From Hardwood to Classroom: Unleashing the Power of Visible Thinking To Transform Learning
We can take a page from the world of sports to create a paradigm shift in how we are leveraging the rise of generative AI to create better learning expereinces
The basketball crossover is a simple yet powerful move - if you know how, when, and why to use it.
Popularized in the NBA by Tim Hardawy’s “killer crossover” in the 90s, the crossover is a basketball maneuver in which a player dribbling the ball pretends to go one way and then switches the ball rapidly from one hand to the other, to make a change in direction.
The goal of the crossover is often to create space for your next move. If executed correctly it’s almost unstoppable. It even worked on MJ.
I first picked up a basketball in the 4th grade. I still remember trying my first crossover - “unguarded” and in my own half. I didn’t know why or when you did a crossover. I just knew how to execute it.
A conversation with our gym teacher later that day helped me better understand when and why a crossover is effective. She could only provide that valuable and incisive coaching because sport makes thinking visible. It makes your thinking easier to coach.
Movement unmasks a great part of our internal logic and helps others see what we are aiming for. You can look at the interaction between any two players and see if not hear the conversation - provided you speak “the language”. It’s poetry in motion.
The success of any good coaching and tutoring system is greatly dependent on making learners’ thinking as visible as possible. That’s why it can sometimes be easier to coach players in a game than tutor students in the classroom.
There’s a lot of exctiment at the moment that the rise of AI will make tutoring better. Unfortunately, many if not most AI-powered tutoring efforts are currently focused on the ability to deliver more personalized content which while valuable will not create the paradigm shift required for the breakthrough we all seek.
Conversational agents (powered by large language models or LLMs) provide us with a uniquely scalable opportunity to make “thinking visible” and understand how learners think more clearly.
One way to do this is by asking students to teach and train their own AI-agents - not the other way around. Instead of creating more Dr. Oaks to mentor aspiring Pokemon masters, we need to create more Pokemon for aspiring learners to train.
By engaging with a conversational agent, powered by LLMs, novices can more easily and readily surface their thinking process. We can imagine a future where each individual has their own LLM that they’ve taught different skills that are then put to the test.
By doing this conversationally, we encourage learners to be structured, methodical and clear about the underlying component of any skill - or their perception of it.
The beauty of this approach lies in its potential for visible thinking: we can interrogate these LLMs to see where the learner might be misunderstanding a concept or missing crucial information. The thinking becomes very visible.
If this concept seems a little futuristic, consider this: it's already common practice in the world of software development. Just like an author who needs an editor to proofread and review their work, software developers utilize a process known as 'code review'.
In a code review, developers read and check each other's code, looking for errors and suggesting improvements. This practice encourages transparency in the thinking and problem-solving process, allowing for better collaboration, understanding, and ultimately, learning.
Training their own “pokemon” and deploying it on a quest in a simulated environment is not the only way to make learners’ thinking visible - although it might be the most fun. Other examples could be:
Interactive storytelling: LLMs can engage students in interactive narratives where they play a critical role in shaping the story. This allows learners to express their understanding and creativity, making their thought processes and problem-solving strategies visible. For example, students can be asked to guide a character through a series of obstacles using their knowledge of a particular subject.
Role playing exercises: LLMs can participate in role-playing exercises where students assume different roles and perspectives. This can help surface their understanding of complex concepts, empathy, and ability to see things from different viewpoints.
Reflective Journaling: LLMs can prompt students to engage in reflective journalling, asking them to document their thought process as they work through a problem or learn a new concept. This not only makes their thinking visible but also promotes metacognition – thinking about their own thinking.
Everybody seems to be working on launching their own AI-powered tutor with the explicit goal of scaling one-to-one tutoring. These efforts are important but will not create the paradigm shift needed to truly move the needle on learning outcomes. They will just create more of the same.
To really push the needle on tutoring, we need to completely shift the paradigm. We need to put learners in the driver’s seat. Only then can we make their thinking visible and see where they are dropping their killer crossovers - and in turn make sure they deploy them more effectively.
I hope you enjoyed the last edition of Nafez’s Notes. I’m constantly refining my personal thesis on innovation in learning and education. Please do reach out if you have any thoughts on how to make thinking more visible or any other ideas. If you are building a startup in this space I’d love to hear from you!
Finally, welcome to all the new subscribers that have joined since the last issue. Please do reach out if you have any thoughts or comments and don’t forget to share with your friends.
If you are new here you might also enjoy some of my most popular pieces:
The Gameboy instead of the Metaverse of Education - An attempt to emphasize the importance of modifying the learning process itself as opposed to the technology we are using.
Using First Principles to Push Past the Hype in Edtech - A call to ground all attempts at innovating in edtech in first principles and move beyond the hype
We knew it was broken. Now we might just have to fix it - An optimistic view on how generative AI will transform education by creating “lower floors and higher ceilings”.
That's a very interesting perspective! I think also that integrating social interactions in that realm that you suggest will add to the richness of the experience. I believe the paradigm shift lies in personalizing education entangled with enabling students to exchanging knowledge not only with AI models, but also with each others.