Learning and transfer
MIT Horizon shares learning strategies for transfer.
By MIT Horizon
In July 1969, humanity achieved a historic milestone. Astronauts reached the moon, opened up the lunar module, and stepped out. Neil Armstong uttered the immortalized phrase “One small step for (a) man, one giant leap for mankind.” It was a beautiful, majestic moment. Now, imagine how much less impressive that would have been if Neil Armstrong had uttered them right before taking an awkward step and falling on his face.
Walking on the moon, as you know, is not the same as walking on Earth. How did they manage to avoid any catastrophic (or, at least, embarrassing) mix-ups, even though it was the first time anyone in history had done it? Was walking on the moon “close enough” to what they already knew how to do? Or was it because they actually practiced, wearing the same kinds of suits, using the same kind of equipment, in situations that simulated what it would be like to walk in low gravity?
As you likely know, Apollo 11 astronauts trained an incredible amount to be ready for what they would face, including practicing in ways that mimic low gravity. They did so in lots of different scenarios and locations, to make sure they felt secure in their abilities, even in the brand new context (outer space!) where they’d be applying them.
Of course, most things we do in life are not as alien as leaving Earth, but every situation we encounter is different from one we have previously learned or practiced. And, unfortunately, humans aren’t really great at adapting to new situations. If you’ve ever tried something new, practiced it a bit, felt really good about your learning, only to find that you hadn’t quite mastered it enough to repeat it, you’ve experienced a failure to transfer your learning. This, sadly, is the default state for a lot of our learning. We learn well enough to feel like we’ve got it down, but not so well that we can flawlessly use that information when we might actually need it. Our mind likes to look at the times when we practice and say “Yes, you’ve got it.” But, in reality our learning tends to be something we might be able to apply in very particular cases, in very similar situations, if we get the right hints or support or if we get a few minutes to relearn it first.
So, how can we avoid that outcome? The good news is that research has found certain approaches to learning are more likely to allow you to use the knowledge and skills you gain, even in novel situations. The bad news is that they generally require more work than more straightforward, rote kinds of learning. But, as astronauts would agree, anything worth doing is worth putting the effort into making sure it is useful!
Learning Strategies for Transfer
In a previous post, we talked about some techniques that lead to better learning — namely, automaticity, conceptual understanding, and generative activities. Those kinds of activities create the kind of robust learning that sets you up to potentially apply knowledge and skills to new scenarios. Let’s dive into another couple of techniques that can help make transfer more likely.
Practice makes perfect
Just like the astronauts we discussed earlier, if the goal of your learning is to be able to apply your knowledge and skills in a new setting, practice doing that! For example, if you are learning project management skills, do some exercises across different domains or using new tools. You could first map out the next few weeks of a software project on a whiteboard, followed by practice in other contexts like launching a new learning and development initiative or in project managing a marketing campaign while using specific software tools. Applying the same skills to these different contexts helps create a more robust understanding of how it can be applied in the future.
Analogies
Another way to practice applications to new situations is through the use of analogies. This provides a way to connect the original learning to a new context, even if it is different from the ones you’ll likely encounter. Sticking with project management, someone learning new techniques in a workshop may be more likely to apply those techniques in the future if they spend some time thinking of the ways in which project management is analogous to, for example, conducting an orchestra or navigating a ship. This extra level of processing and abstraction makes the concepts more generalizable to new contexts.
Alignable differences
To help varied practices have as great an impact as possible, focus on finding alignable differences. While exploring what makes two concepts alike is important, figuring out what distinguishes them is also crucial. For example, someone exploring generative AI systems can aim to learn about general topics, like machine learning, and, to further their understanding in ways that will transfer, can explore the difference between concepts like machine learning and statistical learning or supervised versus unsupervised learning.
Reflection
Reflection is an important part of managing the learning process. It is also potentially useful for helping you integrate new knowledge with your prior experiences, creating a deeper, more flexible understanding. After engaging in a learning activity, take the time to reflect on what you learned, how it connects to what you already know, and how you’d explain it to someone else. These steps can help stimulate the deeper processing that leads to enhanced transferability.
These strategies can help you rethink your learning process. Rather than viewing it like writing a book that gets stored on a shelf, think of learning like creating a new lens to see information through. When you encounter novel scenarios, you can swap those lenses around adaptively instead of using the more laborious process of trying to find the relevant reference in your mental library and retrieving it. This will help enhance how well you can transfer your learning, preparing you to be more flexible and innovative, no matter the situation where you apply it.
Originally published at https://horizon.mit.edu/.
