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Record 3 of 2153
Automating CPM-GOMS
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Author and Affiliation:
John, Bonnie(Carnegie-Mellon Univ., Human-Computer Interaction Inst., Pittsburgh, PA, United States)
Vera, Alonso(NASA Ames Research Center, Moffett Field, CA, United States)
Matessa, Michael(NASA Ames Research Center, Moffett Field, CA, United States)
Freed, Michael(NASA Ames Research Center, Moffett Field, CA, United States)
Remington, Roger(NASA Ames Research Center, Moffett Field, CA, United States)
Abstract: 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 is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the construction of GOMS models have not yet come into general use.
Publication Date: Jan 01, 2002
Document ID:
20030068914
(Acquired Oct 02, 2003)
Subject Category: COMPUTER SYSTEMS
Document Type: Journal Article
Publication Information: Volume 4; No. 1
Contract/Grant/Task Num: NAG2-1472
Financial Sponsor: NASA Ames Research Center; Moffett Field, CA, United States
Organization Source: NASA Ames Research Center; Moffett Field, CA, United States
Description: 4p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Distribution under U.S. Government purpose rights
NASA Terms: PSYCHOMOTOR PERFORMANCE; HUMAN RESOURCES; SCHEDULING; MAN MACHINE SYSTEMS; COMPUTER SYSTEMS DESIGN; BIOTECHNOLOGY; HUMAN-COMPUTER INTERFACE; HUMAN FACTORS ENGINEERING
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