30 GenAI and the art of motorcycle maintenance
Gareth Price, Postgraduate Student, Digital Technologies and Education, United Kingdom
In the final study block of my postgraduate degree, I completed a module called ‘Artificial Intelligence Perspectives on Learning’. As part of the assessment for this module, we were required to design and create a digital artefact or activity, using one of the tools we had tried out in the unit to teach an aspect or concept of GenAI which is relevant to education and learning. The tools I used to create my artefact were Scratch, Machine Learning for Kids and ChatGPT.
Taking inspiration from ‘Zen and the Art of Motorcycle Maintenance’ by Robert Pirsig (1974), I made an artefact introducing the user to motorcycle maintenance. Pirsig referred to the scientific method of problem solving: to identify a problem; suggest a hypothesis; conduct an experiment to test the hypothesis; and draw a conclusion as to whether the hypothesis was correct. I needed to use GenAI tools as I had zero experience of motorcycle maintenance myself.
It felt exciting, even cheeky, to think that I could create a learning resource that might teach someone about motorcycle maintenance, without having any knowledge of the subject of my own. Rather than presenting subject matter in a book or a video, I would be getting the user to organise the subject matter for themselves, for someone else to use or to potentially apply their knowledge to the real thing. The artefact interprets the user’s hypotheses as they experiment with why a motorcycle horn is not working. It acts as an extension of the mind by simulating the potential avenues the user might take if they had a real motorcycle in front of them. The artefact was designed to give the user an opportunity to test their hypotheses by interacting with an image of a motorcycle.
Each iteration of the scientific method would introduce the user to concepts in the structure of the motorcycle. This, ultimately, would require “structures.. so complex … no one person can understand more than a small part of them in his lifetime” (Pirsig 1974). That’s where ChatGPT and Machine Learning for Kids came in. These AI tools answered the call for (1) knowledge of the system and (2) scope for the language to allow the user to suggest hypotheses to access this knowledge. These tools enabled me to gather and organise the subject matter far more efficiently than I could alone.
Even new tools can still give us the satisfaction of learning from our own experiences
In the evaluation of the artefact, I was reassured that a particular user recognised its purpose fairly quickly and said, “it’s like troubleshooting”. It wasn’t something I’d considered in the design, but is a link to technical manuals – an entry level to understanding how a system works – that Pirsig (1974) makes in his book. There were a few ‘hallucinations’ which didn’t seem to put the user off: “It’s coming to me now”. This shows that a tool such as this doesn’t have to be faultless; and could still engage the user in experimentation.
As an educator, I have a new appreciation for using GenAI in the context of the ‘scientific method’. When presented with problems, I am more open to using GenAI tools to explore solutions. We surround ourselves with tools, as Robert Pirsig did in his workshop. Even new tools can still give us the satisfaction of learning from our own experiences.
GenAI Tool(s) Used:
References
Pirsig, R. M. 1974. Zen and the Art of Motorcycle Maintenance: An Inquiry into Values. London: Vintage.
