2.17.2014

Gaming communities as educational communities

Gaming communities as educational communities
Presented at MAPSES 2014 in Scranton, PA


I'm optimistic about massively open online education. There’s been a recent round of skepticism about low rates of completion and other difficulties with the current implementation of MOOCs, but I don’t find these numbers discouraging for two reasons. First, I think it's good if anyone is learning anything. 13% is a low completion rate, but these courses are sometimes enrolling 100,000 people and regularly have enrollments of around 50,000 students. 13% completion still means that thousands of people are completing these courses, and tens of thousands more are receiving at least some exposure to material they otherwise wouldn’t. I see that as an unqualified positive success. And second, we don't have standards for comparison for how well these online courses should be performing, and how far we are from meeting those standards. The College de France and the European Graduate School have both been mentioned at this conference as operating on open principles, albeit at smaller scales. But scales matter for evaluating systems as complex as education.So I want to throw another example into the mix in the hopes that it stimulates some more creative ideas in this direction.


I want to look at online gaming communities from an educational context. Modern strategy games, like Starcraft and Dota and League of Legends, are deep and difficult games with steep learning curves and extremely high skill ceilings. Performing well at these games requires both quick strategic thinking under pressure and impressive displays of manual dexterity. Starcraft in particular has become a national sport in Korea over the last decade, with professional leagues broadcasting tournaments on television and top performing players earning salaries, sponsorship, and fan followings comparable to top athletes in other sports. Over the last 3 years the rise of so-called “e-sports” has garnered equally impressive popularity among gamers in America and Europe. Video games have become a successful spectator sport, even though the audience can easily load up the same gaming environment play alongside the pros. To give a sense of the popularity, one of the main streaming sites Twitch.tv is seeing 45 million unique viewers every month, streaming millions of hours of games, with some tournaments easily rivaling ESPN and other traditional sports broadcasts in terms of live viewership. The economics and ethnography of this community are extremely interesting.


But from an educational perspective, these games are difficult to play, and some understanding of the gameplay is required to make watching tournaments entertaining. So there’s an incentive within the community, in order to sustain itself, that it educate the noob players well enough to enjoy the game. So there’s a thriving community of both self-motivated learners and professional or semi-professional experts who take the time to educate, both on a paid and volunteer basis. For the last decade the learning in the community followede a chess club model, with “coaches” who would charge fees to help train a player to improve their game. But over the last few years the community has grown more complex with the rise of the internet. So let me highlight some of the features of this community relevant to MOOCs:


  • Multi-media, multi-technology, radically distributed. The community has a presence in youtube videos and live streaming, on reddit and on wikis and several different message boards and fan pages devoted to discussing both the game and the community around it. There’s also ingame team chat channels, messaging services, and so on. No central authority or necessary package of tools, but a few major hubs of activity across a variety of media and contexts.

  • Learning is situated within this social context among recognizable personalities (if not genuine ‘celebrities’), which provides standards for excellence, personality,  authority and social organization, interpersonal and team drama, art and music, and all the other markings of culture. Within this context, players discuss the “metagame”, which refers to the changing style of gameplay over time as new tricks and techniques are discovered and become widely adopted, and engage in “theorycrafting”, whereby they reason about strategies and tactics, comment on tournament results and rankings and game balance, and so on. In the process, the gamers not only disseminate existing knowledge, but generate new knowledge in the process. The results of this self-motivated, situated learning are very promising. If these gamers were teaching themselves to play chess or any athletic sport, we’d all be very impressed. In fact, these kids have learned to play games that are just as strategically difficult and impressive

  • Learning in this context takes both public and private forms. According to Kow (2013), novices tend to learn best from public media and coaching, while more experienced players tend to form private (or professional) clubs with peer groups in which information is exchanges and practiced at higher levels.

  • Beyond static resources like wikis and youtube videos, players are actively streaming their games at all hours, with international success, at all levels of play including streaming paid novice coaching sessions. Top players are accessible and practice openly in public to very high viewership ratings (sometimes breaking tens of thousands of simultaneous viewers) and lots of community interaction. Lower ranked pros and semi pros have greater or lesser viewership depending not only on the quality of their play, but also on their personality and social notoriety within the community, reinforcing the situatedness of the learning environment. But a number of public streamers are novices, training to get better and potentially break into the community spotlight. In addition, a few “educational streams” have started with explicitly educational functions. For instance, Day[9] has a regular daily stream where he teaches the audience to “be a better gamer”, with tips and analysis to help audiences of all skill levels. It turns the context into an explicitly educational, but the usefulness of the stream has also made it extremely popular, and has turned Day[9] into a community celebrity and respected authority.

  • Learning as a community: Scarlett, a transgendered gamer, has received huge community success despite the traditionally hostile attitude among gamers. This has been the result of both financial pressure from sponsors, visible instances of punishment of community members for hostile or offensive language, and self-policing from more visible members of the community. It demonstrates “unintentional learning” as a byproduct of community organization only indirectly related to the the self-motivated rewards of gaming


Contrast these features with MOOCs as currently implements:
  • Relies on traditional educational contexts and styles to situate the learning. This context may be more or less familiar to students, with little social resources to acclimate students to the educational environment who aren’t familiar with traditional educational contexts.

  • Relies on centralized technological platforms, often through one-way channels of discussion within narrow social context.

  • Depends on self-motivated learners with nothing to reinforce that motivation

  • No continuous, live support. No personalities except academics. No examples of expert performance to emulate or active peers to learn from. No opportunities for occupying the spotlight or potential for making a career from the effort.

Google HelpOuts may provide a platform that can assist the existing MOOC structure. HelpOuts are hangouts with educational focus, learning guitar or a language or math tutoring for a small fee


  • While not everyone is a recognized expert able to give a world-class lecture, we have lots of people able to assist in the educational process in these streaming, coaching, and support roles

  • Helpouts needs a community context and self-motivated culture to reinforce the learning that this technology allows.