The Science of Remembering

How much of what we learn do we actually remember? And what if one of the most effective ways to learn is to regularly challenge ourselves to recall what we already know?

In episode 164 of Teaching Python, Kelly Schuster-Paredes and Julian Sequeira welcome Python educator and Python Morsels creator Trey Hunner to explore the testing effect, retrieval practice, spaced repetition, and interleaving. Trey shares how learning the countries of the world through his geography app, Whereabouts.Earth, helped shape Daily Recall, a spaced repetition learning system for Python programmers.

The conversation goes beyond remembering the right answer to ask whether we understand what we know. Are we recalling a concept or recognizing the shape of a familiar question? Can we apply what we have practiced when the context changes? From Duolingo to Python exercises, the hosts explore why recall needs to work alongside mental models and practical experience, and why learning that feels harder can be more useful over time.

They also examine what this means when AI can generate code for us. Trey, Kelly, and Julian discuss the difference between learning something deeply and getting a task done, how much understanding we need to evaluate AI-generated work, and why foundational knowledge still matters for making informed decisions.

The episode closes with a challenge: before moving on, write down what you want to remember from this conversation. Then see what you can recall a week later.