Supporting efficient development of cognitive models at multiple skill levels: exploring recent advances in constraint-based modeling

This paper presents X-PRT, a new cognitive modeling tool supporting activities ranging from interface design to basic cognitive research. X-PRT provides a graphical model development environment for the CORE constraint-based cognitive modeling engine [7,13,21]. X-PRT comprises a novel feature set: (a) it supports the automatic generation of predictive models at multiple skill levels from a single task-specification, (b) it supports a comprehensive set of modeling activities, and (c) it supports compositional reuse of existing cognitive/perceptual/motor skills by transforming high-level, hierarchical task descriptions into detailed performance predictions. Task hierarchies play a central role in X-PRT, serving as the organizing construct for task knowledge, the locus for compositionality, and the cognitive structures over which the learning theory is predicated. Empirical evidence supports the role of task hierarchies in routine skill acquisition.

[1]  John R Anderson,et al.  An integrated theory of the mind. , 2004, Psychological review.

[2]  Neil T. Heffernan,et al.  Opening the Door to Non-programmers: Authoring Intelligent Tutor Behavior by Demonstration , 2004, Intelligent Tutoring Systems.

[3]  Kenneth R. Koedinger,et al.  Predictive human performance modeling made easy , 2004, CHI.

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

[5]  Richard L. Lewis,et al.  A constraint satisfaction approach to predicting skilled interactive cognition , 2004, CHI.

[6]  Karen Holtzblatt,et al.  Contextual design , 1997, INTR.

[7]  Bonnie E. John,et al.  Comparison of GOMS analysis methods , 1998, CHI Conference Summary.

[8]  Michael Freed,et al.  Automating CPM-GOMS , 2002, CHI.

[9]  Michael E. Atwood,et al.  Project Ernestine: Validating a GOMS Analysis for Predicting and Explaining Real-World Task Performance , 1993, Hum. Comput. Interact..

[10]  Frank E. Ritter,et al.  Embodied models as simulated users: introduction to this special issue on using cognitive models to improve interface design , 2001, Int. J. Hum. Comput. Stud..

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

[12]  Frank E. Ritter,et al.  A User Modeling Design Tool Based on a Cognitive Architecture for Comparing Interfaces , 2002, CADUI.

[13]  Johanna D. Moore,et al.  Proceedings of the Conference on Human Factors in Computing Systems , 1989 .

[14]  Anthony J. Hornof,et al.  GLEAN: a computer-based tool for rapid GOMS model usability evaluation of user interface designs , 1995, UIST '95.

[15]  Richard Gong.  Validating and refining the GOMS model methodology for software user interface design and evaluation , 1993 .

[16]  Frank E. Ritter,et al.  Automated GOMS-to-ACT-R model generation (Best applied paper) , 2004, ICCM.

[17]  Frank J. Lee,et al.  Production Compilation: A Simple Mechanism to Model Complex Skill Acquisition , 2003, Hum. Factors.

[18]  Karen Holtzblatt,et al.  Contextual design , 1997, INTR.

[19]  Frank E. Ritter,et al.  Automated GOMS – to – ACT-R Model Generation , 2004 .

[20]  Frank J. Lee,et al.  Simple cognitive modeling in a complex cognitive architecture , 2003, CHI '03.

[21]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[22]  Richard L. Lewis,et al.  Cognitive Constraint Modeling: A Formal Approach to Supporting Reasoning About Behavior , 2004 .

[23]  Gregg R. Yost.  TAQL: a problem space tool for expert system development , 1992 .

[24]  Richard L. Lewis,et al.  A Constraint-Based Approach to Understanding the Composition of Skill , 2004, ICCM.