The spacing effect, if not the most studied learning factor, is certainly in the top five. As Harry Bahrick and Lynda Hall said in 2005, “The spacing effect is one of the oldest and best documented phenomena in the history of learning and memory research.”

The spacing effect is the finding that repetitions that are spaced over time produce better long-term remembering than the exact same repetitions spaced over a shorter amount of time or massed all together.

About 10 new scientific studies are carried out each year on the spacing effect (I counted 31 in the last three years). Why such frenzied dedication to exploring the spacing effect? Scientists want to know what causes it! It’s really rather fascinating!

To prepare for my upcoming conference presentation at the UK Learning Technologies conference (my presentation is now available on YouTube by clicking here), where they’ve asked me to speak on the spacing effect as it relates to mobile learning and microlearning, I’m doing another review of the scientific research. Here, on my blog, I’ll share tidbits of my translational research effort, especially when I find articles that are particularly interesting or informative.

In this post, I’m looking at Geoffrey Maddox’s review of the spacing research, which was published just last year in 2016 and is the most recent review available (although given the interest in spacing, there are many reviews in the scientific literature). He does a spectacular job making sense of the many strands of research.

In it, he finds that there are six main theories for why the spacing effect occurs. I’ve simplified his list into five theoretical explanations and I’ve ignored his somewhat jargony labels to help normal folks like me and you grok the meaning.

Five Theoretical Explanations for the Spacing Effect

  1. Spacing Prompts More Attention
    Learners may exert more attention to spaced items (compared with massed items).
  2. Spacing Prompts Retrieval
    Learners may be forced to retrieve spaced items (compared with massed items that need no retrieval—because they are still top of mind).
  3. Spacing Prompts More-Difficult Retrieval
    Learners may be prompted to engage in more difficult retrieval of spaced items (compared with massed items) and longer-spaced items (compared with shorter-spaced items).
  4. Spacing Involves More Contextual Variability
    Learners may create more retrieval routes (or more varied retrieval routes) when prompted with spaced items (compared with massed items).
  5. Spacing Prompts Retrieval and Variability
    Spacing benefits learners through both retrieval and variability, but variability, because it induces weaker traces may lead to more retrieval failure, thus lowering retrieval rates when spaced intervals are too long.

Maddox concludes that the only one that even comes close to explaining all the phenomenon in the scientific literature on spacing is the last one, which is really a combination of #2 and #4.

Count me as a skeptic. I just think we may be asking too much to push ourselves toward a unifying theory of spacing at this point. While a ton of research has been done, there are so many aspects to spacing and so much more authentically realistic research left to do that we ought to hold off on tying a pretty bow around one theory or another.

Evidence supporting my skepticism was found in the very next article that I read, where Metcalfe and Xu found more mind-wandering during massed practice than during spaced practice. This would fall into theory #1 above, not 5 (as Maddox recommended) or #2 or #4, which comprise 5.

Practical Implications

This article was not focused on providing practical implications, so it’s probably too much to ask of it. Nevertheless, it does show the complexity of spacing at a cognitive level.

Also, Maddox was pretty clear in describing how robust the scientific research is in terms of the spacing effect. He wrote, Because of its robustness, the spacing effect has the potential to be applied across a variety of contexts as a way of improving learning and memory.”

He also detailed the ways that the science of spacing is so strong, including the following:

  • The spacing effect is: “observed in different animal species,”
  • “across the human lifespan”
  • “with numerous experimental manipulations”
  • “observed with educationally relevant verbal materials”
  • “observed in the classroom”
  • and observed with memory impaired populations”

We as learning professionals can conclude that the spacing effect (1) is real, (2) that it applies to all human beings, (3) that it is relevant to most situations, (4) that it is a powerful learning factor, and (5) that we ought to be utilizing it in our learning designs!

So folks, as I wrote in 2006, we ought to be figure out ways to Space Learning Over Time, using spaced repetitions, perhaps in a subscription-learning format.

Research Cited:

Bahrick, H. P., & Hall, L. K. (2005). The importance of retrieval failures to long-term retention: A metacognitive explanation of the spacing effect. Journal of Memory and Language, 52, 566-577.

Maddox, G. B. (2016). Understanding the underlying mechanism of the spacing effect in verbal learning: A case for encoding variability and study-phase retrieval. Journal of Cognitive Psychology, 28(6), 684-706.

Metcalfe, J., & Xu, J. (2016). People mind wander more during massed than spaced inductive learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(6), 978-984.

Thalheimer, W. (2006, February). Spacing Learning Events Over Time: What the Research Says. Available at: http://work-learning.com/catalog.html.

As you know, if you’ve dabbled into my work for a few years, I’ve closely followed the research finding, “The Spacing Effect,” both from a research perspective and a practical perspective. Indeed, I was one of the first in the workplace learning field to recognize its practical significance, which I wrote about as early as 2002. In 2006 I published the research-to-practice report entitled Spacing Learning Over Time, which should — if there was justice in the world (LOL) or viable trade organizations (OUCH) — be enshrined in the Learning and Development Hall of Fame. Snickers are welcome. Taza Chocolate even better. A few years ago, still wanting to advocate for the practical use of the spacing effect, I began speaking about Subscription Learning at conferences and I developed a website (SubscriptionLearning.com) to encourage folks in the learning field to utilize the spacing effect in their learning designs. SubscriptionLearning.com is being retired in 2017, as it is no longer needed. Blog posts from the website are incorporated in this blog.

I am grateful to the enlightened organizations who have supported my work over the years and specifically to the individuals who continue to encourage the reading of the 2006 research report. Feel free to share yourself.

Now in 2017, I am grateful to another organization, Learning Technologies (in the UK) who is sponsoring me to speak on the spacing effect at their conference starting in a few weeks. As part of my efforts, I am developing a new presentation and I am updating my research compilation on the spacing effect. Stay tuned to this blog as I’m likely to share a few of my findings as I dig into the research.

Indeed, the research on spacing is some of the most interesting I’ve studied over the years. The first thing that fascinates is that there is so much damn research on the spacing effect, also referred to as spaced learning, distributed practice, and interleaving. In 1992, Bruce and Bahrick counted up the number of scientific studies on spacing and found over 300 articles at that time. Every year, there are more and more scientific articles published on spacing. By my rough count of journal articles cited on PsycINFO (a primary social-science database), over the last three years there have been 31 new articles published on the spacing effect (7 in 2014, 14 in 2015, and 10 in 2016).

