Gamification in Behavioral Economics

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Game mechanics that drive people to Action

Behavioral science is openly related to psychology, economics, and marketing. However, not as many individuals make the same relation with game design or software engineering. Where can we set borders? In reality, there is a broad set of tools and frameworks used in behavioral economics that benefit from other sciences. In this article, we aim to address the increasingly important engineering area Game Mechanics, and its applications to the educational sector.

*Definition of Gamification: “The addition of game elements to non-game activities”, is particularly effective for increasing people’s* ***engagement***, ***motivation****, or improving* ***learning***.
(Deterding et al., 2011)

First of all, why gamify something? Especially in economics, where we already have game theory, cost-benefit analysis, and other theoretical frameworks that facilitate complex reasonings and aid in perfecting the decision-making process, it may seem redundant. Nevertheless, the objective of gamification is substantially different. The main purpose lies in engaging and leading the consumer, and not so much in dictating their action. As a result, more and more real-life problems are being adapted to game situations where the consumer/user is nudged towards a specific path. Essentially, it leverages fun to create motivation, just like in addicting video games.

In every job that must be done, there is an element of fun. You find the fun, and – SNAP – the job’s a game! – Mary Poppins

In conventional behavioral economics (if we already arrived there), the focal point of any consultancy project is the experiment. The solution to a problem, being it in marketing, human resources, or any other area, passes through understanding what behavior an organization wants to stimulate in its target group or society. This is precisely why corporations are searching for better solutions through gamification. Certain human psychological actions are difficult to stimulate through “normal” methods and even harder to predict from game theory or related tools that perceive the representative agent as rational.

Let’s take Duolingo.com for example. If the reader has ever tried to learn a foreign language independently (without any teacher, book, or guide), then probably has encountered this user-friendly website. Duolingo was founded 10 years ago and today is a publicly-traded company valued at USD 161.7 million, with more than 400 employees, 500 million users, and 106 different language courses in 40 different languages¹. But, if the reader has ever tried to learn a foreign language independently, then probably has found it not as captivating or easy as it may seem. How did Duolingo achieve this level of success? Can we restrict its merit to simply better or more disciplined users?

Well, the internet plays an important part in today’s world of education, but game mechanics might also be a source of success in this case. The difference between learning a language from a regular website and Duolingo lies in how the language is taught. The latter brings about different features that the reader may not encounter often, such as storytelling, goal framing, badges, points, levels, and other virtual incentives that promote the user to be disciplined and maximize their learning experience. The key lies in turning actions and exercises into fun challenges and creating a story behind the user’s progress so that he stays addicted to the “game” and finding out what is next. These gamified features transform the user’s involvement and the nature of the task at hand (from boring L to exciting J).

This concept may appear to the reader as simple, straightforward, or even common. However, behind these ideas and their application, there is a team of designers, whose objective is to put themselves in the users’ point of view and trace their mental steps. Where would they quit? There is the need, as in any problem-solving situation, to identify and understand the problem, conceptualize the right game mechanic, and finally test it to figure out if the correct mental aspects of the user’s cognitive perception were addressed. In fact, this is a complex process. Amongst all the known (and unknown) biases, being able to understand the real drivers of a specific human choice is a behavioral trial by itself, thus this synergy between behavioral science and gamification enhances the strengths of both areas.

Like Duolingo, many other non-game situations are being transformed by fun, consequently increasing motivation and creativity. Yet, we should never take this as a closed subject. Taking Education, for example, it has been a static, unchanged sector for several decades, that stimulates risk aversion. As Scott Hebert said in his 2018 Ted Talk on gamification uses for education, “the Education system is a system in an engagement crisis”. Children are in school to learn, and shouldn’t be scared to fail or be creative and innovative. We should encourage autonomy and make learning fun so that the behavior and opinion towards school takes a positive and rewarding turn. The setup of a non-game question needs to address the participants (as different individuals), their expectations, and all the time-sensitive and contextual factors, hence it is clear that children’s opinions on how to learn should be taken into consideration. Only then can their behavior be effectively altered over time, possibly creating a new generation of learners.

In sum, gamification constructs a setting where the user is led towards a specific outcome, like learning a new language or a new subject in school, through the construction of a fun, engaging, and playful setting. At the end of it all, it is a win-win.