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

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.

REFERENCES

• 1: ABRAMS, R. A., MEYER, D. E., AND KORNBLUM, S. 1990. Eye-hand coordination: eculomotor control in rapid aimed limb movements. J. Exper. Psychol. Human Percept. Perf. 16, 2, 248-267.
• 2: ANDERSON, J.R. 1976. Language, Memory, and Thought. Lawrence Erlbaum, Hillsdale, N.J.
• 3: ANDERSON, J. R. 1987. Skill acquisition: Compilation of weak-method problem solutions. Psychol. Rev. 94, 192-210.
• 4: ANDERSON, J.R. 1993. Rules of the Mind. Lawrence Erlbaum, Hillsdale, N.J.
• 5: BOVAIR, S., KIERAS, D. E., AND POLSON, P.G. 1990. The acquisition and performance of text editing skill: A cognitive complexity analysis. Human-Comput. Interact. 5, 1-48.
• 6: Stuart K. Card , Allen Newell , Thomas P. Moran, The Psychology of Human-Computer Interaction, Lawrence Erlbaum Associates, Inc., Mahwah, NJ, 1983
• 7: GRAY, W. D., JOHN, B. E., AND ATWOOD, M. E. 1993. Project Ernestine: A validation of GeMS for prediction and explanation of real-world task performance. Human-Comput. Interact. 8, 3, 209-237.
• 8: HALLETT, P.E. 1986. Eye movements. In Handbook of Perception and Human Performance, K. R. Boff, L. Kaufman, and J. P. Thomas, Eds. Vol. 1. Wiley, New York, 10-1-10-112.
• 9: JOHN, B. E. 1996. TYPIST: A theory of performance in skilled typing. Human-Comput. Interact. 11,321-355.
• 10: Bonnie E. John , David E. Kieras, Using GOMS for user interface design and evaluation: which technique?, ACM Transactions on Computer-Human Interaction (TOCHI), v.3 n.4, p.287-319, Dec. 1996 [doi>10.1145/235833.236050]
• 11: Bonnie E. John , David E. Kieras, The GOMS family of user interface analysis techniques: comparison and contrast, ACM Transactions on Computer-Human Interaction (TOCHI), v.3 n.4, p.320-351, Dec. 1996 [doi>10.1145/235833.236054]
• 12: KIERAS, D. E. 1988. Towards a practical GOMS model methodology for user interface design. In Handbook of Human-Computer Interaction, M. Helander, Ed. North-Holland Elsevier, Amsterdam, 135-158.
• 13: KIERAS, D. E. 1998. A Guide to GOMS model usability evaluation using NGOMSL. In Handbook of Human-Computer Interaction, M. Helander, T. Landauer, and P. Prabhu, Eds. 2nd ed. North-Holland, Amsterdam. To be published.
• 14: KIERAS, D. E. ANn MEYER, D.E. 1997. An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Human-Comput. Interact. To be published.
• 15: KIERAS, D. E. ANn POLSON, P. G. 1985. An approach to the formal analysis of user complexity. Int. J. Man-Mach. Stud. 22, 365-394.
• 16: David E. Kieras , Scott D. Wood , David E. Meyer, Predictive engineering models using the EPIC architecture for a high-performance task, Proceedings of the SIGCHI conference on Human factors in computing systems, p.11-18, May 07-11, 1995, Denver, Colorado, United States [doi>10.1145/223904.223906]
• 17: John Laird , Paul Rosenbloom , Allen Newell, Universal subgoaling and chunking: the automatic generation and learning of goal hierarchies, Kluwer Academic Publishers, Norwell, MA, 1986
• 18: MEYER, D. E. ANn KmRAS, D. E. 1997a. A computational theory of executive cognitive processes and multiple-task performance: Part 1. Basic mechanisms. Psychol. Rev. 104, 3-65.
• 19: MEYER, D. E. ANn KmRAS, D. E. 1997b. A computational theory of executive cognitive processes and multiple-task performance: Part 2. Accounts of psychological refractory-period phenomena. Psychol. Rev. To be published.
• 20: MCMILLAN, G. R., BEEWS, D., SALAS, E., STRUB, M. H., SUTTON, R., ANn VAN BREDA, L. 1989. Applications of Human Performance Models to System Design. Plenum Press, New York.
• 21: ROSENBAUM, D.h. 1991. Human Motor Control. Academic Press, New York.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human information processing

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)

General Terms:
Human Factors

Keywords:
cognitive models, usability engineering