Human performance modeling: Difference between revisions

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Cognitive Architectures are broad theories of human cognition based on a wide selection of human empirical data and are generally implemented as computer simulations. They are the embodiment of a scientific hypothesis about those aspects of human cognition relatively constant over time and independent of task (Gray, Young, & Kirschenbaum, 1997; Ritter & young, 2001). Cognitive architectures are an attempt to theoretically unify disconnected empirical phenomena in the form of computer simulation models. While theory is inadequate for the application of human factors, since the 1990s cognitive architectures also include mechanisms for sensation, perception, and action. Two early examples of this include the Executive Process Interactive Control model (EPIC; Kieras, Wood, & Meyer, 1995; Meyer & Kieras, 1997) and the ACT-R (Byrne & Anderson, 1998).

A model of a task in a cognitive architecture, generally referred to as a cognitive model, consists of both the architecture and the knowledge to perform the task. This knowledge is acquired through human factors methods including task analyses of the activity being modeled. Cognitive architectures are also connected with a complex simulation of the environment in which the task is to be performed - sometimes, the architecture interacts directly with the actual software humans use to perform the task. Cognitive architectures not only produce a prediction about performance, but also output actual performance data - able to produce time-stamped sequences of actions that can be comapredcompared with real human performance on a task.

Examples of cognitive architectures include the EPIC system (Hornof & Kieras, 1997, 1999); CPM-GOMS (Kieras, Wood, & Meyer, 1997), the Queuing Network-Model Human Processor (Wu & Liu, 2007, 2008),<ref name=":4">{{Cite journal|title = Queuing Network Modeling of Driver Workload and Performance|url = http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4298914|journal = IEEE Transactions on Intelligent Transportation Systems|date = 2007-09-01|issn = 1524-9050|pages = 528–537|volume = 8|issue = 3|doi = 10.1109/TITS.2007.903443|first = Changxu|last = Wu|first2 = Yili|last2 = Liu}}</ref><ref>{{Cite journal|title = Queuing Network Modeling of a Real-Time Psychophysiological Index of Mental Workload #x2014;P300 in Event-Related Potential (ERP)|url = http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4604816|journal = IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans|date = 2008-09-01|issn = 1083-4427|pages = 1068–1084|volume = 38|issue = 5|doi = 10.1109/TSMCA.2008.2001070|first = Changxu|last = Wu|first2 = Yili|last2 = Liu|first3 = C.M.|last3 = Quinn-Walsh}}</ref> and the ACT-R (Anderson, 2007; Anderson & Lebiere, 1998).