One of the main reasons that so many research articles are published on the spacing effect is that the phenomenon is so intriguing. Why would spacing repetitions over time produce so much more remembering than giving the learners the exact same repetitions but simply massing them all at once or spacing them with less time in between? Freakin’ fascinating! So researchers keep digging into the complexities.

Harry Bahrick and Lynda Hall announced in 2005 that, “The spacing effect is one of the oldest and best documented phenomena in the history of learning and memory research.” And, just last year in a scientific review article, Geoffrey Maddox wrote, Because of its robustness, the spacing effect has the potential to be applied across a variety of contexts as a way of improving learning and memory.”

Stay tuned, as I hope to be be spacing my research compilations over time…

Research

Bahrick, H. P., & Hall, L. K. (2005). The importance of retrieval failures to long-term retention: A metacognitive explanation of the spacing effect. Journal of Memory and Language, 52, 566-577.

Maddox, G. B. (2016). Understanding the underlying mechanism of the spacing effect in verbal learning: A case for encoding variability and study-phase retrieval. Journal of Cognitive Psychology, 28(6), 684-706.

Thalheimer, W. (2006, February). Spacing Learning Events Over Time: What the Research Says. Available at: http://work-learning.com/catalog.html.

A 2003 meta-analysis found that fitness training was likely to improve cognitive functioning in older adults.

I'm reprising this because it is one of Psychological Science's most cited articles as recently as September 1, 2016.

Fitness and Aging

The researchers examined 18 scientific studies and 197 separate effect sizes. They categorized measures of cognitive functioning into four categories as depicted above in the graph, including:

  • Executive functioning (the ability to plan, schedule, and generally engage in high-level decision-making).
  • Controlled processing (the ability to engage in simple decision-making).
  • Visuospatial processing (the ability to transform visual or spatial information).
  • Speed processing (the ability to make quick reactions).

As you can see in the graph above, overall the groups that exercised outperformed those who didn't.

 

Some Details:

  • Results were stronger for people 66-80 than for those 55-65 (judged by effect size), although all groups showed significant benefits from exercise.
  • Exercise for less than 30 minutes produced very little benefit compared to exercise for 30-60 minutes.
  • Females seemed to get more benefits from exercising, but the way comparisons were made makes this conclusion somewhat sketchy.
  • Those who engaged in both weight-training and cardio-training had slightly better results than those who did cardio alone.

 

Research Citation:

Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychological Science, 14, 125-130.

 

More Information

Check out a 2009 blog post I wrote on aging and cognition, and test your knowledge with the quiz!!

Those of us in the learning professions are naturally enamored with the power of learning. This is all fine and good–learning is necessary for human survival and for our most enlightened achievements–but too narrow a focus on learning misses a key responsibility. Indeed, learning without sustained behavior change is like feeding a man who's planning to jump off a bridge. Nice, but largely besides the point. 

The bottom line is that we learning professionals must not only look to the science of learning, but also the science of behavior change.

My friend and colleague Julie Dirksen has been thinking about behavior change for years. Here's a recent article she wrote:

Here is another recent resource on behavior change:

It's good to keep this all in perspective. Science often moves slowly and in fits and starts. There is great promise in the many and varied research areas under study. You can see this most fully in the health-behavior-change field. There's a ton of research being done. Here's a quick list of research being done on behavior change:

  • Cardiac health
  • Obesity
  • Clean cooking
  • Asthma
  • HIV and STD prevention
  • College-student drinking
  • Cancer prevention
  • Child survival
  • Recycling
  • Use of hotel towels
  • Young-driver distraction
  • Hand washing
  • Encourage walking and cycling
  • Smoking cessation
  • Healthy pregnancy behaviors
  • Promoting physical activity

Okay, the list is almost endless.

One of the findings is not surprising. Lasting behavior change is very difficult. Think how hard it is to lose weight and keep it off, or stop an internet addition. So it's great that researchers are looking into this.

In the learning field, we have our own version of behavior-change research. It's called transfer. We've already learned a lot about how to get people to transfer what they've learned back to their jobs or into their lives. We're not done learning, of course.

One thing we do know is that training by itself is rarely sufficient to produce lasting change. Sometimes our learners will take what they've learned, put it immediately into practice, deepen their own learning and continue to learn and engage and use what they've learned over time. Too often, they forget, they get distracted, they get no support.

 

Summary

My four messages to you are these:

  1. Keep your eyes open for Behavior Change Research.
  2. Keep your eyes open for Transfer-of-Learning Research.
  3. Don't be a fool in thinking that training/learning is enough.
  4. We learning professionals have a responsibility to enable usable behavior change.

 

Dr. Karl Kapp is one of the learning field’s best research-to-practice gurus! Legendary for his generosity and indefatigable energy, it is my pleasure to interview him for his wisdom on games, gamification, and their intersection.

His books on games and gamification are wonderful. You can click on the images below to view them on Amazon.com.

 

 

The following is a master class on games and learning:

 

Will (Question 1):

Karl, you’ve written a definitive exploration of Gamification in your book, The Gamification of Learning and Instruction: Game-Based Methods and Strategies for Training and Education. As I read your book I was struck by your insistence that Gamification “is not the superficial addition of points, rewards, and badges to learning experiences.” What the heck are you talking about? Everybody knows that gamification is all about leaderboards, or so the marketplace would make us believe… [WINK, WINK] What are you getting at in your repeated warning that gamification is more complex than we might think?

Karl:

If you examine why people play games, the reasons are many, but often players talk about the sense of mastery, the enjoyment of overcoming a challenge, the thrill of winning and the joy of exploring the environment. They talk about how they moved from one level to another or how they encountered a “boss level” and defeated the boss after several attempts or how they strategized a certain way to accomplish the goal of winning the game. Or they describe how they allocated resources so they could defeat a difficult opponent. Rarely, if ever, do people who play games talk about the thrill of earning a point or the joy of being number seven on the leaderboard or the excitement of earning a badge just for showing up.

