One of the things that goes into my work is taking research and theory, and putting it into practice. Which manifests in a number of ways, but I thought I’d share one. Credit goes to the team at Elevator 9, because this is definitely a team effort. That is, others take my initial stabs, theory and practice, and turn it into practice. And the results are inspiring.
So, Elevator 9 is about taking what’s done in training events, and augmenting that to actually yield change that sticks. Importantly, also to document same. To do that, they started with my interpretation of the impact of spacing on learning, to yield an initial set of predictions. We moderated that on the basis of practicality.
They have some initial data, and it actually supports the premises. When folks follow the learning recommendations, they learn. When, for instance, they instead try to address all the interventions in one batch at the end, it doesn’t work. Of course, if learners don’t do it at all, they don’t become performers.
One barrier to all this is that people are busy. When the intervention recommendations come, it may not be at a suitable time. That led the team (e.g. COO Page Chen and Elizabeth Dalton primarily, in this case) to look at research on what leads people to actually choose to engage. Naturally, the recommendations, including from CEO David Grad, were to have a ‘pause’ button that would allow the learner to have the recommendation come later the same day. More importantly, the recommendation was to specify a particular time that would be good.
The premise is that when folks can commit to another time, they’re more likely to actually do it. If they actually specify a time, they’re making an even stronger commitment. That’s all to the good! (And that outcome wouldn’t have come from one person, but it comes from partnering.) This is theory again translating into practice.
It makes sense; research on spaced learning typically is done by college students in psych or education classes, in controlled studies. We’re instead looking at real people in real contexts. The reality we all face is different than the controlled conditions most research is conducted in. To be fair, we want those controlled conditions first, to give us predictions, but then we need to adapt to the current circumstances.
In fact, that’s the reason to pay attention to learning science (*cough* The Learning Science Conference *cough*), to get the first best guess and then refine through testing. If you don’t pay attention to the science, either you’re tuning will take longer, or you’ll be so wrong you abandon the initiative (or fall back on mistaken folklore). Neither’s optimal. So, to take theory and practice into practice, you need to take your interpretations of learning science, and then test and refine. It’s work, but the outcome is better. And, that’s what we’re about after all, right?