Coglunch - 10 October, 2002
Automating Human Performance Modeling at the Millisecond Level
Alonso Vera
Senior Research Scientist at NASA Ames Research Center
and Senior Systems Scientist at Carnegie Mellon University
CPM-GOMS is a modeling method that combines the task decomposition of
a GOMS analysis with a model of human resource usage at the level of
cognitive, perceptual, and motor operations. CPM-GOMS models have made
accurate predictions about skilled user behavior in routine tasks, but
developing such models has been tedious and error-prone. We describe
a process for automatically generating CPM-GOMS models from a
hierarchical task decomposition expressed in a computational modeling
tool called Apex, 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 models
of automated teller machine interaction and use of a CAD tool. The
models show 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) in order 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 becomes dramatically easier. CPM-GOMS is a powerful modeling
method that may have remained underused because of expertise and labor
required. Apex-CPM provides a computational engine for CPM-GOMS,
greatly facilitating the modeling of human performance and the
millisecond level.
Last modified: Tue Feb 28 11:26:25 PST 2006 by emma@csli.stanford.edu