The elements of points, badges and leaderboards (PBLs) are the least exciting and enticing elements of playing games. So there is no way we should lead with those items when gamifying instruction. Sure PBLs play a role in making a game more understandable or in determining how far away a player is from the “best” but they do little to internally motivate players by themselves. Reliance solely on the PBL elements of games to drive learner engagement is not sustainable and not even what makes games motivational or engaging. It’s the wrong approach to learning and motivation. It’s superficial; it’s not deep enough to have lasting meaning.

Instead, we need to look at the more intrinsically motivating and deeper elements of games such as: challenge, mystery, story, constructive feedback (meaningful consequences) strategy, socialization and other elements that make games inherently engaging. We miss a large opportunity when we limit our “game thinking” to points, badges and leaderboards. We need to expand our thinking to include elements that truly engage a player and draw them into a game. These are the things that make games fun and frustrating and worth our investment in time.

 

Will (Question 2):

You wrote that “too many elements of reality and the game ceases to be engaging,”—and I’m probably taking this out of context—but I wonder if that is true in all cases? For example, I can imagine a realistic flight simulator for fighter pilots that creates an almost perfect replica of the cockpit, g-forces, and more, that would be highly engaging… On the other hand, my 13-year-daughter got me hooked on Tanki, an online tank shot-em-up game, and there are very few elements of reality in the game—and I, unfortunately, find it very engaging. Is it different for novices and experts? Are the recommendations for perceptual fidelity different for different topic areas, different learning goals, et cetera?

Karl:

A while ago, I read a fake advertisement for a military game. It was a parody. The fake game description described how the “ultra-realistic” military game would be hours of fun because it was just like actually being in the military. The description told the player that he or she would have hours of fun walking to the mess hall, maintaining equipment, getting gasoline for the jeep, washing boots, patrolling and zigging and cleaning latrines. Now none of these things are really fun, in fact, they are boring but they are part of the life of being in the military. Military games don’t include these mundane activities. Instead, you are always battling an enemy or strategizing what to do next. The actions that a military force performs 95% of the time are not included in the game because they are too boring.

 If games where 100% realistic, they would not be fun. So, instead, games are an abstraction of reality because they focus on things within reality that can be made engaging or interesting. If a game reflected reality 100%, there would be boring game play. Now certainly, games can be designed to “improve” reality and make it more fun. In the game, The Sims, you wake up, get dressed and go to work which all seems pretty mundane. However, these realistic activities in The Sims are an abstraction of the tasks you actually perform. The layer of abstraction makes the game more exciting, engaging and fun. But in either the military game case or The Sims, too much reality is not fun.

The flight simulator needs to be 100% realistic because it’s not really a game (although people do play it as a game) but the real purpose of a simulation is training and perfection of skills. A flight simulator can be fun for some people to “play” but in a 100% realistic simulator, if you don’t know what you are doing, it’s boring because you keep crashing. For someone who doesn’t know how to fly, like me. If you made a World War II air battle game which had 100% realistic controls for my airplane, it wouldn’t be fun. In game design, we need to balance elements of reality with the learning goal and the element of engagement.

For some people, a simulator can be highly engaging because the learner is performing the task she would do on the job. So there needs to be a balance in games and simulations to have the right amount of reality for the goals you are trying to achieve.

 

Will (Question 3):

In developing a learning game, what should come first, the game or the goals (of learning)?

Karl:

Learning goals must come first and must remain at the forefront of the game design process. Too often I see the mistake of a design team becoming too focused on games elements and losing site of the learning goals. In our field, we are paid to help people learn, not to entertain them. Learning first.

Having said that, you can’t ignore or treat the game elements as second class citizens, you can’t bolt-on a points system and think you have now developed a fun game—you haven’t. The best process involves simultaneously integrating game mechanics and learning elements. It’s tricky and not a lot of instructional designers have experience or training in this area but it’s critical to have integration of game and learning elements, the two need to be designed together. Neither can be an afterthought.

 

Will (Question 4):

Later we’ll talk about the research you’ve uncovered about the effectiveness of games. As I peruse the literature on games, the focus is mostly on the potential benefits of games. But what about drawbacks? I, for one, “waste” a ton of time playing games. Opportunity costs are certainly one issue, but maybe there are other drawbacks as well, including addiction to the endorphins and adrenaline; a heightened state of engagement during gaming that may make other aspects of living – or learning – seem less interesting, engaging. What about learning bad ideas, being desensitized to violence, sexual predation, or other anti-social behaviors? Are there downsides to games? And, in your opinion, has the research to date done enough to examine negative consequences of games?

Karl:

Yes, games can have horrible, anti-social content. They can also have wonderful, pro-social content. In fact, a growing area of game research focuses on possible pro-social aspects of games. The answer really is the content. A “game” per-say is neither pro- or anti-social like any other instructional medium. Look at speeches. Stalin gave speeches filled with horrible content and Martin Luther King, Jr. gave speeches filled with inspiring content. Yet we never seem to ask the question “Are speeches inherently good or bad?”

Games, like other instructional media, have caveats that good instructional designers need to factor when deciding if a game is the right instructional intervention. Certainly time is a big factor. It takes time to both develop a game and to play a game. So this is a huge downside. You need to weigh the impact you think the game will have on learner retention or knowledge versus another instructional intervention. Although, I can tell you there are at least two meta-analysis studies that indicate that games are more effective for learning than traditional, lecture-based instruction. But the point is not to blindly choose game over lecture or discussion. The decision regarding the right instructional design needs to be thoughtful. Knowing the caveats should factor into the final design decision.

Another caveat is that games should not be “stand-alone.” It’s far better for a learning game to be included as part of a larger curriculum rather than developed without any sense of how it fits into the larger pictures. Designers need to make sure they don’t lose site of the learning objective. If you are considering deploying a game within your organization, you have to make sure it’s appropriate for your culture. Another big factor to consider is how the losers are handled in the game. If a person is not successful at a game, what are the repercussions? What if she gets mad and shuts down? What if he walks away halfway through the experience because he is so frustrated? These types of contingencies need to be considered when developing a game. So, yes, there are downsides to games as there are downsides to other types of instruction. Our job, as instructional designers, is to understand as many downsides and upsides as possible for many different design possibilities and make an informed, evidence-based decision.

