Although I have not been doing any game developing for some time, I have been doing some reflecting on game-based STEM learning. One of my work colleagues demonstrated to me a chemistry game that they had been involved in developing, and I had also vaguely thought about PhD study (as if I had time!) to do with game learning themes, and made some visual notes and stumbled across some interesting thoughts.
I’ve been thinking about the performance aspect of game-playing. In STEM learning, there are some schools of thought in which performance is a dirty word. These pedagogical perspectives propose that STEM subject learning can all too easily be perceived as a battery of performance challenges, and that this is a recipe for cascades of inhibitory anxiety in western educational cultures in which performance ability tends to be perceived as related to ostensibly intrinsic, largely immutable, individual characteristics.
It is often noted by enthusiasts of game-based learning that learners tend to have much less performance anxiety in game contexts than in formal learning contexts, and demonstrate comparably greater resilience. When playing games, it seems that people are quite open to tackling challenges and overcoming them.
One fairly straightforward interpretation of this attitude contrast is that game-playing is a basically low-stakes activity; being a mediocre performer at some game is not generally perceived as a value judgement on a person in the way that a formal learning challenge might be. With nothing of great import to lose, why should there be anxiety? This hypothesis suggests a potentially major problem for the future of game-based learning. If it becomes an established and accepted truth that formal-like learning is possible through game-play, what was seen as harmless fun may become a serious measure of a learner’s sense of self-worth, with all the concomitant anxiety that such a measure implies. Play becomes work.
Another aspect of performance in game playing is the notion of the importance of unpredictability and the role of what I term high-pressure flow. The flow I allude to here is the flow-state made famous by Mihaly Csikszentmilhalyi, which is basically a state of optimal stimulation balanced somewhere between low stimulus boredom and high stimulus anxiety. The thought of such a flow state suggests to me two markedly different conditions. One kind of flow is a kind of detached relaxation in which one feels able to do what one wishes, but that activity may not be very well, active (at least outwardly). The word revery perhaps invokes what I aim to convey, in the sense of a feeling of deep understanding, of seeing connections between things whose connections had not before seemed apparent. This kind of flow (the low pressure kind) could be thought of as the preparatory basis of all sorts of creative (and synthesising) activity that would follow from the insights stemming from immersion in the flow state.
High pressure flow corresponds more to performance and pushing at one’s limits while focusing narrowly on some specific activity. This strikes me as being associable with the phenomenon of hormeosis. Hormeosis is the ability of organisms (and perhaps other dynamic systems) to ramp up their capacity to perform the functions that they normally perform, discovering that as a matter of course in workaday life these functions are not performed to anywhere near their peak capacity (as is only prudent, otherwise should these functions be even somewhat compromised then the organism would be unable to function adequately under typical circumstances). High pressure flow activities are characterised by high stakes error avoidance, with even quite minor errors tending to be largely non-recoverable from once made, requiring a return to some remote starting point and a repeat attempt to progress from there.
It seems plausible to me that high pressure flow is a feature of a lot of game playing because games that can be easily defined (and hence remembered and shared) are more likely than not to be based around some sort of fairly prescriptive goals or conditions rather than being conducive to free-form associations of ideas. When games are designed for learning, especially in STEM contexts, the specificity of the purpose of play is likely to be all the more pronounced (although games that are hugely free-form, such as Minecraft, have been influential in the STEM learning game world).
In STEM subjects, the concepts of methods, rules, and deterministic processes are of great significance in developing learners’ understanding of the subject content. Methods and rules are expected to be well defined enough that the processes that they are used to model can be specified and predicted. Prediction and control are arguably the raison d’etre of applied science. The precision and accuracy requirements of STEM learning has a commonality with the high stakes error avoidance outlook of high pressure flow, but without the imposition of the time constraints and hormeosis-prompting difficulty spikes typical of high pressure flow; the very factors that most strongly characterise that flow state (taking exams could be a notable exception). I found myself trying to put this across to a colleague of mine recently by saying that when the way to win a game involves planning and specifying a procedure beforehand and then executing the procedure, the game is not really being played any more so much as it is being witnessed. Designing a procedure that could have been executed by an appropriately instructed machine is not so much playing a game as telling a machine how to play the game on your behalf. The ‘live’ experience of being the game’s player fades, and along with it I suspect does the much vaunted intrinsic motivation that game playing is supposed to offer.
There is in principle a role for low pressure flow in STEM learning in that the low pressure flow state has affinities with more experimental activities in which curiosity is more of a driver than the intent to perform well. Learning activities based around weakly directed experimentation are notoriously ineffective at translating into measurable learning, at least one reason for which may be that what learners learn (and when they learn it) when they undertake such activities cannot be known in advance, so anyone wanting to measure the results of such learning has a difficult job to do. Some sort of precarious balance probably exists wherein the scope of activities is narrow enough to make the meaning of them clear, but also wide enough to make the ways in which these meanings are discovered conducive to a sense of free exploration (medium pressure flow?), but STEM learning game design looks like it has a long way to go to find that balance.