Engagement And Motivation: Brain-based Learning And Other "Silver Bullets"

Engagement And Motivation: Brain-based Learning And Other "Silver Bullets"
Summary: Games, gamification, humor, animation, and brain-based learning.

Pros And Cons Of Engagement Techniques

This is the last part of the three-piece series exploring different approaches to increasing learner engagement.

Games And Gamification

Games and gamification (two different approaches) are sometimes lumped together as an engagement tool. Surely, if anything creates engagement, it is fun! What does the research say? Many other articles online refer to a study showing that gamification can increase engagement and retention by 90%! Who wouldn’t want that level of engagement? They even cite the source: "The Federation of American Scientists, 'A Meta-Analytical Examination of the Instructional Effectiveness of Computer-Based Simulation Games' (2001, Tracy Sitzman) [1]."

A meta-study sounds compelling as it reviews other studies rather than just relying on one single study. Except, when you read the study by Traci Sitzman (note: it’s not Tracy, it’s Traci) you’ll learn what they really found:

[...] Consistent with theory, post training self-efficacy was 20% higher, declarative knowledge was 11% higher, procedural knowledge was 14% higher, and retention was 9% higher for trainees taught with simulation games, relative to a comparison group. However, the results provide strong evidence of publication bias in simulation games research.

Overall, it is positive. But how did this 9% retention rate turn into 90%? If you’re interested in digging deeper into games and gamification myths, I’ve spent a full article on that [2].

That said, microlearning (discussed in the previous part), with the combination of spaced retrieval over time, games, and gamification applied correctly in alignment with performance goals can and should be in your design toolkit. I’m just not convinced that novice learning designers have the time and expertise to dig through all these snake oil stats to find the truth behind them.


One of the elements of games and gamification that delivers on engagement is surprise. In their book, Surprise: Embrace the Unpredictable and Engineer the Unexpected, Tania Luna and Dr. LeeAnn Renninger explore their research findings and surprise you a lot:

Through colorful narratives and compelling scientific findings, authors Tania Luna and Dr. LeeAnn Renninger shine a light on the world's least understood and most intriguing emotion. They reveal how shifting our perception of surprise lets us thrive in the face of uncertainty. And they show us how surprise acts as a shortcut that turns a typical product into a meaningful experience, a good idea into a viral one, awkward small talk into engaging conversation, and daily life into an adventure.


Emotions are often left out of learning design because we need space for all the content "to cover." Did you know that you can design surprise as well? The authors do a great job explaining the phases of surprise through their research and what can go wrong with your "engineered design." On a personal level, I enjoyed the authors’ writing style as well. And speaking of emotions, this research-based TED talk (or book) by Dr. Lisa Feldman Barrett is a must:

For the past 25 years, psychology professor Lisa Feldman Barrett has mapped facial expressions, scanned brains and analyzed hundreds of physiology studies to understand what emotions really are. She shares the results of her exhaustive research—and explains how we may have more control over our emotions than we think.

Emotions are also at the center of Nick Shackleton-Jones's How People Learn: Designing Education and Training that Works to Improve Performance through his 5Di affective context model of learning. If you're interested in this user-centered design model, start with this short video intro: you might be surprised at how emotions play a role in the learning process.


Humor can rely on surprise as well. Good storytellers and public speakers use humor to drive home a point, make us reflect, or just enlighten the room. The question is, should we use humor in learning design to increase engagement? Connie Malamed has a well-written article on using humor in learning. She walks us through some of the pros and cons of this element [3].

Banas (2011) sums it up well, "The clearest findings regarding humor and education concern the use of humor to create learning environment. The use of positive, non-aggressive humor has been associated with a more interesting and relaxed learning environment, higher instructor evaluations, greater perceived motivation to learn, and enjoyment of the course."

Emotional engagement promotes better recall and increases perceived motivation to learn. But only if the humor is directly related to the actions and decisions people need on the job. If humor is simply entertainment to spice up the content, then it can become a distraction. In fact, you will most likely remember the funny script but not what the learning was about. I literally had this conversation with a colleague last year, where both of us recalled a funny sales training (including the characters and the scene) but neither of us could remember what the topic was.

Humor And Brainstorming

One positive side effect of humor is creative thinking. When you bring people together to brainstorm, nobody wants to come up with ideas that are laughable. But if you deliberately ask for wrong or impossible solutions, for example, you’ll see examples of much better divergent thinking.

Brain-Based Learning

I have to admit, back in the day, I was thrilled to learn about my neurons and brain chemicals such as dopamine. I was amazed at how quickly I became a neuroscientist of learning. Or not. Today, I’m more confused than ever about what we know and what we don’t know about the brain, and especially the practical implications of this for learning design. I am still amazed by the various brain plasticity studies and fMRI pictures but we overgeneralize and misunderstand the findings.