 

Will (Question 5):

As you found in your research review, feedback is a critical element in gaming. I’ve anointed “feedback” as one of the most important learning factors in my Decisive Dozen – as feedback is critical in all learning. The feedback research doesn’t seem definitive in recommending immediate versus delayed feedback, but the wisdom I take from the research suggests that delayed feedback is beneficial in supporting long-term remembering, whereas immediate feedback is beneficial in helping people “get” or comprehend key learning points or contingencies. In some sense, learners have to build correct mental models before they can (or should) reinforce those understandings through repetitions, reinforcement, and retrieval practice.

Am I right that most games provide immediate feedback? If not, when is immediate feedback common in games, when is delayed feedback common? What missed opportunities are there in feedback design?

Karl:

You are right; most games provide immediate, corrective feedback. You know right-away if you are performing the right action and, if not, the consequences of performing the wrong action. A number of games also provide delayed feedback in the form of after-action reviews. These are often seen in games using branching. At the end of the game, the player is given a description of choices she made versus the correct choices. So, delayed feedback is common in some types of games. In terms of what is missing in terms of feedback, I think that most learning games do a poor job of layering feedback. In well-designed video games, at the first level of help, a player can receive a vague clue. If this doesn’t work or too much time passes, the game provides a more explicit clue and finally, if that doesn’t work, the player receives step-by-step instructions. Most learning games are too blunt. They tend to give the player the answer right away rather than layers choices or escalating the help. I think that is a huge missed opportunity.

 

Will (Question 6):

By the way, your book does a really nice job in describing the complexity and subtlety of feedback, including Robin Hunicke’s formulation for what makes feedback “juicy.” What subtleties around feedback do most of us instructional designers or instructors tend to miss?

Karl:

Our feedback in learning games and even elearning modules is just too blunt. We need more subtlety. Hunicke describes the need for feedback to have many different attributes including the need for the feedback to be tactile and coherent. She refers to tactile feedback as creating an experience where the player can feel the feedback as it is occurring on screen so that it’s not forced or unnatural within the game play. Instructional designers typically don’t create feedback the player or learner feels, typically, they create feedback that is “in your face” such as “Nice job!” or “Sorry, try again.” She describes coherent feedback as feedback that stays within the context of the game. It is congruent with on screen actions and activities as well as with the storyline unfolding as the interactions occur. Our learning games seem to fail at including both of these elements in our feedback. In general, our field needs to focus on feedback that is more naturally occurring and within the flow of the learning.

 

Will (Question 7):

Do learners have to enjoy the game to learn from it? What are the benefits of game pleasure? Are there drawbacks at all?

Karl:

Actually, research by Tracy Sitzmann indicates (2011) that a learner doesn’t have to indicate that he or she was “entertained” to learn from a serious game. So fun should not be the standard by which we measure the success of game. Instead, she found that what makes a game effective for learning is the level of engagement. Engagement should be the goal when designing a learning game. However, there are a number of studies that indicate that games are motivational. Although, one meta-analysis on games indicated that motivation was not a factor. So, I am not sure if pleasure is a necessary factor for learning. Instead, I tend to focus more on building engagement and having learners make meaningful decisions and less on learner enjoyment and fun. This tends to run counter to why most people want a learning game but the reason we should want learning games is to encourage engagement and higher order thinking and not to simply make boring learning fun. Engagement, mastery and tough decision making might not always be fun but, as you indicated in your questions about simulations, it can be engaging and learning results from engagement and then understanding the consequences of actions taken during that engagement.

 

Will (Question 8):

As I was perusing research on games, one of my surprises was that games seemed to be used for health-behavior change at least as much as learning. What they heck’s going on?

Karl:

Games are great tools for promoting health. We all know that we should focus on health and wellness but we often let other life elements get in the way. Making staying healthy a game provides, in many cases that little bit of extra motivation to make you stay on course. I think games for health work so well because they capitalize on our already existing knowledge that we need to stay healthy and then provide tracking of progress, earning of points and other incentives to help us give that extra boost that makes us take the extra 100 steps needed to get our 10,000 for the day. Ironically, I find games used in many life and death situations.

 

Will (Question 9):

In your book you have a whole chapter devoted to research on games. I really like your review. Of course, with all the recent research, maybe we’ve learned even more. Indeed, I just did a search of PsycINFO (a database of scientific research in the social sciences). When I searched for “games” in the title, I found 110 articles in peer-reviewed journals in this year (2016) alone. That’s a ton of research on games!!

Let’s start with the finding in your book that the research methodology of much of the research is not very rigorous. You found that concern from more than one reviewer. Is that still true today (in 2016)? If the research base is not yet solid, what does that mean for us as practitioners? Should we trust the research results or should we be highly skeptical — OR, where in-between these extremes should we be?

Karl:

The short answer, as with any body of research, is to be skeptical but not paralyzed. Waiting for the definitive decision on games is a continually evolving process. Research results are rarely a definitive answer; they only give us guidance. I am sure you remember when “research” indicated that eggs were horrible for you and then “research” revealed that eggs were the ultimate health food. We need to know that research evolves and is not static. And, we need to keep in mind that some research indicated that smoking had health benefits so I am always somewhat skeptical. Having said that, I don’t let skepticism stop me from doing something. If the research seems to be pointing in a direction but I don’t have all the answers, I’ll still “try it out” to see for myself.

That said the research on games, even research done today, could be much more rigorous. There are many flaws which include small sample sizes, no universal definition of games and too much focus on comparing the outcomes of games with the outcomes of traditional instruction. One would think that argument would be pretty much over but decade after decade we continue to compare “traditional instruction” with radio, television, games and now mobile devices. After decades of research the findings are almost always the same. Good design, regardless of the delivery medium, is the most crucial aspect for learning. Where the research really needs to go, and it’s starting to go in that direction, is toward comparing elements of games to see which elements lead to the most effective and deep learning outcomes. So, for example, is the use of a narrative more effective in a learning game than the use of a leaderboard or is the use of characters more critical for learning than the use of a strategy-based design? I think the blanket comparisons are bad and, in many cases, misleading. For example, Tic-Tac-Toe is a game but so is Assassin’s Creed IV. So to say that all games teach pattern recognition because Tic-Tac-Toe teaches pattern recognition is not good. As Clark Aldrich stated years ago, the research community needs some sort of taxonomy to help identify different genres of games and then research into the learning impact of those genres.

