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What is gamification?

Gamification is when a task relies on game elements or mechanics to increase engagement, motivation, attention, in a way that achieves learning outcomes.  

Gamified content has grown more-and-more in popularity and use over the last decade. Academic and industry researchers chalk this up to the natural demographic changes. A fancy way of saying that there are more people in schools and the workforce who have grown up playing video games and experiencing their highly interactive environments.   

They won’t only be comfortable with the environments offered by gamification but will, in fact, expect it.  

Newzoo infographic showing the global games market which includes products of gamification.
https://newzoo.com/insights/articles/newzoo-games-market-numbers-revenues-and-audience-2020-2023/

How new is gamification? 

The overall concept of gamification isn’t new. It’s been around for a long time, but the idea of digital gamification has only been in practice since the early 1970s and it wasn’t until the 2000s that most folk could agree on what to call it.  

What is or what isn’t gamification is a debate that some still have today, but TIQ Software has been in the gamification ring for decades and we’re pretty solid on the ins and outs — info we plan on coaching you through in this handy playbook. Want to know more about gamification’s history? You can check it out here.

What are the types of gamification? 

All gamification can fall into two types of design — structural gamification and content gamification. What type is used on any project depends on the learning outcomes you want to achieve and, as always, how much time and money you have.  

Structural style 

This style of gamification involves taking already made content and applying gamification to it without altering or changing the structure of it. The user becomes engaged and motivated to work through the content by the gaming elements layered on top of it.  

This can often be done by adding achievement badges, points, timers, rewards, progression, and task sequencing. When using structural style, it’s important to remember that learning and development theories still apply and flow, context, and even story or theme shouldn’t be forgotten — even if only lightly applied.  

TIQ Software implements this type of gamification in many of its projects and an easy example of how it all fits together can be found in our demo here.  

Content style 

This style is when you take the original content drill it down to its core and then build it back up from the foundation to become a game on its own. The level you drill down or alter the content exists along a spectrum, but in essence you want to add gamified and interactive elements to make the game more engaging for the user.  

Deeper story, simulation, or game mechanics are often required and the process is often much longer and more involved, expensive, than going with a more structural style. An example of the content style is Solar Energy Defenders, where the science of solar energy was broken down into a Plants vs. Zombies tower-defense style game for users looking to learn about solar energy.  

Does gamification have genres or sub-genres? 

Yes. There are different genres and sub-genres within gamification, serious games and edutainment games being two of the largest and most defined in 2021, but the new and expanding field of gamification continues to grow alongside the technology and techniques of industry 4.0. 

Serious games 

Video and computer games with the primary focus of education or skill development. These games are designed for a user to learn first and always, but while engagement is still requirement, but with a serious game it often doesn’t arise through entertainment. Learn more about serious games.  

Edutainment games 

Video and computer games with an equal (ish) focus on entertainment and education. The term edutainment goes beyond games and includes passive forms of entertainment like television, movies, radio, and literature, but interactive games are the leaders of this genre. Learn more about edutainment games.  

To make things even more confusing gamification can also have all the genres and sub-genres that commercial or indie video or computer games have.  

Learn these 7 elements for gamification success!

The Gamification Mixing board set at the default 50%

There are 7 components that you can mix for a successful structural or content styled gamification project. These 7 components are best visualized in the form of a mixing board, so you can raise or lower each area of your project before you start, getting the best mix for your audience.  

1. Learning 

Is learning the primary focus of your gamification project? If it is this should be set higher depending on how much of priority learning is. Most gamification projects focus at least tangentially on teaching something to someone.  

2. Story 

Does your gamification project have a fully fleshed out world? Branching narrative design? Or is it more a general theme with story elements. A higher slider here shows how much focus you put on story as a tool to increase engagement. A higher story slider is often associated to content styles of gamification. 

3. Game mechanics 

The number of systems, their sophistication, and difficulty determines your game mechanics’ slider level.  At the low-end points and badges motivate the user through content, but at the high-end full avatar customization and systems like movement, conflict resolution (combat), turn order, and leaderboards could all come into play. It’s also important to consider the collaboration and competition levels you want to have between different players when thinking about game mechanics.   

4. Simulation

Do you have simulation content? How close to reality is it? The more involved a simulation is, the more immersive it is, and the more real it appears to be is what moves the slider from low to high.  

5. Feedback 

In most, if not all, gamification projects feedback should be immediate. When users interact with the game, they need to understand their actions. They need to know if what they did was right or wrong. But how detailed and personalized the feedback becomes determines the slider’s level. High levels often include built-in dashboards where users, employers, or educators, can view and analyze key analytics.  