What Is Brain-Based Learning After All?

Isn’t all learning brain-based? Like foot-based walking? Aren’t we just unlucky with labeling things: microlearning is not about duration; the 70:20:10 approach is not about the numbers; gamification is not about designing games; and now, we have brain-based learning. I did my best to find the official definition of brain-based learning for workplace learning. All I can say is that it’s supposed to use the latest findings from neuroscience to guide us on how to design brain-friendly learning experiences.

The Theory Vs. Practice

In theory, we all agree it is important to design for the brain. In practice, however, we seem to disagree on how we put that theory into practice. The problem is that brain-based learning means different things for everyone. When I posed this question on LinkedIn, a lot of people chimed in with "to me..." answers. The more articles I read on the topic, the more I became convinced that it is a mix of already known things from learning science and cognitive psychology, along with overgeneralized specific lab findings. But then it gets worse. Articles refer to learning styles (debunked), goldfish memories (debunked), visual brains processing information 60,000x faster, raising our dopamine by playing a game, etc. There was one name that I bumped into over and over again: Abreena Tompkins.

"Physiologically, your neurons are keen and aware for no more than 20 continuous minutes," says Abreena Tompkins, an instruction specialist. "Your neurons have gone from full-fledged alert to utter collapse during those 20 minutes, and it takes two to three minutes for them to recover and return to total alert fully. You’ve shifted your focus if you take a pause longer than three minutes [4]."

Wow! 20 minutes, exactly? How does Abreena Tompkins know that? Searching for brain-based solutions I kept running into references to Abreena Tompkins and her meta-study:

“Our brains are only capable of staying focused for short bursts of time. Abreena Tompkins understands this very well. She performed a huge meta-analysis of brain-based research on learning and concluded that "Physiologically, your neurons are keen and alert for no more than 20 consecutive minutes. At the end of those 20 minutes, your neurons have gone from full-fledged alert to total collapse..."

It is not entirely clear how the paper selection process happened for her dissertation but it appears that brain-based learning was accepted "as is" with its own category. In fact, none of the learning science papers mentioned brain-based learning. Brain-based learning was its own category [5]. The main source for the quotes above was actually Perry [6].

Learning requires attention. And attention is mediated by specific parts of the brain. Yet, neural systems fatigue quickly, actually within minutes. With three to five minutes of sustained activity, neurons become "less responsive;" they need a rest (not unlike your muscles when you lift weights). — Perry

Is It Fact Or A "Silver Bullet"?

Unfortunately, I couldn’t find this paper anywhere. On a positive note, Oprah and Dr. Bruce Perry just came out with a book! Is brain-based learning a fact or a silver bullet?

No matter whether I agree with someone's opinion or not (as long as they are based on cited research), I always tend to dig for the opposite position to have a balanced view. Thanks to Paul A. Kirschner and Mirjam Neelen, I found the reality check about "Brain-Based Bullocks" [7].

One of the key takeaways for me (and anyone whose audiences are not lab animals or paid grad students in isolated studies but rather people in the messy workplace under competing priorities and often unclear goals) is that you can’t just grab some lab findings and pop it into the classroom. For example, repetition is good for memory and recall, but it can significantly reduce motivation. As a learning professional you need to find the balance, not just based on neurons and brain chemicals, but also on the reality in the workplace. According to Daniel Willingham, neuroscience applied to education is mostly unimpressive [7].

Learning became like sports where everyone can have an opinion and strategy without any data to remotely support it as long as it looked scientific. I am hopeful that in the next decade we will learn more practical things about the brain that we don’t know today. But we have a long way to get there. Today we’re not even applying basic, evidence-based findings that we do know of.


Movement is more engaging than static things! Then let’s make things move! Animation is for the rescue?

Animation is not one thing. It has different styles. This can range from arranging limited, pre-drawn elements to handcrafted masterpieces. Viewers may not necessarily know (or should know) how much work goes into animations but there is time, cost, and quality at risk if we don’t set expectations.

Animation does not just simply mean "moving." Animation is about the story that is depicted by the movement. The word "anima" means "soul." If you just make something move for the sake of engagement and ignore the soul part, you’re not an animator, you’re a mover.

Does Animation Improve Learning?

It can. According to Connie Malamed, research is mixed on using animation. Probably because we use it for the wrong reasons?

There are quite a few studies that compared animation-based learning to learning from static graphics. In these studies, the effectiveness of animation produced mixed results and some results were even contradictory. On the down side, there were several studies that showed animation-based learning had no notable benefits compared to still graphics (Teversky et al., 2002).