So, I am always skeptical of game research and try to carefully describe limitations of the research I conduct and to carefully review research that has been conducted by others. I tend to like meta-analysis studies which are one method of looking at the body of research in the field and then drawing conclusions but even those aren’t perfect as you have arguments about what studies were included and what studies were not included.

At this point I think we have some general guidelines about the use of games in learning. We know that games are most effective in a curriculum when they are introduced and described to the learners, then the learners play the game and then there is a debrief. I would like to focus more on what we know from the research on games and how to implement games effectively rather than the continuous, and in my opinion, pointless comparison of games to traditional instruction. Let’s just focus on what works when games do provide positive learning outcomes.

 

Will (Question 10):

A recent review of serious games (Tsekleves, Cosmas, & Aggoun, 2014, 2016) concluded that their benefits were still not fully supported. “Despite the increased use of computer games and serious games in education, there are still very few empirical studies with conclusive results on the effectiveness of serious games in education.” This seems a bit strong given other findings from recent meta-analyses, for example the moderate effect sizes found in a meta-analysis from Wouters, van Nimwegen, van Oostendorp, & van der Spek (2013).

Can you give us a sense of the research? Are serious games generally better, sometimes better, or rarely better than conventional instruction? Or, are they better in some circumstance, for some learners, for some topics – rather than others? How should us practitioners think about the research findings?

Karl:

Wouters et al. (2013) found that games are more effective than traditional instruction as did Stizmann (2011). But, as you indicated, other meta-analysis studies have not come to that conclusion. So, again, I think the real issue is that the term “games” is way too broad for easy comparisons and we need to focus more on the elements of games and how the individual elements intermingle and combine to cause learning to occur. One major problem with research in the field of games is that to conduct effective and definitive research we often want to isolate one variable and then keep all other variables that same. That processes is extremely difficult to do with games. New research methods might need to be invented to effectively discover how game variables interact with one another. I even saw an article that declared that all games are situational learning and should be studied in that context rather than in an experimental context. I don’t know the answer but there are few simple solutions to game-based research and definitive declarations of the effectiveness of games.

However, having said all that, here are some things we do know from the research related to using games for learning:

  • Games should be embedded in instructional programs. The best learning outcomes from using a game in the classroom occur when a three-step embedding process is followed. The teacher should first introduce the game and explain its learning objectives to the students. Then the students play the game. Finally, after the game is played, the teacher and students should debrief one another on what was learned and how the events of the game support the instructional objectives. This process helps ensure that learning occurs from playing the game (Hays, 2005; Sitzmann, 2011).
  • Ensure game objectives align with curriculum objectives. Ke (2009) found that the learning outcomes achieved through computer games depend largely on how educators align learning (i.e., learning subject areas and learning purposes), learner characteristics, and game-based pedagogy with the design of an instructional game. In other words, if the game objectives match the curriculum objectives, disjunctions are avoided between the game design and curricular goals (Schifter, 2013). The more closely aligned curriculum goals and game goals, the more likely the learning outcomes of the game will match the desired learning outcomes of the student.
  • Games need to include instructional support. In games without instructional support such as elaborative feedback, pedagogical agents, and multimodal information presentations (Hays, 2005; Ke, 2009; Wouters et al., 2013)., students tend to learn how to play the game rather than learn domain-specific knowledge embedded in the game. Instructional support that helps learners understand how to use the game increases the effectiveness of the game by enabling learners to focus on its content rather than its operational rules.
  • Games do not need to be perceived as being “entertaining” to be educationally effective. Although we may hope that Maria finds the game entertaining, research indicates that a student does not need to perceive a game as entertaining to still receive learning benefits. In a meta-analysis of 65 game studies, Sitzmann (2011) found that although “most simulation game models and review articles propose that the entertainment value of the instruction is a key feature that influences instructional effectiveness, entertainment is not a prerequisite for learning,” that entertainment value did not impact learning (see also Garris et al., 2002; Tennyson & Jorczak, 2008; Wilson et al., 2009). Furthermore, what is entertaining to one student may not be entertaining to another. The fundamental criterion in selecting or creating a game should be the learner’s actively engagement with the content rather than simply being entertained (Dondling, 2007; Sitzmann, 2011).

 

Will (Question 11):

If the research results are still tentative, or are only strong in certain areas, how should we as learning designers think about serious games? Is there overall advice you would recommend?

Karl:

First of all, I’d like to point to the research that exists indicating that lectures are not as effective for learning as some believe. So practitioners, faculty members and others have defaulted to lectures and held them up as the “holy grail” of learning experiences when the literature clearly doesn’t back up the use of lectures as the best method for teaching higher level thinking skills. If one wants to be skeptical of learning designs, start with the lecture.

Second, I think the guidelines outlined above are a good start. We are literally learning more all the time so keep checking to see the latest. I try to publish research on my blog (karlkapp.com) and at the ATD Science of Learning blog and, of course, the Will at Work blog for all things learning research are good places to look.

Third, we need to take more chances. Don’t be paralyzed waiting for research to tell you what to do. Try something, if you fail, try something else. Sure you can spend your career creating safe PowerPoint-based slide shows where you hit next to continue but that doesn’t really move your career or the field forward. Take what is known from reading books and from vetted and trusted internet sources and make professionally informed decisions.

 

Will (Question 12):

Finally, if we decide to go ahead and develop or purchase a serious game, what are the five most important things people should know?

Karl:

  1. First clearly define your goals. Why are you designing or purchasing a serious game and what do you expect as the outcome? After the learners play the game what should they be able to do? How should they think? What result do you desire? Without a clearly defined outcome, you will run into problems.
  2. Determine how the game fits into your overall learning curriculum. Games should not be stand-alone; they really should be an integral part of a larger instructional plan. Determine where the serious game fits into the bigger picture.
  3. Consider your corporate culture. So cultures will allow a fanciful game with zombies or strange characters and some will not. Know what your culture will tolerate in terms of game look and feel and then work within those parameters.
  4. If the game is electronic, get your information technology (IT) folks involved early. You’ll need to look at things like download speed, access, browser compatibility and a host of other technical issues that you need to consider.
  5. Think carefully and deeply before you decide to develop a game internally. Developing good, effective serious games is tough. It’s not a two-week project. Partner with a vendor to obtain the desired result.
  6. (A bonus) Don’t neglect the power of card games or board games for teaching. If you have the opportunity to bring learners together, consider low-tech game solutions. Sometimes those are the most impactful.