6. Replayability 

How replayable is your gamification project? How much of the content users can replay, whether the game changes or scales when they replay it, and how long they can access to the replayable components sets the level here.  The higher the slider the more open to replay your content is.  

7. Simplicity 

The goal of your project may not be simple, but how to engage with the gamification components of it probably should be. A low slider here would mean the game is complex and probably requires a tutorial or even a rulebook. A high slider means a user could jump right in and start playing.   

For some specific gamification mixing board examples check out serious games and edutainment games.  

What about fun? 

Fun and gamification have a intertwined relationship. Gamification needs to motivate and engage and one major way of doing that is through fun, entertainment, and enjoyment. So, while fun may not always be the main focus, fun almost always equals engagement and motivation. Crank up the fun whenever you can.   

State of gamification 

The last few years have seen exponential growth in the realm of gamification, but is that across every industry? What are some of the new and exciting things happening in gamification? Take a glance below in this 2021 pulse check.  

Schools and higher education 

Use of gamification in schools has been studied over the last decade. They’ve pointed to a number of advantages of gamified learning over more traditional methods. Student engagement, performance, attitude, and motivation were all found to be improved when game-based learning was used. 

A number of studies have also examined particular aspects of gameplay elements, like the awarding of points and badges, leaderboards, and user progression. These elements significantly improved student motivation and engagement. The education industry has also benefited from game design partnerships both at the indie and commercial level with games like Minecraft.  

Workplace training 

Research on the use of gamification for training of employees in the workplace shows benefits to those found in education. The use of gamification within industry has significantly increased over the last 5 years and feedback from clients and users shows improvements in motivation and engagement in both structural and content focused gamification systems.  

The use of gamified systems is expected to only increase as more-and-more companies attempt to develop emerging skills within their workplace or adopt learning for a more remote setting.  

2021 will be a year where workplace inclusion and culture training will continue to grow in the corporate gamified landscape, second only in to the powerful product knowledge gamified training awaiting sales and frontline teams by increasing channel performance by a remarkable amount

Health, wellness, and personal development 

Gamification has also been used in the areas of physical and mental health by increasing engagement and motivation to exercise, self-actualize, meditate, and even build habits. The mobile app world has hundreds of thousands of applications dedicated to these areas from Couch to 5k, an app that helps get users trained to run and walk up to 5 kilometres, to Habitica an app that helps gamify a to do list and build good habits all with a retro gamified role-playing game (rpg) backdrop.  

These apps often have a powerful social component rewarding users from engaging with others so they don’t succeed or fail within a silo. Throughout 2021 these applications will continue to grow in popularity as users look for new ways to take care of personal challenges.  

Does data matter? 

There is increasing interest in using data collected during gamified learning. The data analytics performed can range from fairly simple analysis through to complex, multi-parameter psychometric model fitting.  

Often this is shown on an admin dashboard, a location where user data is summarized and often graphically displayed, showing how they interacted with the content. The aim being to assist instructors in monitoring student progress or assessing course effectiveness. 

TIQ Software's gamification Insights analytics panel

Detailed data, like for each question, is also available, often including percentage of correct answers or the number of responses for each individual incorrect answer. It should even be possible to download a file containing a complete log of user interactions with the software.  

Data matters because the future of productivity is driven by it. 

A data driven future  

Gamification is ideally suited to gathering large amounts of information about a user’s interactions with, and responses to, the material.

Opening the door wide for responsible data collection and analysis, obtaining info about the user’s abilities and their progress with the material. You could even discover more historically elusive information like their level of motivation and engagement.  

This info can often be gathered in the background allowing users to focus on the content and learning without any test anxiety or jitters. This style of challenge can provide a more realistic assessment of a user’s abilities.  

What information you need will vary highly depending on your situation. A project manager responsible for implementing the course will require top-level info, the big picture, about the course and its ability to meet company objectives. Training managers may need to see more detailed information about an individual user’s progress and achievement. A course developer would need an overview showing how different tasks and questions are doing, like percentage correct or time spent.   

Overall allowing different levels within a corporate hierarchy to drill down as far as needed is where peak functionality meets productivity when data and reporting is required.  

Simple Vs. Complex — Fight! 

As mentioned previously, many different methods of greatly varying complexity are available for analyzing your data. The level of complexity should match your need.  

