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This conversation is with the author of the chapter “Beyond ‘Zoom University’: A Heuristic for Advancing Inclusive Digital and Online Pedagogy” in our new co-edited book, Recentering Learning: Complexity, Resilience, and Adaptability in Higher Education (JHU Press, 2024). The book (in paper and ebook form) is available for order from JHU Press and Amazon.
Jenae Cohn is the executive director at the Center for Teaching and Learning at the University of California, Berkeley.
Q: What main themes of your chapter would you like readers to take away and bring back to their institutions and organizations?
A: In my chapter, I make the case that educators and higher education administrators need to think much more flexibly about what a learning environment can look and feel like. I wrote this chapter in response to much of the pandemic discourse about the “efficacy” of remote learning, which I always found misguided. The unique conditions of the pandemic and the impossible, traumatic conditions under which classes had to be moved online make it impossible to extrapolate any meaningful conclusions about online learning design beyond emergency circumstances.
So, to me, the more valuable takeaway from the extraordinary events of the pandemic is: How do we use the variety of spaces, environments and tools available to us to meet the needs of a diverse student body more meaningfully? And how do we examine space and environment more critically so that more students have an opportunity to succeed? How do we center inclusive and equitable approaches to instruction and align those with what we know about who our students really are? These are the questions I answer in this chapter, and there’s a heuristic at the end that instructors and administrators can use to assess the extent to which their technology-enhanced courses are inclusive and equitable for their students.
Q: What are potential opportunities and levers to recenter learning within research-intensive colleges and universities?
A: Working at a research-intensive university myself, I’m aware that recentering learning in that context requires a focus on inspiring faculty and on reminding them that the experience of teaching and that even students’ experience of learning is, ultimately, joyful. To that end, I think one of the biggest opportunities to recenter student learning is to bring more students themselves into the conversations. What do students love about their courses? What do they find challenging? What inspires or motivates them to learn?
At a place like Berkeley, some faculty have very few opportunities to get to know their students closely, particularly if they are teaching large classes. So, I think the more that leaders in centers for teaching and learning or across campus can amplify student stories, publish student voices and remind faculty of their impact to change students’ lives, the better.
Q: How might the rapid evolution of generative AI impact the work of recentering learning?
A: I think the rapid evolution and prevalence of generative AI (and all of the attendant worries about it) complicates the work of recentering learning. There are both opportunities and threats in focusing on GenAI and its future impacts on the classroom experience. On the one hand, any emergent technology creates an opportunity to rethink our assumptions about what goes into an effective learning experience. Many of the debates about generative AI’s impacts on academic integrity, for example, have led to fruitful conversations about what goes into effective assignment and assessment design, which is all part of recentering learning at the research institution. Yet there’s quite a bit of easy slippage into returning to a very instrumentalist vision of learning when generative AI comes into the mix.
Many of its use cases focus, for example, on outputs and what is, well, generated. We know that effective learning is driven by social experiences and the processes of wrestling with challenging ideas. Generative AI can be part of that process, but instructors and administrators have to be intentional about asking the right questions to that end. It’s less important, in my mind, to see how GenAI can make teaching more “efficient,” for example, and more important to examine how the usage of GenAI technologies shape our values about what’s important for students to learn.