 

Will (Question 13):

One of your key pieces of advice is for folks to play games to learn about their power and potential. What kind of games should we choose to play? How should we prioritize our game playing? What kind of games should we avoid because they’ll just be a waste of time or might give us bad ideas about games for learning?

Karl:

I think you should play all types of games. First, pick different types of games from a delivery perspective so pick some card games, board games, causal games on your smartphone and video games on a game console. Mix it up. Then play different types of games such as role-play games, cooperative games, matching games, racing games, games where you collect items (like Pokémon Go). The trick is to not just play games that you like but to play a variety of games. You want to build a “vocabulary” of game knowledge. Once you’ve built a vocabulary, you will have a formidable knowledge base on which to draw when you want to create a new learning game.

Also, you can’t just play the games. You need to play and critically evaluate the games. Pay attention to what is engaging about the game, what is confusing, how the rules are crafted, what game mechanics are being employed, etc.? Play games with a critical eye. Of course, you will run the danger of ruining the fun of games because you will dissect any game you are playing to determine what about the game is good and what is bad but, that’s ok, you need that skill to help you design games. You want to think like a game designer because when you create a serious game, you are a game designer. Therefore, the greater the variety of game you the play and dissect, the better game designer you will become.

 

Will (Question 14):

If folks are interested, where can they get your book?

Karl:

Amazon.com is a great place to purchase my book or at the ATD web site. Also, if people have access to Lynda.com, I have several courses on Lynda including “The Gamification of Learning”. And I have a new book coming out in January co-authored by my friend Sharon Boller called “Play to Learn” where we walk readers through the entire serious game design process from conceptualization to implementation. We are really excited about that book because we think it will be very helpful for people who want to create learning games.

 

You can click on the images below to view Karl’s Gamification books on Amazon.com.

 

 

 

 

Research

Sitzmann, T. (2011). A meta-analytic examination of the instructional effectiveness of computer-based simulation games. Personnel Psychology, 64(2), 489–528.

Tsekleves, E., Cosmas, J., & Aggoun, A. (2016). Benefits, barriers and guideline recommendations for the implementation of serious games in education for stakeholders and policymakers. British Journal of Educational Technology, 47(1), 164-183. Available at: http://onlinelibrary.wiley.com/doi/10.1111/bjet.12223/pdf

Wouters, P., van Nimwegen, C., van Oostendorp, H., & van der Spek, E. D. (2013). A meta-analysis of the cognitive and motivational effects of serious games. Journal of Educational Psychology, 105(2), 249-265. http://dx.doi.org/10.1037/a0031311

This post is for research geeks, and it's really just an introduction — maybe a gentle warning — as I don't have time or the statistical expertise to explore this deeply.

 

The Basics

When scientific experiments get done, researchers typically compare one experimental treatment to second one (or to no-treatment at all). So for example, we might compare two versions of the same elearning program, one that utilizes spaced repetitions and a second that uses unspaced repetitions. When we do such comparisons we need to know two things before we can draw conclusions:

  1. Statistical Significance:
    How likely is it that the experimental results might be caused by random chance. Social scientists aim for results that are more than 95% likely to result from the experimental factors being studied. In other words, if we did the same experiment 100 times, we should expect the same outcome at least 95% of the time.
  2. Effect Size:
    How different are the actual results. Are they sufficiently large to be meaningful?

If we don't take effect sizes into account, we can have an experiment that is statistically significant but not practically significant. That is, we can have statistical significance, but not effect-size significance. Without looking at effect-size calculations, we can be fooled into thinking that an experimental result is meaningful when it actually shows no substantial advantage for one learning method compared with another.

So for example, suppose that a new mobile-learning app improves learning by less than one-half of one percent, but cost $10,000 per learner…

Meta-analyses are statistical studies that compile many scientific studies, looking at the whole of the results. Meta-analyses have been a potent source of wisdom because they take complicated and complex results over a range of studies and combine them in a way that helps us make sense of the overall trends. Meta-analyses rely on effect sizes to calculate the overall importance of the factors being studied.

 

Some Subtleties

As with all things in science, over time scientists make improvement and refinements in their work. Effect sizes are no different. Recently, researchers have found that meta-analyses have to be interpreted with wisdom, otherwise the results may not be what they seem. Of specific concern is the finding that published studies tend to report higher effect sizes than unpublished studies. Quasi-experimental designs reported higher effect sizes than randomized control studies. Et cetera…

Here are some recommendations for researchers from Cheung and Slavin (2016), who are focused on educational research, but whose recommendations are widely applicable:

  • In doing a meta-analysis, don't just look at published studies. Moreover, work diligently to gather all studies that have been done.
  • Researchers, in general, should utilize randomized trials whenever possible. Those doing meta-analyses should look at these separately because they are likely to have the least-biased data.
  • Policy makers and educators (and I, Will Thalheimer, would add all workplace learning professionals) should "insist on large, randomized evaluations to validate promising programs."

 

Some Research Articles of Relevance

Cheung, A. C. K. & Slavin, R. E. (2016). How methodological features affect effect sizes in education. Educational Researcher, 45(5), 283-292.
 
Ueno, T., Fastrich, G. M., & Murayama, K. (2016). Meta-analysis to integrate effect sizes within an article: Possible misuse and Type I error inflation. Journal of Experimental Psychology: General, 145(5), 643-654. http://dx.doi.org/10.1037/xge0000159
 
van Assen, M. A. L. M., van Aert, R. C. M., & Wicherts, J. M. (2015). Meta-analysis using effect size distributions of only statistically significant studies. Psychological Methods, 20(3), 293-309. http://dx.doi.org/10.1037/met0000025

The journal Nature reported today that a new map of the brain reveals 97 newly-found regions, each specialized to certain functions.

