. (2025). Hype, Fear, and Everything in Between: A Critical Typology of Responses to AI and their Implications for Language Teacher Education. Technology in Language Teaching & Learning, 7(2), 103219 Available at: https://doi.org/10.29140/tltl.v7n2.103219

00:00 Podcast intro

01:41 Reflections on the PhD Viva

04:55 Teacher identity

08:19 Overview of the PhD research

09:26 Six AI writing categories

11:03 Integrity and voice

14:33 Participants and context

16:55 Self regulating AI use in writing

19:33 Students surprising sophistication

24:45 Struggle in L2 writing

32:12 Why writing still matters

38:19 Academic norms versus authorial voice

44:11 AI and the loss of voice

49:09 Institutional AI typology

51:51 Teacher education directions

57:05 AI detectors and in-class writing

01:07:30 Tech hype vs pedagogy

01:11:53 Reading AI research critically

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.

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.

I'm joined by Peter Davidson from Zayed University to discuss the 2023 article by David Brooks: 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.

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 at Leeds on June 19th.

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