Automating human-performance modeling at the millisecond level

Vera, Alonso H., John, Bonnie E., Remington, Roger, Matessa, Michael and Freed, Michael A. (2005) Automating human-performance modeling at the millisecond level. Human-computer Interaction, 20 3: 225-265. doi:10.1207/s15327051hci2003_1

Author Vera, Alonso H.
John, Bonnie E.
Remington, Roger
Matessa, Michael
Freed, Michael A.
Title Automating human-performance modeling at the millisecond level
Journal name Human-computer Interaction   Check publisher's open access policy
ISSN 0737-0024
Publication date 2005-01-01
Sub-type Article (original research)
DOI 10.1207/s15327051hci2003_1
Open Access Status DOI
Volume 20
Issue 3
Start page 225
End page 265
Total pages 41
Place of publication Mahwah
Publisher Lawrence Erlbaum Assoc Inc
Language eng
Subject 17 Psychology and Cognitive Sciences
Abstract 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.
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Psychology Publications
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Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 11 times in Scopus Article | Citations
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Created: Thu, 18 Oct 2007, 00:06:57 EST