In an article, entitled, "A multi-modal parcellation of human cerebral cortex," the 12 scientists found 97 new structures and validated the "83 areas previously reported using post-mortem microscopy," bringing the total structures per hemisphere to 180.

New Brain Map

As the scientists declare, such a map is critical to neuroscientists in evaluating neurological functioning.

"Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience."

As should be obvious, we are still in the infancy of neuroscience. Any recommendations about learning — supposedly based on neuroscience, should be taken with extreme skepticism. See related article.

For nice review of the findings, see article in the New York Times.

 

New research just published (July 11, 2016) shows that the blood-glucose hypothesis about willpower is probably not true, at least not as evidenced by current scientific studies.

The idea — previously held — was that blood glucose mediated the propensity of people to exert willpower, with decreased blood glucose making it less likely that someone would persevere in a task.

Bigstock-Group-of-business-people-Busi-14495489

I myself had read some of the previous research and shared the blood-glucose hypothesis. Apparently, current research doesn't back up this claim. Miguel A. Vadillo, Natalie Gold, and Magda Osman — writing in the journal Psychological Science, utilized a "new meta-analytic tool, p-curve analysis, to examine the reliability of the evidence from" 19 studies focusing on blood glucose and willpower. They found that overall there was not a reliable effect of glucose.

Here are two quotes from the article:

The findings from the present study are a surprise in the context of the wide acceptance of the glucose hypothesis in general scientific research and its popularity, as evidenced by the number of citations of Gailliot et al. (2007) in the literature and the continued influence of this hypothesis in recent reviews on ego depletion (e.g., Baumeister, 2014; Baumeister & Alghamdi, 2015). Moreover, the hypothesis has intuitive and seemingly practical appeal. If one accepts that a failure of self-control in regulating actions contributes to the many personal and societal problems that people face (Baumeister et al., 2000), then glucose supplements would provide a simple means to enhance willpower and ameliorate these problems (Baumeister & Tierny, 2011). In light of our results, it is doubtful that such a recommendation will work in the real world. This conclusion converges with recent evidence that glucose might have little or no impact on domain-general decision-making tasks (Orquin & Kurzban, 2016) and with an intriguing series of meta-analyses and preregistered replications suggesting that the ego-depletion effect itself might be less robust than previously thought (Carter, Kofler, Forster, & McCullough, 2015; Hagger et al., in press).

Our results suggest that, on average, these studies have little or no evidential value, but they do not allow us to determine whether the significant results are due to publication bias, selective reporting of outcomes or analyses, p-hacking, or all of these. It is not impossible that some of these studies are exploring small but true effects and that their evidential value may be diluted by the biases that pervade the rest of the studies. Perhaps future research will show that glucose does play a role in ego depletion effects, but our conclusions are based on the analysis of the extant literature in this area. Thus, our contribution must be seen as an additional piece of information in the wider context of attempts to verify the reliability of the glucose model of ego depletion.

 

Practical Ramifications

In the past, I used the glucose-depletion idea as a partial explanation why day-long training sessions were difficult for learners. I also used it as a rationale for plying my workshop participants with treats in the afternoon. Well, at least I tried to make them somewhat healthy! As the meta-analysis above reveals, it's likely that some other mechanism is involved in the difficulties learners have during intensive learning sessions. As trainers and instructional designers, we still have to figure out a way to support learners during long learning sessions to prevent attention-zapping fatigue…

 

Research Reviewed

Vadillo, M. A., Gold, N., and Osman, M. (2016). The bitter truth about sugar and willpower: The limited evidential value of the glucose model of ego depletion. Psychological Science, Published Online July 11, 2016. Available at: http://pss.sagepub.com/content/early/2016/07/08/0956797616654911.full

 

For millennium, scholars and thinkers of all sorts — from scientists to men or women on the street — thought that memories simply faded with time.

Locke said:

"The memory of some men, it is true, is very tenacious, even to a miracle; but yet there seems to be a constant decay of all our ideas, even of those which are struck deepest, and in the minds of the most retentive; so that if they be not sometimes renewed by repeated exercise of the senses, or reflection on those kinds of objects which at first occasioned them, the print wears out, and at last there remains nothing to be seen."  John Locke quoted by William James in Principles of Psychology (p. 445, the 1952 Great Books edition, original 1891).

However, in the mid 1900's research by McGeoch (1932), Underwood (1957) and others found that memories can fade when what is learned interferes with other things learned. Previous things learned can interfere with current learning (proactive interference) and current learning can be interfered with by subsequent learning (retroactive interference).

The debate between decay and interference went on for over a century! Indeed, it paralleled the debate in physics over the property of light. Is it a wave or a particle?

The first ever photograph of light as both a particle and wave

In physics, the debate was so important that Albert Einstein won the Nobel Prize for the solution. Einstein's solution was simple. Light was BOTH a wave and a particle. The picture above is reported by Phys.org to be the first photograph demonstrating light's dual properties.

Now in the psychological research, we have the first experimental evidence that forgetting may be caused by BOTH decay and interference.

In a clever experiment, published just this month, Talya Sadeh, Jason Ozubko, Gordon Winocur, and Morris Moscovitch found evidence for both interference and decay.

Their research appears to be inspired, at least partially, by neuroscience findings. Here's what the authors say:

"Two approaches have guided current thinking regarding the functional distinction between hippocampal and extrahippocampal memories. The first approach maintains that the hippocampus supports a mnemonic process termed recollection, whereas extrahippocampal structures, especially the perirhinal cortex, support a process termed familiarity… Recollection is a mnemonic process that involves reinstatement of memory traces within the context in which they were formed. Familiarity is a mnemonic process that manifests itself in the feeling that a studied item has been experienced, but without reinstating the original context." (p. 2)

To be clear, this was NOT a neuroscience experiment. They did not measure brain activity in any way. They measured behavioral findings only.

In their experiment, they had people engage in a word-recognition task and then gave them either (1) another word-learning task, (2) a short music task, or (3) a long music task. The first group's word-learning task was designed to create the most interference. The longer music task was designed to create the most decay (because it took longer).

The results of the experiment were consistent with the researcher's hypotheses. They claimed to have found evidence for both decay and interference.

