Discover
Dead Ideas in Teaching and Learning
Dead Ideas in Teaching and Learning
Author: Columbia University Center for Teaching and Learning
Subscribed: 43Played: 686Subscribe
Share
© Copyright 2026 Dead Ideas in Teaching and Learning
Description
Dead Ideas in Teaching and Learning is a podcast from the Columbia University Center for Teaching and Learning. Our mission is to encourage instructors, students, and leaders in higher education to reflect on what they believe about teaching and learning.
69 Episodes
Reverse
Thomas Tobin, one of the foremost voices on Universal Design for Learning (UDL), joins us to preview his forthcoming book, UDL at Scale: Whole-Campus Universal Design for Learning. Where his earlier work made UDL manageable for individual instructors, Tobin's new publication asks what happens when an entire campus — including administrators — advocates for and values universal design. Tobin first joined the Dead Ideas in Teaching and Learning podcast to discuss inclusive teaching in 2022 (listen to "Student Perceptions of Instructor Authority and Inclusive Teaching").In this episode, we tackle the dead idea that learners make impartial, rational decisions about how they learn best. Tobin complicates this notion by sharing a contemporary example: students' increased reliance on AI to bypass the fundamental building blocks of learning. He argues that students will thrive as co-designers of learning only when UDL supports underlie those classroom experiences. UDL is only effective when it is possible, permitted, supported, rewarded, and expected across an educational institution at the faculty, student, and administrative levels.Learn more about our guest’s new publication: Tobin, Thomas J. UDL at Scale: Whole-Campus Universal Design for Learning (Oklahoma University Press, 2026)Other publications mentioned in this discussion: Tobin, Thomas J. Reach Everyone, Teach Everyone: Universal Design for Learning in Higher Education (West Virginia University Press, 2018)Weimer, Maryellen. Learner-Centered Teaching: Five Key Changes to Practice (Wiley, 2013)
For five years, Chris Gallagher, Kristi Girdharry, and Kevin Smith sat down each semester with the same set of twenty Northeastern University students. What began as an analysis of these students’ writing skills evolved into a book on how students often understand the learning process more clearly than faculty recognize. Gallagher, Girdharry, and Smith's new book, Getting Learning Right: The Promise of Higher Education, takes aim at some of the myths that circulate in public discourse about college - that students enroll simply for the credential or that everything can be learned online, for example. In this episode, we focus instead on what the students themselves had to say about their own undergraduate experience. These anecdotes and the insights they provide might just be the inspiration we need to reshape the future of higher education. Learn more about our guests’ new publication, Getting Learning Right: The Promise of Higher Education (MIT Press).Other articles mentioned in this conversation: “Not Just Another AI Statement: Modeling Process and Collaboration in Higher Education” (Inside Higher Ed)
In this special bonus episode, we step away from our typical one-on-one interview format to share excerpts from a student panel that our host Amanda Irvin moderated at the recent "Reimagining Teaching and Learning in the Age of AI" Forum. This event was a joint effort coordinated by the Columbia Center for Teaching and Learning, the Data Science Institute, Columbia Alliance, the School of Engineering, and Teachers College.Four Columbia students, representing a range of disciplines, backgrounds, and relationships with AI, reflect candidly on what it's actually like to be a learner in this moment. They share how AI functions in their academic lives, what they wish faculty understood about their use of it, and what they need from instructors as the landscape continues to shift. The conversation is less a debate about AI and more an exploration about the relational fabric of learning. A full transcript with speaker attributions and bios, as well as a link to the video recording, are available in the show notes.
In this episode, we sit down with Dr. Madisson Whitman, Director of Undergraduate Studies and Assistant Director of Curriculum Development at Columbia University's Center for Science and Society, and Lecturer in the Department of Anthropology. Drawing on her work in Science and Technology Studies (STS), Whitman challenges one of the most pervasive assumptions of our moment: that AI in higher education is a foregone conclusion.In her recent letter to the editor in the Columbia Spectator, a student-run campus newspaper, Whitman offered a direct rebuttal to the sentiment that "AI is here to stay, so what does that mean for Columbia?" Instead, she invites us to resist the sense of "technological inevitability" that pervades so much of today's academic dialogue and to ask what we might be foreclosing when we don’t question AI’s presence in education.Together, we trace the through-lines between pandemic-era surveillance, "dysfunction creep," and the quiet ways AI is being folded into the learning management systems. We also consider what it looks like to teach with AI rather than through it. Dr. Whitman reminds us that progress is never as linear as it's sold. Educators must keep learning at the center of the conversation, even when urgency and marketing do their best to crowd it out.Other materials referenced in this episode: "AI Is Here to Stay: What Does That Mean for Columbia?" — Columbia Spectator"Letter to the Editor: AI Is Not Inevitable" — Madisson Whitman"A Rant About Technology" — Ursula K. Le Guin
In this episode, we talk with Dr. Lucy Appert, Senior Director of Teaching Excellence & Innovation at NYU Arts & Science, and host of the new NYU Office of Teaching Excellence and Innovation’s podcast, What Learning Looks Like. As an academic with 25+ years of teaching experience and a deep commitment to student-centered practices, Lucy shared with us her insights on what learning truly means in an age of AI-driven "efficiency."Together, we discuss a key problem in higher education: while educators may accept the messy, developmental nature of learning, students are being marketed an idealized reality where AI-supplemented education is frictionless and instantaneous. The What Learning Looks Like podcast offers a counter-messaging to this misleading EdTech and AI marketing. Instead, true learning involves struggle, synthesis, and personal transformation. Lucy also challenges one of higher education's most persistent “Dead Ideas”: that we cannot change. From pandemic pivots to new faculty communities exploring AI in the classroom, it is clear that higher education is very capable of fluctuation and change. Explore the What Learning Looks Like podcast: https://podcasts.apple.com/us/podcast/what-learning-looks-like/id1839490516 Other materials referenced in this episode: Learning Objectives & Bloom’s Taxonomy



