Gamification, the use of game elements in non-game contexts, is increasingly being implemented in both student and organizational learning initiatives. Many of these efforts are atheoretical, meaning that the teachers using them don’t necessarily have a well-grounded reason for gamifying. Instead, they often gamify with the intention of making learning more “fun.”
Unfortunately, 1) not all gamification is fun and 2) fun is sometimes counterproductive. It is common belief by educators that I’ve spoken with that fun and learning are opposed – as you increase the fun of a learning activity, its impact on learning goes down.
Personally, that doesn’t make a lot of sense to me. Fun and learning should go hand in hand. It seems much more likely that the ways learning activities are being made fun are the problem – not the fun itself.
So if an instructor does want to gamify learning, what theories might be used to guide it? How can gamification be used that won’t potentially harm learning, fun or not?
Recent research by Landers, Bauer, Callan and Armstrong sheds some light on this question by exploring several psychological theories of learning in relation to gamification. Specifically, they identify categories of theories that speak to gamification.
- Theory of Gamified Learning. First, and perhaps most relevant, is the theory of gamified learning. This theory proposes that gamification can affect learning via one of two processes and is intended to guide decision-making when creating gamified activities. Critically to both, gamification should not be intended just to “get people to learn,” and gamification cannot replace high-quality instruction. Instead, it should be targeted at learner behavior and attitudes.
- Gamification can target a behavior or attitude that we already know affects learning. For example, we already know that students who spend more time engaging in meta-cognition (thinking about how they learn) tend to have higher grades. Thus, gamification might be used to increase meta-cognition (e.g., a mobile app might be used to reward students who “check in” to studying).
- Gamification can target a behavior or attitude that makes existing instruction more effective. We might have a great lesson plan to teach oceanography, but students might be bored. To increase their interest, we might bring in an interactive demonstration to illustrate key points. In such cases, the demonstration doesn’t actually teach anything new – it is a type of gamification intended to increase student engagement.
- Conditioning. Classical and operant conditioning are classic psychological theories of learning. Although they have been generally replaced and supplemented with many other theories over the years, they continue to explain a great deal of behavior, especially in children. The most successful type of psychological therapy, cognitive behavioral therapy, is even largely based upon operant conditioning principles (the “behavioral” part). At its core, conditioning is quite simple – the goal of the instructor is to create a positive association with a beneficial activity (like studying).
- Expectancy Theories. Expectancy theory is used to describe human motivation. It actually describes three separate motivational processes, listed below. Any particular learning activity can be described as the product of these three processes – if any of the three are low, there will be low motivation.
- Expectancy, which is how likely you believe your actions will lead to a consequence. For example, if I work hard, I’ll score high on the leaderboard.
- Instrumentality, which is how likely you believe that consequence will lead to a reward. For example, if I score high on the leaderboard, I’ll feel good about myself.
- Valence, which is the value you place on that reward. For example, feeling good about myself is very important.
In combination, we might conclude that a leaderboard is likely to be unsuccessful 1) if students don’t think their effort will lead to a high position on the leaderboard, and 2) if students don’t think that a high position on the leaderboard will lead to anything they want.
- Goal-Setting Theory. Goal-setting theory is one of the most well-supported theories of motivation in psychology, and it applies well to learning. People are motivated by SMART goals: specific, measurable, attainable, realistic, and time-bound. If you incorporate SMART goals in gamification, you are much more likely to get students to do what you want them to do.
- Self-Determination Theory. One of the more recent theories of motivation is self-determination theory, which posits that all humans are motivated by a drive to self-determine – to identify a path for themselves forward through life. This is done by meeting three needs: feeling competent in the tasks you attempt, feeling that you have accomplished those tasks without the influence of others, and feeling that your life is connected to those around you. SDT also defines two types of motivation: intrinsic, which refers to the motivation needs met by satisfaction of those three needs, and extrinsic, which is motivation that is not self-determined. Other-determined motivation is most often considered synonymous with incentives, like gold stars, grades, and recognition from others. Recent work in SDT has revealed that intrinsic and extrinsic motivations work together – that intrinsic motivation occurs when tasks have been internalized, whereas extrinsic motivators are most useful to get people to try new tasks. For example, a person being forced to play piano by a parent might hate it at first but do it anyone to make her parents happy, but later, as she becomes highly competent and autonomous playing, that playing becomes enjoyable on its own. Gamification can be used the same way, to introduce a person to something they don’t have any experience with or know they are good at so that they develop intrinsic motivation later.