If only basic information is required and simple analysis methods can provide it then more complex analysis is an unnecessary time waster. But realize that, if it’s found to be unreliable or invalid, then a more complex analysis is probably needed. 

UnreliableInvalid
Giving very different results for very similar data sets.A situation where a simple interpretation of data can lead to erroneous conclusions or spurious correlation
Spurious correlation example relating number of people who drowned by falling into polls with films Nicolas Cage has appeared in.
Image from tylervigan.com

The future of gamification 

Artificial intelligence (AI), machine learning (ML), and adaptive learning are almost certain to play an increasingly significant role in gamification through 2021 and beyond.  

Machine learning 

Machine learning has the potential to significantly reduce the effort required to perform detailed analysis of gamification data. In its simplest form, supervised learning, output results are obtained from an example data set and the system is “trained” to determine the correct answers.

ML could be used to determine which users would be expected to meet the required level of competency, or even the real-time identification of users with low levels of engagement so early intervention actions could be taken.  

More complex levels of ML involve unsupervised learning, where the system itself identifies patterns in the data, without being given specific correct answers but just some overall goal.

A common form of unsupervised learning is cluster analysis, where the system identifies different groupings into which the data appear to fall.

Another form is reinforcement learning, where some kind of points or similar reward mechanism is used to steer the system in the overall required direction, again without specific outcomes being preconfigured. 

Adaptive Learning 

With adaptive learning, the system, on analyzing data from users as they progress through the course, could decide what material should be presented next to individual learners.

If a user already had a good working knowledge of the material, via the data, then they could instead be presented with new material or challenges that meets their level.

The other side of the coin would also be true, a user struggling with the material could be given more foundational challenges or practice before moving into more difficult tasks. 

What’s next?

While gamification in education and the corporate world has exploded over the last few years, 2021 and beyond is bursting with further growth. Data-driven decision making, technological innovation, and a growing game-focused population will push gamification into becoming a staple for at-home, at-office, at-school, and on-the-move mobile learning today, tomorrow, and into the future.  

Artificial intelligence and machine learning will almost certainly be used to in the future, both in data analytics and adaptive learning roles. 

It’s going to be an exciting and amazing ride for those looking to teach and learn.  

Further Reading / References

Subhash, S. and Cudney, E. A. (2018) Gamified learning in higher education: A systematic review of the literature. Computers in Human Behavior, 87, 192–206. DOI: 10.1016/j.chb.2018.05.028. 

Hew, K. F., Huang, B., Chu, K. W., Chiu, D. K. (2016). Engaging Asian students through game mechanics: Findings from two experiment studies. Computers & Education, 92–93, 221–236. DOI: 10.1016/j.compedu.2015.10.010. 

Chang, J. W., Wei, H. Y. (2016). Exploring Engaging Gamification Mechanics in Massive Online Open Courses. Educational Technology & Society, 19(2), 177–203. DOI: N/A. 

Bengtsson, M. (2020). Using a game-based learning approach in teaching overall equipment effectiveness. Journal of Quality in Maintenance Engineering, 26(3), 489-507. DOI: 10.1108/JQME-03-2019-0031. 

Scalise K., Bernbaum, D. J., Timms, M., Harrell, S. V., Burmester, K., Kennedy, C. A., Wilson, M. (2007). Adaptive Technology for E-Learning: Principles and Case Studies of an Emerging Field. Journal of the American Society of Information Science and Technology, 58(14), 2295–2309. DOI: 10.1002/asi.20701 

Wilson, M., Scalise, K., Gochyyev, P. (2019). Domain modelling for advanced learning environments: the BEAR Assessment System Software. Educational Psychology, 39(10) 1199–1217. DOI: 10.1080/01443410.2018.1481934. 

Kučak, D., Juričić, V., Đambić, G. (2018). Machine Learning in Education – A Survey of Current Research Trends. Annals of DAAAM & Proceedings, 0406-0410. DOI: 10.2507/29th.daaam.proceedings.059. 

Stimpson, A. J., Cummings, M. L. (2014). Assessing Intervention Timing in Computer-Based Education Using Machine Learning Algorithms. IEEE Access, 2:78-87. DOI: 10.1109/ACCESS.2014.2303071. 

Hussain, M., Zhu, W., Zhang, W., and Syed Muhammad Raza Abidi, S. M. R. (2018). Student Engagement Predictions in an e-Learning System and Their Impact on Student Course Assessment Scores, Computational Intelligence and Neuroscience, 1-21. DOI: 10.1155/2018/6347186. 

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