Tutorial 25

GOMS Analysis for Parallel Activities

Bonnie E. John, Carnegie Mellon University
Wayne D. Gray, George Mason University

Monday, May 8

Objective

Participants will learn an extension of GOMS, called CPM-GOMS, that predicts human performance on parallel tasks.

Content

This tutorial presents the basic theoretical concepts of GOMS and CPM-GOMS. GOMS is a method for analyzing human performance in terms of the Goals, Operators, Methods and Selection rules necessary to sequential activities. CPM-GOMS models are especially suited for predicting performance time of skilled users on tasks with overlapping or parallel activities. This tutorial demonstrates how to construct a CPM-GOMS model, how to interpret its predictions, and how to use it for making what-if evaluations of design decisions and for directing design effort. Participants will do computer exercises that illustrate the construction and use of CPM-GOMS models.

Audience

This introductory-level tutorial is intended for practitioners responsible for designing or evaluating computer systems that require users to engage in parallel activities or for researchers who want to use GOMS to analyze such tasks. No background in GOMS modeling or psychology will be assumed. Macintosh experience is desireable, but not required.

Presentation

Lecture, exercises

Instructors

Bonnie E. John is an Assistant Professor in the Departments of Computer Science and Psychology, and the HCI Institute, at Carnegie Mellon University. In her current research, she is extending GOMS-like models to deal with highly interactive environments, learning, and problem solving. Wayne D. Gray is an Associate Professor of Psychology and a Fellow of the Krasnow Institute for Advanced Studies at George Mason University. His current research interests range from cognitive modeling to understanding and designing human-computer interactions.

Keith Instone / instone@acm.org / 95-01-05