When to use animation, then? According to a meta-study, one of the most effective ways to use animation is when the specifics of the displayed changes themselves are the focus of learning:

The results of three meta-analyses show that the effectiveness of learning from animations, when compared to learning from static pictures, is rather limited. A recent re-analysis of one of these meta-analyses, however, supports that learning from animations is considerably more effective than learning from static pictures if the specifics of the displayed changes need to be learned [8].

From the perspective of practicality, high-end animations (hand-drawn and custom-made) are one of the most expensive and time-consuming elements of learning design. Any little change request by stakeholders through the review cycle can lead to time and budget issues.

What About Pre-Built Animation?

A common use of animation is the illustration of a story or the "spicing" up of narratives. For that, hand-drawn animation would be too expensive. What about pre-built animations such as Renderforest, Animaker, PowToon, Moovly, or Vyond?

These options can reduce the time to create animation but they come with restrictions. You can only change what the application allows you to change. The other disadvantage is that seeing the same characters and gestures over and over again in different courses can dramatically reduce engagement.

For some, the cartoonish style of the animation is a no-go from the beginning. You can also use animation creatively. For example, they can show the consequences of your decisions in a branching design.


After reading this article you may feel like there is no silver bullet for learner engagement. There isn’t. None of the discussed approaches would work for all learning problems, all projects, and everywhere. Clark Quinn's new book, MAKE IT MEANINGFUL: Taking Learning Design From Instructional to Transformational, may offer more actionable insights on the fundamental problem: whatever you design, it must be meaningful for the audience. Otherwise, it doesn't matter what approach you take. The approaches discussed in this three-piece series are tools and techniques you can use in combination, to cook up the best meal:

  • Like a good chef, you need to use the right ingredients, at the right time, in the right recipe. For that, you need to have a variety of tools and techniques, a pinch of creativity, and loads of evidence-based science.
  • You need to start cooking! You can’t watch a video or listen to a podcast and not cook. Start with what you have now, and iterate.
  • Measure. Evaluate. Data insights for your specific project trump any theoretical debate about what works and what doesn't. (While correlation is not causation, correlations over and over again are a pretty good indicator of success.)

Final Thought: Measurement

What gets measured, gets done. What gets measured, gets designed for. Measuring vanity metrics like the number of completions, time spent in training, satisfaction, etc., will make you design your learning differently than measuring the application, the learning transfer, and eventually, the business impact.

Learning is not the end goal. Doing is. Learning means change. And change is hard when you have other priorities competing for time and focus. Therefore, don’t waste your audience’s time.


  1. Work backward from business goals/performance gaps, beliefs, etc.
  2. Identify the desired behaviors (actions, decisions, beliefs, etc.) and their real barriers. Don’t take for granted what leadership and management say.
  3. Be proactive and consultative. Don’t wait until someone comes to you with a training need. It will be way too late to do anything other than satisfying someone’s project plan with a "deliverable" they forgot to tell you about months before.
  4. Address learning problems and opportunities with learning.
  5. If you do decide that learning is the solution, focus on decision-making and task competence, not knowledge recall or content reading exercises.
  6. Create authentic scenarios that match both the expectations on the job for the role and also the skills level of the audience. Scaffold the learning: novice learners need more guidance, experts need more autonomy.
  7. Use the combination of techniques discussed to design relevant, challenging, and meaningful learning experiences that focus on the application of learning on the job (learning transfer).

P.S. What Questions Do You Still Have About Engagement And Motivation?

One of my unanswered questions is about the role of self-efficacy. If you want to explore motivation further, I suggest learning about the expectancy-value theory (EVT):

Motivation is affected by several factors, including reinforcement for behavior, but especially also students’ goals, interests, and sense of self-efficacy and self-determination. The factors combine to create two general sources of motivation: students’ expectations of success and the value that students place on a goal. Viewing motivation in this way is often called the expectancy-value model of motivation.


[1] Why Games?

[2] Ramifications Of Gamification In Learning

[3] Does Humor Enhance Learning?

[4] Top 7 reasons why you should develop and deploy learning nuggets (bite-sized learning) in eLearning

[5] Brain-Based Learning Theory: An Online Course Design Model

[6] Perry, Bruce D., M.D., Ph.D. 2004. “How the Brain Learns Best.” Instructor Magazine.

[7] Brain-Based Bullocks

[8] When learning from animations is more successful than learning from static pictures: learning the specifics of change

Further Reading;

This article is the third of a three-part series exploring questions related to learning, engagement, and ways to increase learner engagement. You can read the first article of the series here and the second article here