Motivation is all you need
The more valuable the AI learning tools we can use become, the more important designing for learner motivation is.
Designing for learner motivation is the key missing piece in educational products. No matter the advances we make in creating better learning experiences from first principles, the failure to design experiences that harness human motivation and specifically intrinsic motivation will always hold us back.
The seemingly unstoppable rise of AI in all aspects of our lives, not least of which is learning and education, makes designing for motivation even more important. It now becomes a central issue when thinking of creating equitable access for technology - and narrowing the gap between the haves and have nots.
Perhaps one of the clearest examples that brings to surface the importance of motivation lies in the ongoing search for the “super AI tutor” - a seemingly silver bullet that will solve all our educational problems.
Belief in mythical figures aside, it is important to understand that tutoring, like almost all the most important educational interventions, has two components: “a motivation intervention (like a personal trainer saying “c’mon, give me thirty more seconds of this plank!”) and an instructional intervention”.
We know a lot about creating good instructional interventions - for motivated students. In contrast, we know relatively little about creating motivated learners in the first place. This is the main reason why most tutoring (and educational) interventions currently report low efficacy, and why the misguided search for a super robo tutor is doomed to fail.
If we care about creating a tide that raises all boats then we need to focus on getting better at delivering motivational interventions or at least strengthening the motivational components in our educational products.
There are at least 3 levers we can pull on in our pursuit of creating and harnessing motivation in learners.
First, we should leverage the science of motivation and embed its key principles deliberately in our product design. We should go beyond gamification and “chocolate covered broccoli” to creating truly engaging and enjoyable learning experiences. Games (not gamification) provide a great source of inspiration here. The rise of AI and other technologies will have a role to play here but better games are more important than better (new) tech.
Second, we should embrace the messiness of human relationships and connection. In order to motivate learners, we must connect with them first as people. Human connection is by design a messy and inefficient process but it is integral to transformational impact. We need to resist the temptation to take out the human connection to make the “process more efficient”
As Paul LeBlanc, former president of SNHU, argues in his latest book “Broken”: successful systems of care or education “use platforms, data, and technology to standardize the non-relational and to support scale, while protecting the space for mattering, aspiration, and relationship”.
Ensuring learners feel they matter, have big aspirations for themselves, and have relationships they can rely on is key to creating motivated learners. It is messy, but integral.
Finally, a big determinant of what motivates people to learn will be the larger culture of learning within which they find themselves embedded. The more valuable the AI learning tools we can use become, the more valuable cultures that support learning will be.
Creating and sustaining a culture of learning is a multifaceted effort - which goes beyond a single classroom, school, home - and certainly educational product. A big part of this is influenced by policy and societal decisions. Nevertheless, we can be intentional about the values we instil in the products we develop and the surrounding learning communities. Games provide another great example here with successful “communities of practice” at Minecraft, Scratch, and others.
On the 12th of June 2017, a group of researchers at Google published a paper under the title “Attention is All You Need”. This paper introduced a new “AI model”: the Transformer (which provides the “T” in GPT). In many ways, that paper heralded the current wave of generative AI. As that wave seeps into education maybe all you (and learners) need is motivation.
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!
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”.