Episode 49: Jason Lodge

"You can't have an aha moment unless you go through a period of being stuck or struggling or confused before you get there.”

“AI will help you get to the finish line, but it's not going to give you the kind of work related positive impact that you would have by going through that process yourself.”

In this 49th episode of The Opposite of Cheating Podcast, David is joined by Professor Jason Lodge (University of Queensland), an educational psychologist and lead author of the Australian Framework for Artificial Intelligence in Higher Education.

Together, David and Jason dig into what the learning sciences tell us about “the work of learning”—why meaningful learning is often hard, why confusion can be a productive signal, and how AI can create a “performance without process” trap by helping students reach the finish line without building the underlying capability. Jason argues for moving beyond single snapshot assessments, equipping educators with a toolbox of context-sensitive approaches, and re-centering human relationships in teaching—especially as scale, equity, and the future role of teachers come under pressure.

The conversation closes with a clear throughline: know students better to understand their learning better, and keep asking whether we’re doing the things that truly matter.

You can follow Jason on LinkedIn at https://www.linkedin.com/in/jasonmlodge/

You can access the Australian Framework for Artificial Intelligence in Higher Education at https://s3.ap-southeast-2.amazonaws.com/assets.acses.edu.au/app/uploads/2025/12/Lodge-et-al-2025-Australian-Framework-for-Artificial-Intelligence-in-Higher-Education.pdf.

(Disclaimer: episode quotes and summary were created using Youtube's Transcript and ChatGPT and edited by a human. Any errors are the responsibility of the human).