Caveats

Every scientific experiment has caveats. Usually these are pointed out by the researchers themselves. Often, it takes an outside set of eyes to provide caveats.

Did the researchers prove, beyond the shadow of a doubt, that forgetting has two causes? Short answer: No! Did they produce some interesting findings? Maybe!

My big worry from a research-design perspective is that their manipulation distinguishing between recollection and familiarity is somewhat dubious, seemingly splitting hairs in the questions they ask the learners. My big worry from a practical learning-design perspective is that they are using words as learning materials. First, most important learning situations utilize more complicated materials. Second, words are associative by their very nature — thus more likely to react to interference than typical learning materials. Third, the final "test" of learning was a recognition-memory task that involved learners determining whether they remembered seeing the words before — again, not very relevant to practical learning situations.

Practical Ramifications for Learning Professionals

Since there are potential experimental-design issues, particularly from a practical standpoint, it would be an extremely dubious enterprise to draw practical ramifications. Let me be dubious then (because it's fun, not because it's wise). If the researchers are correct, that memories that are context-based are less likely to be subject to interference effects; we might want to follow the general recommendation — often made today by research-focused learning experts — to provide learners with realistic practice using stimuli that have contextual relevance. In short, teach "if situation–then action" rather than teaching isolated concepts. Of course, we didn't need this experiment to tell us that. There is a ton of relevant research to back this up. For example, see The Decisive Dozen research review.

Beyond the experimental results, the concepts of delay and interference are intriguing in and of themselves. We know people tend to slide down a forgetting curve. Perhaps from interference, perhaps from decay. Indeed, as the authors say, "it is important to note that interference and decay are inherently confounded."

Research

The experiment:

Sadeh, T., Ozubko, J. D., Winocur, G., & Moscovitch. M. (2016) Forgetting patterns differentiate between two forms of memory representation. Psychological Science OnlineFirst, published on May 6, 2016 as doi:10.1177/0956797616638307.

The research review:

Sadeh, T., Ozubko, J. D., Winocur, G., & Moscovitch, M. (2014). How we forget may depend on how we remember. Trends in Cognitive Sciences, 18, 26–36.

 

 

In a recent research article, Tobias Wolbring and Patrick Riordan report the results of a study looking into the effects of instructor “beauty” on college course evaluations. What they found might surprise you — or worry you — depending on your views on vagaries of fairness in life.

Before I reveal the results, let me say that this is one study (two experiments), and that the findings were very weak in the sense that the effects were small.

Their first study used a large data set involving university students. Given that the data was previously collected through routine evaluation procedures, the researchers could not be sure of the quality of the actual teaching, nor the true “beauty” of the instructors (they had to rely on online images).

The second study was a laboratory study where they could precisely vary the level of beauty of the instructor and their gender, while keeping the actual instructional materials consistent. Unfortunately, “the instruction” consisted of an 11-minute audio lecture taught by relatively young instructors (young adults), so it’s not clear whether their results would generalize to more realistic instructional situations.

In both studies they relied on beauty as represented by facial beauty. While previous research shows that facial beauty is the primary way we rate each other on attractiveness, body beauty has also been found to have effects.

Their most compelling results:

1.

They found that ratings of attractiveness are very consistent across raters. People seem to know who is attractive and who is not. This confirms findings of many studies.

2.

Instructors who are more attractive, get better smile sheet ratings. Note that the effect was very small in both experiments. They confirmed what many other research studies have found, although their results were generally weaker than previous studies — probably due to the better controls utilized.

3.

They found that instructors who are better looking engender less absenteeism. That is, students were more likely to show up for class when their instructor was attractive.

4.

They found that it did not make a difference on the genders of the raters or instructors. It was hypothesized that female raters might respond differently to male and female instructors, and males would do the same. But this was not found. In previous studies there have been mixed results.

5.

In the second experiment, where they actually gave learners a test of what they’d learned, attractive instructors engendered higher scores on a difficult test, but not an easy test. The researchers hypothesize that learners engage more fully when their instructors are attractive.

6.

In the second experiment, they asked learners to either: (a) take a test first and then evaluate the course, or (b) do the evaluation first and then take the test. Did it matter? Yes! The researchers hypothesized that highly-attractive instructors would be penalized for giving a hard test more than their unattractive colleagues. This prediction was confirmed. When the difficult test came before the evaluation, better looking instructors were rated more poorly than less attractive instructors. Not much difference was found for the easy test.

Ramifications for Learning Professionals

First, let me caveat these thoughts with the reminder that this is just one study! Second, the study’s effects were relatively weak. Third, their results — even if valid — might not be relevant to your learners, your instructors, your organization, your situation, et cetera!

  1. If you’re a trainer, instructor, teacher, professor — get beautiful! Obviously, you can’t change your bone structure or symmetry, but you can do some things to make yourself more attractive. I drink raw spinach smoothies and climb telephone poles with my bare hands to strengthen my shoulders and give me that upside-down triangle attractiveness, while wearing the most expensive suits I can afford — $199 at Men’s Warehouse; all with the purpose of pushing myself above the threshold of … I can’t even say the word. You’ll have to find what works for you.
  2. If you refuse to sell your soul or put in time at the gym, you can always become a behind-the-scenes instructional designer or a research translator. As Clint said, “A man’s got to know his limitations.”
  3. Okay, I’ll be serious. We shouldn’t discount attractiveness entirely. It may make a small difference. On the other hand, we have more important, more leverageable actions we can take. I like the research-based findings that we all get judged primarily on two dimensions warmth/trust and competence. Be personable, authentically trustworthy, and work hard to do good work.
  4. The finding from the second experiment that better looking instructors might prompt more engagement and more learning — that I find intriguing. It may suggest, more generally, that the likability/attractiveness of our instructors or elearning narrators may be important in keeping our learners engaged. The research isn’t a slam dunk, but it may be suggestive.
  5. In terms of learning measurement, the results may suggest that evaluations come before difficult performance tests. I don’t know though how this relates to adults in workplace learning. They might be more thankful for instructional rigor if it helps them perform better in their jobs.
  6. More research is needed!

Research Reviewed

Wolbring, T., & Riordan, P. (2016). How beauty works. Theoretical mechanisms and two
empirical applications on students’ evaluation of teaching. Social Science Research, 57, 253-272.