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Predictive engineering models based on the EPIC architecture for a multimodal high-performance human-computer interaction task

Published: 01 September 1997 Publication History

Abstract

Engineering models of human performance permit some aspects of usability of interface designs to be predicted from an analysis of the task, and thus they can replace to some extent expensive user-testing data. We successfully predicted human performance in telephone operator tasks with engineering models constructed in the EPIC (Executive Process-Interactive Control) architecture for human information processing, which is especially suited for modeling multimodal, complex tasks, and has demonstrated success in other task domains. Several models were constructed on an a priori basis to represent different hypotheses about how operators coordinate their activities to produce rapid task performance. The models predicted the total time with useful accuracy and clarified some important properties of the task. The best model was based directly on the GOMS analysis of the task and made simple assumptions about the operator's task strategy, suggesting that EPIC models are a feasible approach to predicting performance in multimodal high-performance tasks.

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      cover image ACM Transactions on Computer-Human Interaction
      ACM Transactions on Computer-Human Interaction  Volume 4, Issue 3
      Sept. 1997
      112 pages
      ISSN:1073-0516
      EISSN:1557-7325
      DOI:10.1145/264645
      Issue’s Table of Contents

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 01 September 1997
      Published in TOCHI Volume 4, Issue 3

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      1. cognitive models
      2. usability engineering

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