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Michael Matessa

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Michael Matessa

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Publications by Michael Matessa (bibliography)

» 2005 «

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Vera, Alonso H., John, Bonnie E., Remington, Roger, Matessa, Michael and Freed, Michael A. (2005): Automating Human-Performance Modeling at the Millisecond Level. In Human-Computer Interaction, 20 (3) pp. 225-265

“A priori prediction of skilled human performance has the potential to be of great practical value but is difficult to carry out. This article reports on an approach that facilitates modeling of human behavior at the level of cognitive, perceptual, and motor operations, following the CPM-GOMS method (John, 1990). CPM-GOMS is a powerful modeling method that has remained underused because of the expertise and labor required. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a computational modeling tool, taking advantage of reusable behavior templates and their efficacy for generating zero-parameter a priori predictions of complex human behavior. To demonstrate the process, we present a model of automated teller machine interaction. The model shows that it is possible to string together existing behavioral templates that compose basic HCI tasks, (e.g., mousing to a button and clicking on it) to generate powerful human performance predictions. Because interleaving of templates is now automated, it becomes possible to construct arbitrarily long sequences of behavior. In addition, the manipulation and adaptation of complete models has the potential of becoming dramatically easier. Thus, the tool described here provides an engine for CPM-GOMS that may facilitate computational modeling of human performance at the millisecond level.”

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» 2002 «

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John, Bonnie E., Vera, Alonso H., Matessa, Michael, Freed, Michael and Remington, Roger (2002): Automating CPM-GOMS. In: Terveen, Loren (ed.) Proceedings of the ACM CHI 2002 Conference on Human Factors in Computing Systems Conference April 20-25, 2002, Minneapolis, Minnesota. pp. 147-154.

» 1999 «

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Byrne, Michael D., Anderson, John R., Douglass, Scott and Matessa, Michael (1999): Eye Tracking the Visual Search of Click-Down Menus. In: Altom, Mark W. and Williams, Marian G. (eds.) Proceedings of the ACM CHI 99 Human Factors in Computing Systems Conference May 15-20, 1999, Pittsburgh, Pennsylvania. pp. 402-409. Available online

“Click-down (or pull-down) menus have long been a key component of graphical user interfaces, yet we know surprisingly little about how users actually interact with such menus. Nilsen's [8] study on menu selection has led to the development of a number of models of how users perform the task [6, 21. However, the validity of these models has not been empirically assessed with respect to eye movements (though [1] presents some interesting data that bear on these models). The present study is an attempt to provide data that can help refine our understanding of how users interact with such menus.”

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» 1997 «

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Anderson, John R., Matessa, Michael and Lebiere, Christian (1997): ACT-R: A Theory of Higher Level Cognition and Its Relation to Visual Attention. In Human-Computer Interaction, 12 (4) pp. 439-462

“The ACT-R system is a general system for modeling a wide range of higher level cognitive processes. Recently, it has been embellished with a theory of how its higher level processes interact with a visual interface. This includes a theory of how visual attention can move across the screen, encoding information into a form that can be processed by ACT-R. This system is applied to modeling several classic phenomena in the literature that depend on the speed and selectivity with which visual attention can move across a visual display. ACT-R is capable of interacting with the same computer screens that subjects do and, as such, is well suited to provide a model for tasks involving human-computer interaction. In this article, we discuss a demonstration of ACT-R's application to menu selection and show that the ACT-R theory makes unique predictions, without estimating any parameters, about the time to search a menu. These predictions are confirmed.”

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