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 I 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

Phil is joined by Lily Abadal and Nidhi Sachdeva to talk about reducing device reliance, rebuilding in-class writing, and using technology with clear pedagogical intent. Lily describes redesigning written assessments by breaking the traditional term paper into smaller in-class, long-form writing components, encouraging device-free classroom culture without heavy policing, and emphasizing silence, reflection, discussion, and mentorship.

Nidhi brings research from cognitive science to bear on tech-related concerns like distraction, cognitive load, and outsourcing thinking. She guides us through the limitations of flipped learning, and why we might want to bring some COVID legacy independent tasks back into the classroom.

We also lay out the stall for why personalised feedback, workbooks and visible teacher investment in students are things worth hanging on to.

Lily Abadal is an Assistant Professor of Instruction in the Philosophy Department at the University of South Florida - St. Petersburg. She specializes in normative ethics, applied ethics, moral psychology, and philosophy of psychology. Her recent interests include moral injury, character formation, and AI Ethics. She explores all things through a Neo-Aristotelian lens.

She’s interested in helping mission-centered schools design pedagogical strategies, develop integrity-centered policies, re-imagine assessments that align with their values, and encourage genuine character formation in the age of AI.

Lily writes about all of the above on her Substack, Wisdom in the Machine Age: https://substack.com/@wisdominthemachineage

You can also find more information on her website: https://www.drlilyabadal.com/

Nidhi Sachdeva is a leading Canadian Science of Learning researcher, specializing in evidence-informed learning design, post-secondary education, and educational technology. She teaches online learning and microlearning from a cognitive science perspective at OISE’s Department of Curriculum, Teaching, and Learning at the University of Toronto. A recognized expert in translating educational research into practical classroom strategies, she has been featured on numerous podcasts and currently serves as Chair of researchED Toronto.

Check out Nidhi’s Science of Learning Substack. Listen to Nidhi’s previous TELSIG podcast appearance on education myth busting.

Abadal, L.M. (2025) Only the Humanities can save the university from AI. [Online]. Public Discourse. Available at: https://www.thepublicdiscourse.com/2025/07/98429/ [Accessed 23 January 2026].

Kirschner, P. (2025), When phones go out the window, learning comes in the door. [Online]. Krischnered. Available at: http://www.kirschnered.nl/2025/11/01/when-phones-go-out-the-window-learning-comes-in-the-door/ [Accessed 23 January 2026].

Oakley, B., Johnston, M. Chen, K, Jung, E. and Sejnowski, T. (2025). The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI. [Preprint]. Available at: https://arxiv.org/abs/2506.11015

00:00 Intro 02:34 Lily’s background: ChatGPT forces a rethink of assessment 04:08 Rebuilding the term paper: in-class slow writing and device-free culture 08:29 Nidhi’s stance: thoughtful EdTech (not a tech war) 12:30 Offloading vs outsourcing: what cognitive science says about AI/tech 15:45 What is the classroom for now? Mentorship, practice, and attention 18:29 Lily’s new class design: handouts, recall, annotation, discussion 30:03 Lessons learned from flipped teaching 35:40 The practicalities of unplugging in Higher Ed 37:21 Lily’s case against ChatGPT in Philosophy 44:46 Distinguishing EdTech from AI and social media 53:48 In-class writing as an alternative to exams 55:04 Workbooks and human feedback 01:02:02 Beyond essays: low-Stakes Mastery Quizzes & Assessment for Learning 01:03:25 Why Handwriting Works: Engagement, Cognitive Science & Iterating as a Teacher

Deanne, James and I gather around a virtual Yuletide fireplace, roast chestnuts and perform that time-honoured festive tradition of chewing over key moments in learning tech and EAP from the year gone by. Much as the shepherds probably did.

Is a full in-class digital detox a good idea, and is this a weird thing to suggest in a technology enhanced learning podcast? Did we ever figure out whether students real-time subtitling us is a problem? Would any of us pay for AI-generated music? Did we get carried away with flipped learning after COVID?

As we look back on the debates that have lit up 2025, we'd like to wish all our listeners an awesome holiday and a happy new year.

Listen to Klaus Mundt and Michael Groves on TELSIG

Eaton, S. E. (2025). Global Trends in Education: Artificial Intelligence, Postplagiarism, and Future‑focused Learning for 2025 and Beyond – 2024–2025 Werklund Distinguished Research Lecture. International Journal for Educational Integrity, 21(12). https://link.springer.com/content/pdf/10.1007/s40979-025-00187-6.pdf

Flenady, G., & Sparrow, R. (2025). Cut the bullshit: why GenAI systems are neither collaborators nor tutors. Teaching in Higher Education, 1–10. https://doi.org/10.1080/13562517.2025.2497263

Kirschner, P., (2025), When phones go out the window, learning comes in the door. Krischnered. Available at: http://www.kirschnered.nl/2025/11/01/when-phones-go-out-the-window-learning-comes-in-the-door/

Plate, D., & Hutson, J. (2025). The intellectual bankruptcy of anti-AI academic alarmism: a rebuttal. Teaching in Higher Education, 1–12. https://doi.org/10.1080/13562517.2025.2562594

00:00 Intro to the guests 02:41 James’ new paper on student use of translation 10:24 The case for digital detox 14:03 Pedagogy leads 16:41 Phil’s phones away experiment 19:55 Has flipped learning failed? 26:03 Do students still need English? 29:31 Do unsupervised assessments provide evidence of learning? 34:50 The AI bullshit paper 38:04 Plug for the TELSIG symposium 39:54 Would you pay for AI music? 46:47 Reverting to what makes for good learning 51:35 TELSIG’s Christmas message

James Lamont is an Associate Lecturer in Skills Development, Department of Education, University of York in the United Kingdom. His research interests include the effects of generative AI on student thought processes and outputs, and how universities can adapt to this new environment.

Deanne Cobb-Zygadlo has been an EAP tutor at Nazarbayev University since 2015. She is the co-coordinator of the Technology-Enhanced Learning Special Interest Group (TELSIG) with BALEAP, which is the accreditation organization for the NU Foundation Year Program. She is also a member of the ENAI (European Network for Academic Integrity) Policies Working Group.