Automating Human-Performance Modeling at the Millisecond Level
- ISSN: 07370024
- DOI: 10.1207/s15327051hci2003_1
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.
Automating Human-Performance Modeling at the Millisecond Level
Automating Human-Performance Modeling at the Millisecond Level Alonso H. Vera NASA Ames Research Center & Carnegie Mellon University Bonnie E. John Carnegie Mellon University Roger Remington NASA Ames Research Center Michael Matessa NASA Ames Research Center Michael A. Freed NASA Ames Research Center
RUNNING HEAD: HUMAN PERFORMANCE MODELING) Corresponding Author’s Contact Information:
Dr. Alonso H. Vera
Mail Stop 262-4
NASA Ames Research Center
Moffett Field, CA 94035
Brief Authors’ Biographies: Alonso Vera is a Cognitive Scientist with an interest in human performance modeling tools; he is faculty at Carnegie Mellon and a Senior Research Scientist at NASA Ames Research Center where he leads the HCI Group. Bonnie John is an Engineer and Cognitive Psychologist with an interest in modeling as a usability assessment method; she is a Professor in the Human Computer Interaction Institute at Carnegie Mellon University. Roger Remington is a Cognitive Scientist with an interest in basic cognitive processes; he is a Senior Research Psychologist and heads the Cognition Group at NASA Ames Research Center. Michael Matessa is a Cognitive Scientist with an interest in communication and modeling; he is a Research Psychologist at NASA Ames Research Center. Michael Freed is a Computer Scientist with an interest in cognitive architectures and autonomy; he is faculty at the Institute for Human and Machine Cognition and a Senior Research Scientist at NASA Ames Research Center where he leads the Intelligent Architectures group.
Sign up today - FREE
Mendeley saves you time finding and organizing research. Learn more
- All your research in one place
- Add and import papers easily
- Access it anywhere, anytime