Abstract
There have been a number of successes of real-time application of physiological measures in operational environments such as with the control of remotely piloted vehicles (RPV). More recently, similar techniques have been investigated within the context of improving learning. A major challenge of the learning environment is that an individual’s ability to perform the task, and thus their workload experienced during the task, are constantly changing. Cognitive Load Theory provides insight into how workload interacts with learning. One aspect of this theory is that as information is learned it reduces working memory demands. This paper discusses results from an RPV training study investigating the effects of workload and learning on pupil diameter. Specifically, pupil diameter decreased overtime as the task difficulty was held constant, and increased as new information was presented. The results of these studies are discussed in terms of how they can be used in a physiologically driven adaptive training system.
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Coyne, J., Sibley, C., Baldwin, C. (2011). Ongoing Efforts towards Developing a Physiologically Driven Training System. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Foundations of Augmented Cognition. Directing the Future of Adaptive Systems. FAC 2011. Lecture Notes in Computer Science(), vol 6780. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21852-1_47
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DOI: https://doi.org/10.1007/978-3-642-21852-1_47
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