The role of cognitive task analysis in the application of predictive models of human performance

Predictive modeling of human performance as long been applied in human factors engineering. In the meantime, computational cognitive architecture models have developed a theoretically coherent and sophisticated basis for advanced predictive modeling of human performance. Key is a distinction between fixed task-independent architectural mechanisms and task-specific strategies that control the architecture. Applying the new cognitive modeling approaches to system design problems requires a method for identifying the task strategy, but new results suggest that humans choose task strategies that incorporate optional features that are not based on either architectural constraints or task demands. These optional features strongly influence performance, but cannot be identified by conventional task analysis methods. A heuristic is presented for obtained useful task performance predictions based on characterizing the fast-possible and slowest-reasonable combinations of optional task strategy aspects. The heuristic is illustrated with results from a somewhat complex laboratory task.

[1]  Edward F. Moore,et al.  Gedanken-Experiments on Sequential Machines , 1956 .

[2]  Alan D Samples,et al.  SOAR Architecture , 1985 .

[3]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[4]  K. Ronald Laughery.  Micro SAINT — A Tool for Modeling Human Performance in Systems , 1989 .

[5]  Robert Sutton,et al.  Applications of Human Performance Models to System Design , 1989, Springer US.

[6]  A. O. Dick,et al.  The Human Operator Simulator (HOS-IV) , 1989 .

[7]  Beverly M. Huey,et al.  Human Performance Models for Computer-Aided Engineering , 1990 .

[8]  David E. Kieras,et al.  The Acquisition and Performance of Text-Editing Skill: A Cognitive Complexity Analysis , 1990, Hum. Comput. Interact..

[9]  Constance L. Heitmeyer,et al.  Direct Manipulation and Intermittent Automation in Advanced Cockpits , 1992 .

[10]  Manuel A. Pérez-Quiñones,et al.  Evaluating two aspects of direct manipulation in advanced cockpits , 1992, CHI.

[11]  John R. Anderson,et al.  Rules of the Mind , 1993 .

[12]  David E. Kieras,et al.  Automating interface evaluation , 1994, CHI '94.

[13]  Kevin M. Corker,et al.  Man-Machine Design and Analysis System (MIDAS) Applied to a Computer-Based Procedure-Aiding System , 1994 .

[14]  David E. Kieras,et al.  Using GOMS for user interface design and evaluation: which technique? , 1996, TCHI.

[15]  David E. Kieras,et al.  The GOMS family of user interface analysis techniques: comparison and contrast , 1996, TCHI.

[16]  David E. Kieras,et al.  An Overview of the EPIC Architecture for Cognition and Performance With Application to Human-Computer Interaction , 1997, Hum. Comput. Interact..

[17]  David E. Kieras,et al.  Précis to a practical unified theory of cognition and action: Some lessons from EPIC computational models of human multiple-task performance , 1997 .

[18]  D E Kieras,et al.  A computational theory of executive cognitive processes and multiple-task performance: Part 1. Basic mechanisms. , 1997, Psychological review.

[19]  David E. Kieras,et al.  A computational theory of executive cognitive processes and multiple-task performance: Part 2. Accounts of psychological refractory-period phenomena. , 1997 .

[20]  David E. Kieras,et al.  Predictive engineering models based on the EPIC architecture for a multimodal high-performance human-computer interaction task , 1997, TCHI.