The Brain Science of Microlearning: Why It Works
In 2015, millennials surpassed Gen Xers as the largest generation in the workforce. By 2025, they will make up 75 percent of the workforce. That means that in the next 10 to 15 years, we will see the greatest transfer of knowledge that has ever taken place. With the transfer of knowledge comes a transfer in learning behavior.
We watch videos, access Instagram or Facebook posts, search retailers, buy products online, and check our emails and social media accounts several times a day. Everything comes into the brain very quickly, and it comes in small pieces.
Employees receive information outside of work in little chunks and snippets – whether they’re millennials or not. We need to reach learners in a way that is most comfortable and natural for them – with short snippets of information, available through apps and mobile devices, that are ready and accessible when and where the user needs or wants it.
Why Microlearning Works
Microlearning is a method that uses small moments of learning to drive job performance and employee development. It is appropriate when the learner needs help doing something specific or reference a snippet of content. Microlearning is short and to the point, based on a topic or problem, and easily searched by asking a question or entering keywords.
Most e-learning comes in more of a “macrolearning” format, such as instructor-led classes and massive open online courses, also known as MOOCs. Early in a role, employees need macro-learning to understand their job and the skills they need to perform it. Then, they need reminders of that learning. That is where microlearning comes in.
The theory behind microlearning suggests that short, repetitive learning increases long-term comprehension rates. It has only more recently been popularized due to the widespread availability of mobile devices and apps that allow us to easily apply and integrate the theory into our everyday lives.
The concept of spaced learning was best explained by the research of Hermann Ebbinghaus, a German psychologist who found that progressive injections of new knowledge have a rapid memory decay in the brain. His spaced learning theorysuggests that “learning is better when the same amount of study is spread out over periods of time than it is when it occurs closer together or at the same time.” Ebbinghaus found that repeated practice would enable people to retain more knowledge with each repetition.
Now, let’s look at this theory from a neurological perspective. The more we repeat and use information, the more likely it is to end up in long-term memory. That is why microlearning works so well, particularly with the shift in learning demands we’re seeing today.
In fact, more the 50 percent of 385 employees surveyed by Software Advice indicated that they would be more likely to use their company’s LMS if the lessons were shorter. Longer courses are not only more challenging to digest and retain, but taking them also gets in the way of employees’ daily work. Additionally, research shows that learning in bite-sized chunks makes the transfer of learning from the classroom to the desk 17 percent more efficient.
Microlearning not only mitigates cognitive overload but also supports long-term retention. To that point, Ebbinghaus determined that “overlearning – that is, continuing to practice and study even when we think that we have mastered the material” often prevents us from realizing that breaks and continued repetition prove critical in retaining information long-term. Microlearning is the slow-and-steady tortoise to the cognitive-overloaded hare.
That’s why studying over time helps people perform better on tests than when they “cram.” Unlike sensory and short-term memory, which are limited and decay rapidly, long-term memory can store a huge amount of information for a long time. Between each learning experience or review of a learning experience, learners’ brains need breaks – or spacing – so that the information can be processed and moved from short-term into long-term memory.
Microlearning is quickly becoming such a critical part of the e-learning landscape. Learning solutions must be grounded in the neuroscience of learning but adaptive, evolving to deliver quick snippets of information in the format we’ve now become accustomed.