))
Mine Çetinkaya-Rundel: Teaching in the AI era — and keeping students engaged
Manage episode 499643870 series 3678167
Content provided by Posit, PBC and PBC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Posit, PBC and PBC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
In this conversation, Mine Çetinkaya-Rundel, data science educator at Duke University and Posit, joins Michael, Hadley, and Wes to talk about teaching data science in a time when AI can write the code for you. Mine shares her journey from actuarial science to academia, the teaching philosophy behind the “whole game” approach, and her experiments using LLMs for instant student feedback. Along the way, the group dives into the joys and risks of coding by hand, the role of open source in the classroom, and what it’s like to work across both the R and Python communities.
What’s Inside:
- How a career in actuarial science led Mine to the world of data science and teaching
- The “whole game” approach to learning and how it helps students stay motivated
- Building an LLM-powered feedback tool for low-stakes assignments
- Balancing AI assistance with the need for hands-on coding experience
- The shared DNA of R and Python scientific computing communities
- The hidden value of live coding, pair programming, and seeing the process — not just the output
5 episodes
Share
