I’ve written before about learning experience design, but I want to take it a bit further. I think we can, and should, go for an aspirational goal, one that stretches us. I want us to work on “transformation.”  So what do I mean by transformation? One way to think about it is “extreme” engagement.

I’ve been pushing the boundaries of my own understanding about learning as a background to design. My goal is to go further than just fact presentation, and lead to not only new skills, but new ways to look at the world. It may be a stretch, but I believe it’s one worth making.

Transformation through training

This isn’t new. A number of theorists have looked at what is called transformative learning. Mezirow’s theory is the original, and others have proposed different facets. Ultimately, however, it’s precipitated by a “disorienting dilemma” and through a variety of necessary steps leads to a fundamentally transformed self. It includes a change in ways of looking at the world, sparked by reflection and reintegration.

One of the problems with this approach is that it requires some serious issue as a catalyst. The type of thing being talked about with transformative learning can even be traumatic. And while we want a learning experience to be meaningful, we don’t want to ruin people’s lives, particularly just to develop a skill.

A gentler approach comes from Pugh, et al. They were looking to create greater understanding, but at a smaller scale, what they call transformative experiences. Here, they’re looking for new perspectives, but without a life-altering event. However, their focus is largely on K6, and has to do with applying scientific knowledge to enable new understandings, which is good, but telling people to go out and find out how an idea changes their perspective is not as focused as we need.

The principle here, of smaller but still meaningful change is important; the question is how to frame it usefully for the sake of designing experiences.

Expectation and perception in learning

A rich expression of the drive for learning comes from the “free energy principle.” This model suggests that learning occurs for a specific reason. The goal is to conserve energy by minimizing the gap between what we expect will occur, and what ultimately happens. That is, we learn to become better aligned with the world.

We can either change the world, or ourselves, which is a powerful explanation for the value of models. Causal models of the world serve the specific function of explaining occurrences and predicting outcomes. Our brains naturally build these models (as the theory would predict). And our natural approach works well for what Geary terms “biologically primary learning.” These are things like dangers, and social interactions. However, for human-made constructs like mathematics, which are biologically secondary, our instinctive learning may take us astray.

This implies, however, that building useful models is more complicated at the level of most of schooling. What we need is to find ways to make such learning of primal importance and then support the outcomes. We need to motivate and support learning.

The free energy principle also implies, at face value, that sitting in a warm quiet room will achieve this lack of “surprise.”  Yet we have drives that mean we have to exert ourselves; we need to eat, sleep, and more. We therefore are driven to experiment to improve our models. However, if the costs are too high we won’t. Ultimately this means we need to make it safe to experiment. At the biologically primary level, we call this play.

Integrating conation and cognition

In cognitive science, we differentiate between the cognitive (thinking), affective (feeling), and conative (volition) aspects of our actions. And instructional design tends to ignore the latter. We are beginning to understand the importance of motivation for learning, and the need to reduce anxiety. Yet that’s the way we make secondary learning plausible.

So, I’ll suggest that to start with creating a transformative learning experience, we need to help learners understand that there’s the need to know, and that they don’t know it. If they don’t believe they need to know it, they won’t care. If they think they already know it, they won’t invest. It takes both.

This is where tapping into intrinsic interest matters. We can find out from the experts why they’ve spent years learning about this, why they find the topic fascinating. Or we can make the case for the abilities they’ll acquire and why they’re important. And they may already get that they don’t know it, but if they’re overconfident, it may take waking them up.

Once we’ve secured their interest, we’re not done. Even if they commit, they may lose interest, or they may backslide. And we need to address both. It has to be more than “do it until you get it right.” It may not be “until you can’t get it wrong,” either. I think a reasonable approximation is that they do it until they’re confident enough to risk it in the real world. Again, confidence is an affective issue, not a cognitive one.

And, we need to not just pique their interest, but maintain it. The practice activities that allow them to make and test predictions need to be contextualized so that they recognize it’s a real, and interesting, application. And the level of challenge needs to be appropriate. Moreover, it has to be “safe” to fail. Once they’re committed, you don’t want to lose that momentum. Ultimately, they should be prepared to go out and apply the knowledge to real-world problems.

From there, in many ways it’s similar to change management. Even if they’ve bought in, they may backslide. You may need to address their confidence, provide encouragement, reward appropriate behavior, cite other successes, make progress manifest, and more. Scaffolding success through coaching and stretch assignments, gradually removed, can cement this new ability.

If we can make a model meaningful, provide practice applying it, and leave the learner with confidence in a new skill, I’ll suggest we’ve transformed them. And that, in my mind, is a good outcome.