We have not been able to track or collect mouse or keyboard or joystick data with millisecond accuracy. We have not been able to use our eye trackers to collect location information for dynamic regions of interest in video games. What we have not had, however, are the tools to manipulate and collect data from these populations of experts in their tasks of expertise. Fortunately, the world has turned towards a direction more favorable to the university researcher.Īlthough we do not argue that our tasks are of societal or commercial importance, Footnote 1 we do argue that with the spread of video gaming, university-based researchers now have ready access to a population of performers who have put in the hundreds and thousands of hours needed to achieve true expertise. Whereas, data collection tools capable of recording hand and eye movements to the nearest millisecond, and experimentation tools capable of manipulating the task environment in ways designed to isolate or highlight theoretical factors of interest, exist in the university laboratory. Experts and populations of motivated novices exist for important real-world tasks such as laparoscopic surgery (Keehner et al., 2004 Keehner, 2011), piloting aircraft and helicopters (Hays et al., 1992 Proctor et al., 2007), detecting enemy submarines hiding in deep waters (Ehret et al., 2000), and call-center operators (Gray et al., 1993).
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Traditionally, there have been disconnects between the first three and the last of this list. Ideally, researchers who seek to understand complex, cognitive behavior in dynamic task environments would have access to: (1) a task of societal and/or commercial importance, (2) a population of expert performers, (3) a population of novices who can be motivated to acquire expertise in the task, and (4) task manipulation and data collection tools of high sensitivity.
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