Overall, no single theory is going to explain gamification or be the magic bullet for successful gamification. But these theories provide a strong foundation on which to build such efforts.Footnotes:
- Landers, R.N., Bauer, K.N., Callan, R.C., & Armstrong, M.B. (2015). Psychological theory and the gamification of learning Gamification in Education and Business, 165-186 [↩]
As is becoming a yearly tradition, the Society for Industrial and Organizational Psychology (SIOP) has released its list of anticipated top workplace trends for 2015 based upon a vote of the current SIOP membership. Here they are, with a little commentary:
- Changes in Laws May Affect Employment-Related Decisions. This has been a year of sweeping legal changes, most notably Obamacare and recreational marijuana. I guess drug tests don’t mean quite what they did last year.
- Growth of Corporate Social Responsibility (CSR) Programs. There is a growing expectation that organizations must “give back” to the community. This isn’t a new phenomenon, but is becoming more obvious as more Millennials enter the workforce. I know I wouldn’t work for an organization I thought was evil, no matter the salary.
- Changing Face of Diversity Initiatives. Appearing diverse just isn’t enough anymore – people know what a token hire looks like, and they don’t approve. Instead, diversity must be leveraged for an organizational good.
- Emphasis on Recruiting, Selecting for, and Retaining Potential (down from #3 in 2014). In good economies, people like to jump ship, and things are looking pretty good these days. As the effects of the Great Recession continues to dissipate, personnel (industrial) psychologists will be in increasingly high demand; we identify where to look for new talent, how to hire them, and how to keep them.
- Increased Need to Manage a Multi-Generational Workforce. GenX, GenY, Boomers and Silents are all at work now, and GenY just keeps getting bigger. The traditional approach to generational differences (i.e., the older folks lament how useless the new folks are, while the new folks grin and bear it until they’re in control) doesn’t work so well anymore. If your GenY employees don’t like your management, they’re happy to just leave and find a new place to work, finding startups especially attractive. Things are getting complicated.
- Organizations Will Continue to “Do More with Less” (down from #2 in 2014). No surprise here. Bad economies force belt-tightening, and then upper management realizes that belt can stay tight to squeeze even more profit out of the company.
- Increasing Implications of Technology for How Work is Performed (up from #6, #8 and #9 in 2014). Once again, my lab’s specialty gets a prominent place on the list. The Internet of Things, social media, and wearable tech continue to creep into our work lives.
- Integration of Work and Non-Work Life (up from #7 in 2014). Closely related to the item above, technology has made us so connected at all times that it’s difficult to disengage. Is this me writing a blog post at 10PM? Why yes, it is.
- Continued Use of HR Analytics and Big Data (down from #1 in 2014). Big Data is a tricky topic for I/Os, because a lot of I/Os I’ve chatted with like to think that they’ve been doing Big Data for a long time. They haven’t. Big Data is the art and science of identifying, sorting, and analyzing massive sources of data. And I mean massive – a few hundred thousand cases is a bare minimum in my mind. Imagine sticking an RFID chip on every one of your employee’s badges and tracking their movements every day for a year. What might you do with that dataset? That’s Big Data – a little exploratory, a little computer programming, and a lot of potential.
- Mobile Assessments (up from #4 in 2014). The biggest trend this year will be mobile assessments (another of our research areas!). As people increasingly identify and apply for jobs on their phones, their experience is markedly different from that of a desktop or laptop computer. In some cases, they seem to end up with lower scores. The implications of this are only beginning to be understood.
So what else changed from 2014? First, gamification, previously #5 on the list, has dropped off completely. This is probably because gamification has proven to be quite faddish – lots of organizations adopted it without any clue why they were adopting it, and it didn’t do much. In Gartner’s terms, it’s now in the Trough of Disillusionment. But that just means we’re right at the point where reasonable applications of gamification will begin to be discovered. I know I’m doing my part.
