Continuing my study of gamification, the next step is to look at ways to motivate people:
Examples of motivation found in real life are through:
- Bribery – or offering some type of tangible prize
- Altrusism – helping individuals first and appealing to the individual’s concern for others.
- Praise. People generally want to win and be doing good. Praise helps reinforce whatever they were doing to win such praise.
Sorry to be a cop out but there is no single correct answer; there are actually many ways to do this. To truly understand motivation, we need to delve into some psychology.
The famous psychologist Pavlov, first came up with the observation that behavior is derived from some external stimulus.
B.F. Skinner then built upon this idea by defining the feedback loop, also known as operant conditioning, which is a fundamental insight into behaviorism. Operant conditioning essentially describes that when someone does an action, a response happens, then learning occurs. We learn to alter our responses to stimuli in a feedback loop.
This then led to the concept of behavioral economics, which show that people make mistakes consistently. The following describes a few patterns commonly found in behavioral economics:
- Loss aversion – people are more scared of losing what they already have than by gaining something more.
- Power of defaults – a famous demonstration of this is in increasing the number of registered organ donors. By making the donation the default choice, and making a person check another box to opt out, States have increased registered organ donors but a substantial amount.
- Confirmation bias – if you think you’re going to get a certain result, you tend to find it.
How is this relevant to gamification?
Based on this academic research, we can reasonably conclude that motivating people in games will involve:
- Observation – first looking at what people actually do
- Feedback loops – inserting a process of action and feedback response to motivate a new behavior. A prime example of this being the LinkedIn completion bar.
- Reinforcement. Learning occurs through the reinforcement of stimuli. A certain action leads to a result, then the individual makes an association. Reinforcement can be performed using consequences, such as in the Facebook game Farmville, wher you see withering crops when you don’t tend your farm, or in using rewards, such as providing a badge.
Types of rewards
Rewards can be further articulated using cognitive evaluation theory. Rewards generally fall into three categories:
- Tangible/intangible – such as my first example, this can be a physical badge or money, or an intangible reward such as a foursquare badge.
- Expected or unexpected. People generally love surprises.
- Contingent rewards. This is a more complex reward structure and can be broken down further.
Contingent rewards generally fall into 4 categories:
- Non-contingent, you get the reward based on nothing. This is not too commonly used
- The reward is contingent on engagement, such as starting a task.
- The reward is completion contingent. You must complete the task such as watching a video.
- Or performance contingent. You must do well on the task in order to collect the reward.
This then raises the question or when is the optimal time to give someone an award? I’ve been seeing a lot of really interesting companies such as kiip pop up in this space, providing rewards during optimal times when users experience moments of happiness or achievement in a game. However, more loosely, a few different reward schedules to consider are:
- Continuous rewards, such as getting a reward every time you do something.
- Fixed ratio rewards, every n number of times you complete an action, you get an award.
- Fixed interval reward – reward comes after every x units of time
- And finally perhaps the most interesting – the variable rewards, which is on no fixed schedule, and introduces the element of surprise.
The main drawbacks of using rewards is that this can often de-motivate someone from a task, similar to the use of leaderboards. For example if someone naturally enjoys doing something, such as drawing, offering a reward every time an individual completes the task shifts the enjoyment from an intrinsic nature to an external reward. Studies have shown that when this switch is made and the reward is then taken away, individuals lose the motivation to pursue the task, and drawing quality suffers, or in cases the individual stops drawing altogether.
This is called the over-justification effect and designers need to be mindful of how this can impact a game when rewards are overused.