Dead Ideas in Teaching and Learning

Chris Hakala, director of the Center for Excellence in Teaching, Learning, and Scholarship (CETLS) at Springfield College, joins us this week to dismantle a persistent myth about centers for teaching and learning. With over 30 years in faculty development, assessment, and the study of student learning, Hakala challenges the dead idea that a CTL’s job is to simply hand faculty a fixed set of best practices about student learning.Instead, Hakala argues that fixed practices don’t always meet faculty where they are or reflect the realities of a given academic discipline. Particularly in the age of AI, the most effective CTLs are grounded in evidence-based pedagogical theory while remaining adaptive and creative in their recommendations on how those theories can be expressed in a given classroom. CTLs can and should recognize that every school, department, and discipline will need a customized approach to student learning.Recommended Readings / References: Cramblet Alvarez, Leslie D., and Christopher M. Hakala. Understanding Educational Developers: Tales from the Center. Routledge, 2024.Schofield, Paul. "Why Pedagogy ‘Experts’ Are Wrong." The Chronicle of Higher Education, 22 Apr. 2026, www.chronicle.com/article/why-pedagogy-experts-are-wrong.Appert, Lucy, host. What Learning Looks Like. NYU Arts & Science Office of Teaching Excellence & Innovation, 2024, sites.google.com/nyu.edu/whatlearninglookslikepodcast/home. 

Dr. Tommy Lee, a behavioral neuroscientist in Barnard College at Columbia University’s Department of Neuroscience and Behavior, joins Dead Ideas in Teaching and Learning to challenge one of higher ed’s most persistent assumptions: that memorization is a low-level task standing in the way of real learning. Dr. Lee’s research considers how the brain forms episodic memory, including our memories of experiences and spaces.In this episode, we tackle the dead idea that remembering and thinking are opposites. Lee complicates this notion by drawing on his own research into the hippocampus and other studies on working memory, disproving the notion that memorization crowds out critical thinking. Lee argues that as AI agents make it easier to “just look up info,” this dead idea is again becoming pervasive in higher education. We end the episode with practical guidance for instructors looking to build retrieval practice into their coursework. The end result is a classroom that lowers the stakes for students, reduces their anxiety, and makes progress more tangible. Recommended Readings / References: Lee, S. L. T. (Forthcoming 2027). Neuroscience of learning for AI-enhanced teaching. In E. R. Reynolds & B.R. Johnson (Eds.), The Oxford Handbook of Undergraduate Neuroscience Education. Oxford University Press.Krathwohl, D. R. (2002). A Revision of Bloom’s Taxonomy: An Overview. Theory Into Practice, 41(4), 212–218. https://doi.org/10.1207/s15430421tip4104_2Pfeiffer, B. E., & Foster, D. J. (2013). Hippocampal place-cell sequences depict future paths to remembered goals. Nature, 497(7447), Article 7447. https://doi.org/10.1038/nature12112Pan, S. C., & Rickard, T. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710–756. https://doi.org/10.1037/bul0000151Cowan, N. (2010). The Magical Mystery Four: How Is Working Memory Capacity Limited, and Why? Current Directions in Psychological Science, 19(1), 51–57. https://doi.org/10.1177/0963721409359277Gobet, F., & Simon, H. A. (1996). Recall of rapidly presented random chess positions is a function of skill. Psychonomic Bulletin & Review, 3(2), 159–163. https://doi.org/10.3758/BF03212414Qin, S., Cho, S., Chen, T., Rosenberg-Lee, M., Geary, D. C., & Menon, V. (2014). Hippocampal-neocortical functional reorganization underlies children’s cognitive development. Nature Neuroscience, 17(9), 1263–1269. https://doi.org/10.1038/nn.3788Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), e2422633122. https://doi.org/10.1073/pnas.2422633122Smith, A. M., Floerke, V. A., & Thomas, A. K. (2016). Retrieval practice protects memory against acute stress. Science, 354(6315), 1046–1048. https://doi.org/10.1126/science.aah5067Haak, D. C., Hille Ris Lambers, J., Pitre, E., & Freeman, S. (2011). Increased Structure and Active Learning Reduce the Achievement Gap in Introductory Biology. Science, 332(6034), 1213–1216. https://doi.org/10.1126/science.1204820Diekelmann, S., & Born, J. (2010). The memory function of sleep. Nature Reviews Neuroscience, 11(2), Article 2. https://doi.org/10.1038/nrn2762

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.