Every field counts on science for optimal outcomes. For instance, if carpenters didn’t make use of their knowledge related to math, physics, geometry, and biology (wood, concrete, and so forth), buildings would fall down. Perhaps every carpenter doesn’t know ALL of the math, physics, geometry, biology, and other sciences that go into their craft, but they know the general practices that encompass those sciences.
Likewise, practitioners in the field of learning must count on practices based on learning sciences to provide worthwhile learning outcomes.
Last year, in the ATD Science of Learning Blog, I discussed some straightforward science of learning concepts, such as:
- what it means to learn
- science of learning aims
- how the science of learning can help us with training outcomes.
In 2016, I’m going detail more fully how specific aspects of the learning sciences improve our outcomes. Let’s start with learning transfer.
Learning = Effort
In my May 2015 blog post, I made the statement that “all learning is a refinement of prior knowledge.” The implication is that L&D practitioners need to design learning that considers the prior knowledge that people bring to the table. Sometimes people don’t have enough prior knowledge, sometimes they have a lot, and sometimes the prior knowledge they have is inaccurate.
Here’s the basic idea: When learning, people are involved in “cognitive” (or mental) processing:
- Finding the relevant information.
- Organizing it logically for themselves.
- Integrating it with what they already know (in long-term memory).
People have to create meaning by these (somewhat simplified) processes in order for the processing—or learning—to “stick.” However, they don’t merely pull in what is presented to them and “stuff it” into their memories. First, people must interpret what is presented to them and figure out what parts are important. Then, they have to organize that information into something coherent to them (as personal knowledge), related to what they already know.
Think for a moment about the difficulties of each of these steps. Now, think about all the things learning practitioners may do that can make it even more difficult. In the learning sciences, the ability to create meaning while learning is called “generative learning.” Generative learning takes place when you are able to finish these steps. All learning is generative, in that it requires these steps).
How Do We Know If Learning Stuck?
Because the ability to create meaning (these three steps) is the chief task of learning, how can we know whether it actually occurred? It’s really not through instructional tests. The most critical test is if they can DO what they are trying to learn. On the job, it‘s being able to DO what the instruction is training them to do.
In the language of the science of learning, this is called a “transfer test.” In other words, did the instruction transfer to the workplace? What’s more, research tells us this doesn’t happen that easily.
So, simply asking learners to recall questions on a post-module test doesn’t cut it. In other words, if we have determined that instruction is needed, the assessment should measure transfer—or we don’t know if our work is working.
What Instructional Strategies Promote Sticking?
The obvious next question is “Which instructional methods promote the types of mental/cognitive processing that promote these three steps?” Fortunately, we know one thing for certain: any method must have people connect new information to what they already know.
For example, one method is to get people to summarize what they learned. This is why people write a summary of what they learned from keynote speakers and conference presentations. They realize that creating summaries in their own words helps make what they learned stick. It’s also a terrific study method for anything else you really want to stick.
Indeed, producing a concise summary in your own words does exactly what we discussed earlier:
- figure out what is most important (and what isn’t)
- organize info logically
- determine how to present it coherently and concisely as new material.
This requires interpretation, based on your own understanding and including prior knowledge. How might L&D practitioners use this method in a more asynchronous mode? While this is certainly not as good as producing your own summary in your own words, a designer could create three or four similar summaries with “typical misinterpretations” woven into the wrong ones. (Keep in mind that you should provide very good feedback that explains why those typical misinterpretations are wrong, or you will have lost the opportunity to correct misinformation!) This would cause the reader to do a cognitive task like the one discussed earlier in this. Having to create your own summary requires more effort, but it requires a lot of effort to think through the summaries and compare them.
Next month, I’ll discuss additional instructional strategies L&D pros can use to have people connect new information to what they already know and how we might do this in typical training settings. Can you think of some yourself? Leave me a message about this or any questions you have about this blog post.
Sources
Fiorella, L., & Mayer, R. E. (2015). Learning as a generative activity: Eight learning strategies that promote understanding. New York: Cambridge University Press.
Lee, H.W. Lim, K.Y., Grabowski, B.L. (2008). "Generative learning: Principles and implications for making meaning" in J. M. Spector, M.D. Merrill, J. van Merrienboer, & M.P. Driscoll, (Eds.) Handbook of research on educational communications and technology (3rd ed.). (pp.111-1240. Mahwah, NJ: Lawrence Erlbaum.
