About a month ago I took an online course on how to use some new software. The training was good and when I had completed the modules I felt that I had a solid grasp on how to use it. One week, two weeks, three weeks, four weeks went by before I used the software again. How did I do? It was almost as though I hadn’t taken any training at all. Sure I remembered the basics, but everything else . . . gonzo. I couldn’t remember most of what I had “learned.” The “forgetting curve” is a classic learning problem. So let’s dig in a bit deeper and explore overcoming the forgetting curve and making a shift to continuous learning.
Most corporate training initiatives isolate knowledge from work. You are taught something in a formal course, then you go back to work and try to apply what you learned. And we all know what happens . . . you forget. Hermann Ebbinghaus, a psychologist in the late 1800s identified the forgetting curve, which shows a dramatic loss of retention over a short period of time when the learning isn’t applied immediately or reviewed over time. The forgetting curve shows that the largest memory loss occurs over the first days.
This becomes a big problem when you isolate knowledge from what needs to be done in a learn-first-then-work learning model. The strategy of “participate in the learning event, now go use it in your job” doesn’t work. We are just not able to retain and apply everything we learn in an isolated learning event.
So what is a strategy for overcoming the forgetting curve and making a shift to continuous learning that gets learning closer to the point when the knowledge is actually needed. There are two parts to this strategy.
Part 1: We know from research that effective learning takes place over time. Ebbinghaus’s research identified that spaced repetition increases long-term retention. A large number of studies and experiments over the years have supported this, some concluding that spaced repetition can increase long-term retention by 200%. Reinforcement of learning-over-time limits forgetting and optimizes performance and should be a key part of the learning strategy. This can be effectively achieved by creating micro-learning, or brief refresher learning bursts, delivered frequently post event. Spaced or distributed learning (especially for the first thirty days after a learning event) gives the learner time to process the information and encode it into long term memory. This ensures that the learning lasts beyond just the learning event, carries into the workplace, and positively impacts retention.
“In the industrial model, we cram as much information into the heads of the learners as possible in eight hours of instruction and hope they learn it. In the distributed practice model, we can “feed” small learning bits to learners everyday for weeks at only fifteen minutes at a time until they learn the material. We can then send a periodic “check” or assessment to see if the knowledge is retained and then, if not, send more instruction. The concept of distributed practice has been known for decades as an effective learning technique but who wants to “study” every day.” – Karl Kapp
How do we leverage the strength of spaced learning? Through the use of microlearning. Brief learning experiences of 3-10 minutes, often based on one or two learning objectives, will reinforce learning and support performance. Content elements include graphics, animations, simulations, stories, scenarios, video, audio narration, interactivity, decision making and knowledge checks.
Part 2: The design and reusability of the brief learning experiences allows us to leverage them for in-the-workflow learning at the moment of need. Giving the learner quick, easy access to critical, brief, just-in-time resources allows them to get beyond the moment when they get stuck, and get back in the flow. It’s a powerful tool that helps the learner handle the uncommon situations and exceptions that occur while working. An important benefit is that less training is required closer to the point of need as we move learning closer to work.