Science is not a subject. It is a methodology by which we tackle the problems of the world. Like any methodology, one must learn by actively engaging. Every scientist has at one point sat in a lecture hall of hundreds (or thousands, as is the case at certain universities) for an undergraduate class where the expectation is to passively absorb information for impending exams. A recent meta-analysis from Freeman et al raised questions about whether this form of traditional, lecture-based “teaching by telling” method is really all that effective in maximizing learning and course performance. This group conducted a comprehensive literature analysis of 225 undergraduate STEM teaching studies and found that students engaged in active learning, defined as learning through activities and/or discussions that emphasize higher-order thinking, had significantly greater test scores and lower failure rates compared to those enrolled in passive lecture-based lessons. This effect was present regardless of the specific STEM discipline or the size of the class. At a time when governments want more STEM graduates to build the knowledge economy, alternative evidence-based learning strategies need to be explored in order to address the pipeline problem of increased enrollment with poor passing rates.

Perhaps the solution is to put students in an environment where they can create, collaborate, and fail without career-shattering repercussions. Real life problems require that one is able to confront failure and rise from it rather than to cower and feel defeated. This is how graduate school trains problem-solving and trouble-shooting skills, after all. Active learning through simulation is by no means a new concept; in fact, chess was invented in the 6th century as a way of developing military strategies, while modern-day games have been incorporated into training fighter pilots and business managers alike. Why not extend that to scientists?

video game website figure
Image Credit: Angela Zhou

The big challenge in developing any educational game for any field is gamification: the question of why should students care? Every single person has his or her own motivations for learning and reward systems for accomplishments that determine the level of engagement with the lesson. Yet, the lesson itself exists within the ecosystem of the classroom. Muehrer et al examined the effectiveness of introducing educational gaming sessions to Ontario high schools and found that relationships between teachers, students, and the technology available can all influence the learning process. In one case, having the session in an old building facing the sun with no air conditioning made students restless and unable to focus on the game. These social and environmental factors are tough to address and make it difficult to assess the value of game-based learning. Of course, learner disengagement manifests in different ways at the post-secondary level. The motivation for many is the degree at the very end rather than the sum of what is learnt, done, and produced. Education becomes about “getting through the system.” Thus, the aim of gamification is to create an integrative environment of learning and play that can foster enjoyment (especially in the current undergraduate cohort of tech-savvy millennials) and inspire interest and creativity from the course material.

Although tough, such a task is not impossible. Kerbal Space Program (KSP), for example, is a publicly available space flight simulator game that has inadvertently taught many non-physicists the fundamentals of orbital mechanisms, with communities of gamers gathered online to solve complicated mathematical equations required to launch their spaceships into orbit. In being compelling and challenging (and just plain old fun), KSP is able to engage gamers in the learning process. Gamification is currently being examined as a teaching tool in undergraduate life sciences and engineering classrooms as well as graduate- and professional-level training in the health and biomedical sciences.

With the plethora of personal technological devices available today, multimedia learning not only presents a more engaging classroom experience, but it also provides a powerful data-capturing tool that can continuously measure metrics of individual learning. Although there is still much resistance to these techniques from some educators, there is no denying that sitting passively in a room taking notes is not the most effective way of learning complicated scientific paradigms. Let the next generation of scientists learn through experience and play.

Bonus Round: Data Mining

In addition to being an effective teaching tool, gaming has also made the leap to the lab bench. Researchers have started using gamification as a way of crowdsourcing their own research. Ecologists and geologists have long used citizen scientists to extend their reach in specimen collection; now, scientists in the biomedical fields are enlisting the help of gamers and using human reasoning and spatial awareness to resolve massive amounts of data. Most notable of the kind is FoldIt, a multiplayer online game in which players have to solve protein structures by tweaking, shaking, and wiggling different components of the protein in order to locate the most biologically-relevant, lowest energy, native conformation. FoldIt players (often credited as a coauthor under “Players, F” or a team name on some high-impact publications, such as here and here) have successfully solved many protein structures that would have required incredibly extensive (and expensive) mass-spectrometry-based screening of large libraries. The success of FoldIt can be attributed to its ability to appeal to various short- and long-term rewards and motivations. The game provided opportunities for collaboration and competition, and players were able to interact via chats and forums. These factors contributed to engaging game play and player attrition was not observed.

Cancer Research UK is another active participant in crowdsourcing research. In 2012, they partnered up with Zooniverse to create a game called Cell Slider, where players were asked to identify cancer cells based on colour and brightness from microscopy slides of real tissue samples of cancer patients. The information gathered from game play is then used as a prognostic indicator of how patients will respond to treatment. A tutorial was provided prior to the game for instruction, and the sheer number of participants scanning each slide acted as quality control. Cancer Research UK recently also targeted mobile gamers with Play to Cure: Genes in Space, where players navigate a space ship to map routes, destroy asteroids, and collect various items. Unknowingly, gamers are actually analyzing microarray data from patient tumour samples, saving researchers years of doing the work themselves. These two examples just go to show that not all science happens in the lab.

Acknowledgements: A big thanks to Justen Hoffman Russell, whose savviness with the world of science video gaming contributed immensely to this article.


  1. Cooper S et al. (2010).”Predicting protein structures with a multiplayer online game.” Nature. 466: 756-760.
  2. Freeman S et al. (2014). “Active learning increases student performance in science, engineering, and mathematics.” PNAS. 11(23): 8410-8415.
  3. Friedberg J. (2012). “Revolutionizing education with personalized learning.” TEDxYouth@Toronto.
  4. Khatib et al. (2011). “Crystal structure of a monomeric retroviral protease solved by protein folding game players.Nat Struct and Mol Biol. 18(10): 1175-1177.
  5. Muehrer R et al. (2012). “Challenges and opportunities: using a science-based video game in secondary school settings.” Cult Stud of Sci Educ. 7: 783-805.
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Angela Zhou

Angela is a PhD student at the University of Toronto currently studying immune responses to influenza infection. When not in the lab, she enjoys painting, wandering aimlessly, and spending quality time with good friends.

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One thought on “Level Up: Gaming in Science and Education

  1. Awesome article – have me new insights into the gaming world and how this can be powerfully exploited for science.

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