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extended-abstract

Human performance modeling for all: importing UI prototypes into cogtool

Published:10 April 2010Publication History

ABSTRACT

UI designers use a variety of prototyping tools, from paper and pencil sketching, to drag-and-drop mock-up tools (e.g., Balsamiq Mockups), to sophisticated suites of modeling tools and toolkits (e.g., iRise or dijit, the dojo GUI toolkit ). Many projects would benefit from quickly analyzing prototypes at an early stage without the effort of bringing in users for empirical tests. Most analysis tools, however (e.g., AutoCWW [1], Bloodhound [2], and CogTool [4]), require prototypes to be in their own format, which forces the designer to re-do the prototypes in order to analyze them. Our work is a step toward allowing the CogTool analysis tools to import from many different prototyping tools, so designers will have a path to quick usability analysis without changing the way they currently express their preliminary designs.

References

  1. Blackmon, M. H., Kitajima, M., & Polson, P. G. (2005). Tool for accurately predicting website navigation problems, non-problems, problem severity, and effectiveness of repairs. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '05. ACM, New York, NY, 31--40. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Chi, E. H., Rosien, A., Supattanasiri, G., Williams, A., Royer, C., Chow, C., Robles, E., Dalal, B., Chen, J., & Cousins, S. (2003). The bloodhound project: automating discovery of web usability issues using the InfoScent simulator. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '03. ACM, New York, NY, 505--512. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Feary, M. (2007) Automatic Detection of Interaction Vulnerabilities in an Executable Specification. Lecture Notes in Computer Science, (4562), Berlin: Springer. 487--496 Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. John, B. E., Prevas, K., Salvucci, D. D., & Koedinger, K. (2004). Predictive human performance modeling made easy. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '04. ACM, New York, NY, 455--462. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Teo L., & John B. E. (2008). Towards a Tool for Predicting Goal-directed Exploratory Behavior. In Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting, HFES, Santa Monica, CA, 950--954.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Human performance modeling for all: importing UI prototypes into cogtool

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