Finding Your Flow With Generative AI

Finding Your Flow With Generative AI

There’s a lot of debate about the possible impact of generative AI in education. It’s still relatively and most schools are just scratching the surface with it, or waiting for further/better guidance about how they should or could use that technology. Part of the uncertainty relates to its impact on what we might call ‘deep learning.’?

As I have previously referenced, a recent research paper suggested that one of the threats of AI is that it will mark the point at which we hit ‘peak humanity’ - meaning that we will lose the motivation to learn and evolve because we can offload this work to AI. We will cease to be curious, investigative learners, hungry for knowledge. ?

However, I want to point to an alternate version of the future in which generative AI actually helps learners hit a state of flow. ?

Flow theory is one of my favourite bits of research, because not only is it something you can both explain and understand with relative ease, it’s also something that it’s exciting to experience! The theory comes from Mihaly Csikszentmihalyi and is based on his research on happiness and creativity. Flow theory describes the optimal mental state in which a person is fully immersed and completely absorbed in an activity, to the point where they lose a sense of time and self-consciousness. This happens when a person gets the right balance of challenge, along with skill and when it does, time passes quickly because you’re absorbed and happy with the work because it is highly stimulating, but you also feel like progress is being made. ?

I think that generative AI could really assist with helping students find that state of flow. One of the things it is good at, is helping to remove obstacles to learning by giving you the information you need. The immediacy of generative AI means that you don’t have to lose momentum, you can keep asking until you find what you’re looking for and the conversational element means that there is a sense of progress. ?

Of course within the process, we still need students to cross-reference and fact checking, but the energy created by the process means that they might be able to move through problems far quicker with a sense that they have a support network talking them through the work – not answering THE question (though of course it could), by answering THEIR questions, which supports them. ?

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In simple terms:?

A student needs motivation to make progress. Motivation comes when your skill level is pushed to a comfortably high level, that is met by the challenge and you find a state of FLOW. Generative AI can support a student by helping get their skill level up to the level of the challenge and if this happens, they will find themselves making progress. ??

Of course there are easier ‘route one’ ways of using generative AI, but the human element of this process – teachers training young people how to effectively engage with this technology – is how we can begin to have a different conversation about what the opportunity of all this development really is. ?

We don’t need to reach ‘peak humanity’ - the technology doesn’t need to make us lazy – we just need to find the ways in which it inspires us to want to know more. ?

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