Brain-Based Learning: Matching LMS Technology to the Way People Learn Best

Recent research on human psychology and the brain has put the design and development of learning technology at an intriguing crossroads.

Old learning management systems (LMS) already use simpler applications of brain science, such as presenting knowledge in bite-sized chunks so it can be consumed by the brain’s limited-capacity short-term memory cup. In addition, these systems are able to enable repetition, which also helps the brain ensure storage in long-term memory.

But these more superficial principles are only the beginning of brain-based learning. With new technology, we can now match desired learning with how the brain learns best at a much deeper level.

 The following three brain-based learning approaches can change the way your organization functions:

1. Gamification and learning

By lowering stress, the act of play helps the brain feel rewarded and can, therefore, promote it to attend and act more clearly. But you should not automatically make knowledge into a game. This alone will not guarantee success.

Specific competencies can be built into the play to increase the brain’s learning capabilities. For example, predictive timing is a skill that involves timely execution. At its height, it is spontaneous, automatically executed, and precise. In business, predictive timing may be relevant in a negotiation or a merger. However, both are very different contexts. Learning should be tailored to the business function and not just generically gamified.
In general, your brain maintains its energy level by switching between the focus and unfocused circuits. In my recent book, Tinker Dabble Doodle Try, I explain why the brain needs this cognitive rhythm. Gamification turns the unfocused circuit off in the brain. As a result, the brain becomes consumed by focus. And too much gamification will exhaust the brain. This needs to be taken into consideration when designing learning and training methods.

Gaming can also provide feedback, reward, and flow states. Each of these elements may enhance learning through technology. Rather than simply providing generic gamification, providing growth and even flow opportunities through virtual reality can add meaningful gaming elements.

2. Internal rewards: It’s not just about kudos

Feedback from others is not the only way we learn. In fact, we learn from ourselves through self-monitoring. Including such self-monitoring systems on learning platforms is valuable, but internal or intrinsic rewards involve more than self-monitoring. These rewards require being curious, interested, and challenged to the point that people will act in the absence of external rewards.
When people are engaged based on intrinsic rewards, they weigh their spontaneous interest and enjoyment. On the other hand, extrinsic rewards involve assessing whether that reward has social value.

Both rewards help learning, and technology may be designed to measure the impact of each type of reward to help fine-tune learning for any given individual. Sometimes, extrinsic rewards cancel out intrinsic motivation. Learning technology should be built to detect this.

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3. Making learning relevant: Implement storytelling

During conditions of heightened uncertainty, the brain requires a level of confidence that shows learning is relevant. To do this, technology must provide some level of feedback, not only on the learning, but also on whether the learning matters. This can be done by helping people be confident that the learning is significant.

Some forms of  storytelling have more value than others. For learning to feel relevant it is not just others’ stories that matter. Technology should be designed to document and allow for the story of the user to unfold.

Also, expressive or emotional storytelling is likely to be more helpful than flat storytelling in which emotion and intonation do not factor in. Expressive storytelling helps people concentrate and engage more. Podcast interviews, for example, may be more constructive than telling a generic story.

Based on the key ideas expressed above, the following table can help learning designers take the brain into account when designing technology. Use this as a checklist:

The new possibilities for training processes and programs that stem from brain-based learning technology are exciting. By matching how the brain learns to technology that fuels drive, utilizes play, and makes learning relevant, the future of training and onboarding has the potential to be diverse and more impactful. By letting go of old LMS principles and integrating brain-based technology, your HR and talent management team can be one step ahead of competitors.

Dr. Srini Pillay, founder and CEO of NeuroBusiness Group, is a pioneer in brain-based executive coaching who is dedicated to collaborating with experts to help people unleash their full potential. He also serves as a part-time assistant professor of psychiatry at Harvard Medical School and teaches in the executive education programs at Harvard Business School and Duke Corporate Education.


3 Comments on “Brain-Based Learning: Matching LMS Technology to the Way People Learn Best

  1. I think these are great tips for effective learning. So I have no issue with the recommendations.

    But as a scientist, it bothers me to suggest these are new findings based on brain imagery studies. Most if not all of these are well established behavioral science research findings rooted in decades of psychological studies. Implying these are “neuroscience” discoveries strikes me as putting old wine in a new bottle. And in my opinion discredits the behavioral scientist researchers who truly uncovered these facts. At worst, one could argue that invoking the term “brain science” in this context might be seen as a form of “neuro-seduction” as described in the study “The Seductive Allure of Neuroscience Explanations”

    I’m not trying to be overly critical, but I do believe that when we invoke “science” as the foundation of an HR recommendation, we have to hold ourselves to a particularly high standard of credibility. Otherwise we risk undermining the credibility of our field overall.

    1. Steven-Thank you for your thought provoking comment. First, I want to say overall that I agree with you, so I wish I had been more careful about pointing out which of these findings was enhanced by brain science, which were advanced by behavioral psychology, and which might be preferred because both have advanced our thinking about this. I think that the next time I write about this, I will do exactly that, so thank you. The comments that follow are not meant to be in defense of your very valid criticism, but to perhaps emphasize a different intention. Many of the studies referenced do in fact use brain-based changes as the basis for their arguments, while others use CBT or psychological narratives as a basis. Also, even if this was simply reframing (old wine in new bottles), reframing can be a very effective learning technique when old methods are no longer impactful. In fact, “multiple reframing” techniques really help us get past habits in thinking. However, certain brain-based facts do carry additional value. e.g. showing activation of the unconscious. Philosophically, I actually really value psychodynamic integrations with brain science too, and I value both the objective and subjective elements of learning. The more I write, the more I think it would be great to talk to you about this, so suffice to say, I find your comment helpful, encouraging, and in certain instances as I have pointed out, debatable. I think we need more integration rather than touting brain science as the be-all and end-all of all knowledge, so perhaps that did not come across clearly enough here. And I think we need to exchange ideas in this way so that we can advance the field together.

      1. Srini, thanks for a very thoughtful and balanced response. I strongly agree the best science combines multiple methods to build understanding. And I think many recent advances in neuro-psychological measurement methods and related findings are fascinating and powerful additions to more traditional behavioral science methods.

        The following point is not directed at you, as based on your response I believe you are approaching this the right way. But I do want to more fully explain the reason for my concern.

        As neuro-seduction research has shown, the mere act of putting a brain scan into a powerpoint presentation makes many people more likely to believe the contents are scientifically valid. And in many cases the use of brain scans is valid. But in many it is not. Last year, I asked some friends who are neuroscience professors (and who don’t make money selling HR consulting) to review several neuroscience presentations by an HR “thought leader”. I will not name this person other than to say it was not you! The consensus was the use of neuroscience by this HR thought leader was at best misguided and at worst highly misleading. I also saw some companies pay a lot of money to this same HR thought leader because they were impressed by their “neuroscience credibility”, only to find out the advice they were given was not nearly as sound, accurate nor scientific as the thought leader claimed. In some cases it even created major disruption to the organization. How likely are the leaders of these companies to listen to any “science based” HR professionals after this experience?

        Thus my sensitivity to this topic. I do agree we need to work together to address these types of issues. As it is through this sort of constructive dialogue that one truly advances the field.

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