Second, several tech-related items all got smushed into #4, which made way for new items on the list – multi-generational issues, law changes, CSR, and diversity.
Looks like an exciting year!
Gamification, which refers to the use of game elements in non-game contexts, is commonly used as a way to influence the motivation of people in a variety of contexts, including consumer behavior, employee behavior, and student behavior. Much prior research on gamification has been imprecise in which particular game elements are adopted; for example, a study might implement 3 or 4 game elements simultaneously and compare performance in a “gamified” group to a control group. This generally results in difficult-to-interpret and impractical results; how do you know what aspect of gamification actually changed behavior? And beyond this challenge, the simple framing of an activity as a “game” can potentially alter behavior even further. How can we disentangle the effects of game elements from the effect of game framing?
In an upcoming article in Games and Culture, Lieberoth sought to explore the effect of such framing empirically, which he called shallow gamification. In this study, all participants participated in a 30-minute task where they discussed a variety of questions related to solving a “business problem” in groups of 6 – in this case, understanding why student satisfaction statistics were low in the researcher’s department’s recent student evaluation surveys. Deception was involved. After the task, participants were told that the experiment was over but that they needed to stick around for an additional 20 minutes to wait for another group to finish, during which time they were able to continue engaging in the task. Within this procedure, they were randomly assigned to one of three conditions:
- In the control condition, 23 participants just did the task as described.
- In the shallow gamification condition, 22 participants completed the control task but were additionally provided a game board, but no additional game mechanics were used – players simply progressed along the board as they provided answers.
- In the deep gamification condition, 25 participants completed the control task but were additionally provided a game board, and some game mechanics were introduced; specifically, the rating of their discussion was used to determine how many spaces they progressed.
I don’t personally agree with this characterization; I would say that the shallow gamification condition simply incorporates fewer game elements than the deep gamification condition. I would argue that because the shallow/deep dichotomy is quite artificial – just how much gamification is needed to move from one to the other?
Regardless, did more gamification produce better results than less? Unfortunately, presumably due to the small sample size, the researchers did not use a hierarchical analytic approach despite the grouping. This is problematic because there may have been an effect of the composition of gameplay groups – and if you count the number of groups, there were only 3 to 4 per condition, which is a tiny sample. Instead, the researcher ignored group membership and instead focused upon individual-level effects. That may or may not have mattered; there’s no way to know given what was reported.
At the individual level though, some interesting results appeared. Specifically:
- Gamification conditions were rated as more interesting than the control conditions, although the gamification conditions were not significantly different from each other; this may be a power issue, however, given the small sample size (there was about a .2 SD difference between these conditions, with higher scores for the “deep” conditions). There were no differences on any other dimensions of intrinsic motivation.
- The control condition addressed more items in the task than either of the gamification conditions.
- There were no other differences in behavior between conditions, i.e. time spent on task.
The researcher concluded from this that “framing has a significant effect on enjoyment.”
My major concern with this conclusion is that framing is not really what changed here. To make conclusions about framing, I would have rather the researchers only changed one thing about the study: did they call the activity a game? Instead, they presented a game board, which is itself a type of gamification. The major difference between gamification conditions to me is not that one is shallow and one is deep, but instead that one is gamified with one element (the board) and the other with two (the board and a set of rules). Would we have seen the same effect with simple framing, i.e., “You’re about to play a game.”? Would we have seen the same effect with a different gamification element? What if, for example, only rules had been used, and players had been asked to record their scores on paper? There is no way to know from this study alone.
Regardless, this study provides a compelling example that relatively simple changes inspired by gaming – which I would argue is the heart of “gamification” – can produce measurable effects on motivation. Interestingly, the number of discussion items addressed decreased as a result of such gamification. The researcher suggested that this was because the game framing reduced the feeling of this being a “serious” task. As the researcher put it:
I surmise that that [sic] adding a playful frame to the task actually took away some of the grit and output orientation of more goal-oriented work.
If this type of gamification reduces performance in some contexts, this is certainly an important starting point for future research. But I am hesitant to attribute this to “shallowness” or “depth” alone.Footnotes: