Journal of the Ergonomics Society of Korea (대한인간공학회지)

Ergonomics Society of Korea (대한인간공학회)
권호 표지
DOI QR코드

DOI QR Code

Revised Computational-GOMS Model for Drag Activity

  • Lee, Yong-Ho (Department of Industrial Management Engineering, Korea University) ;
  • Jeon, Young-Joo (Department of Industrial Management Engineering, Korea University) ;
  • Myung, Ro-Hae (Department of Industrial Management Engineering, Korea University)
  • Received : 2011.02.09
  • Accepted : 2011.03.16
  • Published : 2011.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

The existing GOMS model overestimates the performance time of mouse activities because it describes them in a serial sequence. However, parallel movements of eye and hand(eye-hand coordination) have been dominant in mouse activities and this eye-hand coordination is the main factor for the overestimation of performance time. In this study, therefore, the revised CGOMSL model was developed to implement eye-hand coordination to the mouse activity to overcome one of the limitations of GOMS model, the lack of capability for parallel processing. The suggested revised CGOMSL model for drag activity, as an example for one of mouse activities in this study, begins visual search processing before a hand movement but ends the visual search processing with the hand movement in the same time. The results show that the revised CGOMSL model made the prediction of human performance more accurately than the existing GOMS model. In other words, one of the limitations of GOMS model, the incapability of parallel processing, could be overcome with the revised CGOMSL model so that the performance time should be more accurately predicted.

Keywords

References

  1. Anderson, J. R. and Lebiere, C., Atomic Components of Thought, Lawrence Erlbaum Associates, New Jersey, London, 1998.
  2. Back, J., Myung, R. and Yoon, D., Applying CPM-GOMS Analysis for predicting and Explaining Two-Handed Korean Text Entry Task on Mobile Phone, Human Factors and Ergonomics Society Annual Meeting Proceedings, Human Performance Modeling, 977-981, 2010.
  3. Bennett, J., Butler, K. and Whiteside, J., Usability Engineering, A tutorial presented at CHI, '89 Conference on Human Factors in Computing Systems, Austin, TX, April 30-May 5, 1989.
  4. Bieg, H., Reiterer, H. and Bulthoff, H. H., Eye and Pointer Coordination in Search and Selection Tasks, ETRA2010, Austin, TX, March 22-24, 2010.
  5. Bothell, D., ACT-R 6.0 Reference Manual. From the ACT-R Web site: http://act-r.psy.cmu.edu/actr6/reference-manual.pdf, 2007.
  6. Card, S. K., Moran, T. P. and Newell, A., Computer Text-Editing: An Information-Processing Analysis of a Routine Cognitive Skill, Cognitive Psychology, 12, 32-74, 1980b. https://doi.org/10.1016/0010-0285(80)90003-1
  7. Card, S. K., Moran, T. P. and Newell, A., The Psychology of Human-Computer Interaction, L. Erlbaum Associates, 1983.
  8. Fischer, B. and Rogal, L., Eye Hand Coordination in Man: A Reaction Time Study, Biological Cybernetics, 55, 253-261, 1986. https://doi.org/10.1007/BF00355600
  9. Galitz, W., The Essential Guide to User Interface Design, 2nd ed., Wiley, 2002.
  10. Gillan, D. J., Holden, K. and Adam, S., How does Fitts' Law Fit Pointing and Dragging?, Proceedings of the SIGCHI conference on Human factors in computing systems, New York, 227-234, 1990.
  11. Gould, J. D., Boies, S. J., Levy, S., Richards, J. T. and Schoonard, J., The 1984 Olympic Message Systme: A Test of Behavioral Principles of System Design. Communications of the ACM, 758-769, 1987.
  12. Gould, J. D. and Lewis, C., Designing for Usability: Key Principles and What Designers Think., Communications of the ACM, 300-311, 1985.
  13. Gray, W. D., Spohrer, J. C. and Green, T. R. G., End-user programming languages: The CHI '92 workshop report., SIGCHI Bulletin, 25(2), 46-50, 1993. https://doi.org/10.1145/155804.155818
  14. Gribble, P. L., Everling, S., Ford, K. and Mattar, A., Hand Eye Coordination for Rapid Pointing Movements, Experimental Brain Research, 145, 372-382, 2002. https://doi.org/10.1007/s00221-002-1122-9
  15. Henrik, T., Measuring Website Usability for Visually Impaired People - A Modified GOMS Analysis, Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility, Portland, Oregon, 55-62, 2006.
  16. Holleis, P., Otto, F., Hubmann, H. and Schmidt, A., Keystroke-Level Model for advanced Mobile Phone Interaction, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, San Jose, California, 1505-1514, 2007. https://doi.org/10.1145/1240624.1240851
  17. Ivory, M. Y. and Hearst, M. A., Improving Web Site Design, IEEE Internet Computing, vol. 6, no. 2, 56-63, 2002. https://doi.org/10.1109/4236.991444
  18. Jeon, Y. J., Revised GOMS Operator for Drag and Drop, Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting, San Francisco, California, 1742-1746, 2010.
  19. John, B. E., Contributions to Engineering Models of Human-Computer Interaction, Doctoral Dissertation, Canegie Mellon University, Pittsburgh, 1988.
  20. John, B. E., "Why GOMS?", ACM Interaction, NY, USA, 2(4), 80-89, 1995. https://doi.org/10.1145/225362.225374
  21. John, B. E. and Newell, A., Cumulating the Science of HCI: From S-R Compatibility to Transcription Typing, ACM SIHCHI Bulletin, 20, 109-114, 1989. https://doi.org/10.1145/67450.67472
  22. John, B. E. and Kieras, D. E., Using GOMS for User Interface Design and Evaluation: Which Technique?, ACM Transactions on Computer- Human Interaction, 3(4), 287-319, Dec, 1996a. https://doi.org/10.1145/235833.236050
  23. John, B. E, and Kieras, D. E., The GOMS Family of User Interface Analysis Techniques: Comparison and Contrast, ACM Transactions on Computer-Human Interaction, 3(4), 320-350, 1996b. https://doi.org/10.1145/235833.236054
  24. Kieras, D. E., A Guide to GOMS Model Usability Evaluation using NGOMSL, The Handbook of Human-Computer Interaction. 2nd edition, North-Holland, Amsterdam, 1996.
  25. Kieras, D. E., A Guide to GOMS Model Usability Evaluation using GOMSL and GLEAN3, Technical report, University of Michigan, Ann Arbor, MI., 1999.
  26. Kieras, D. E. and Knudsen, K., Comprehensive Computational GOMS Modeling with GLEAN. In Proceedings of BRIMS 2006, Baltimore, May 16-18, 2006.
  27. Kieras, D. E. and Meyer D. E., An Overview of the EPIC Architecture for Cognition and Performance with Application to Human-Computer Interaction, Human-Computer Interaction, 12, 391-438, 1997. https://doi.org/10.1207/s15327051hci1204_4
  28. Kieras, D. E., Scott, D. W. and Meyer D. E., Predictive Engineering Models Using the EPIC Architecture for a High-Performance Task, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 11-18, Denver, Colorado, United States, 1995.
  29. Landauer, T. K., The Trouble With Computers: Usefulness, Usability, and Productivity. MIT Press, 1995.
  30. MacKenzie, I. S., Movement time Prediction in Human-computer Interfaces, Human-Computer Interaction (2nd ed.), 483-493. Kaufmann, Losaltos, CA., R. M. Baecker, W. A. S. Buxton, J. Grudin and S. Greenberg (Eds.), 1992.
  31. MacKenzie, I. S. and Soukoreff, R. W., Text Entry for Mobile Computing: Models and Methods, Theory and Practice, Human-Computer Interaction, 17, 147-198, 2002. https://doi.org/10.1207/S15327051HCI172&3_2
  32. Myung, R., Keystroke-level Analysis of Korean Test Entry Methods on Mobile Phones, International Journal of Human-Computer Studies, 60, 545-563, 2004. https://doi.org/10.1016/j.ijhcs.2003.10.002
  33. Newell, A., Unified Theories of Cognition, Harvard University Press, Cambridge, 1990.
  34. Olson, J. R. and Nilsen, E., Anlaysis of the Cognition Involved in Spreadsheet software Interaction, Human-Computer Interaction, 3, 309-350, 1988.
  35. Olson, J. R. and Olson, G. M., The Growth of Cognitive Modeling in Human-Computer Interaction since GOMS, Human-Computer Interaction, 5, 221-265, 1990. https://doi.org/10.1207/s15327051hci0502&3_4
  36. Parush, A., Nadir, R. and Shtub, A., Evaluating the layout of graphical user interface screens: Validation of a numerical, computerized model. International Journal of Human Com-puter Interaction, 10(4), 343-360, 1998. https://doi.org/10.1207/s15327590ijhc1004_3
  37. Puerta, A. and Maulsby, D., MOBI-D: A Model-Based Development Environment for User-Centered Design, Proceedings of CHI '97, Atlanta, 4-5, 1997.
  38. Ritter, F. E, Shadbolt, N. R., Elliman, D., Young, R., Gobet, F. and Baxter, G. D., Techniques for Modeling Human Performance in Synthetic Environments: A Supplementary Review, Wright-Patterson Air Force Base, 2001.
  39. Salvucci, D. D. and Goldberg, J. H., Identifying Fixations and Saccades in Eye-Tracking Protocols, Proceedings of the EyeTracking Research and Applications Symposium, Palm Beach Gardens, Florida, 71-78, 2000.
  40. Smith, B. A., Ho, J., Ark, W. and Zhai, S., Hand Eye Coordination Patterns in Target Selection, Proceedings of Eye Tracking Research & Applications Symposium 2000, Palm Beach Garden, FL, USA, 2000.
  41. Takahiro, H. and Kazuyuki, S, Different Memory Types for Generating Saccades at Different Stages of Learning, Neuroscience Research, 55(3), 271-284, 2006. https://doi.org/10.1016/j.neures.2006.03.009
  42. Viviani, P., Baud-Bovy, G. and Redolfi, M., Perceiving and Tracking Kinaesthetic Stimuli: Further Evidence of Motor Perceptual Interactions, Journal of experimental psychology, 23(4), 1232-1252, 1997.
  43. Whisenand, T. G. and Emurian, H. H., Analysis of cursor movements with a mouse, Proceedings of HCI International '97, San Francisco, USA, 533-536, 1997.
  44. Wiecha, C. and Boles, S., Generating User Interfaces: Principles and Use of It Style Rules, Proceedings of the Third Annual ACM SIGGRAPH Symposium on User Interface Software and Technology, 21-30, 1990.
  45. Williams, K. E., Computer-aided GOMS: A Description and Evaluation of a Tool that Integrates Existing Research for Modeling Human-Computer Interaction, International Journal of Human-Computer Interaction, 18, 39-58, 2005. https://doi.org/10.1207/s15327590ijhc1801_3

Cited by

  1. Extracting Flick Operator for Predicting Performance by GOMS Model in Small Touch Screen vol.32, pp.2, 2013, https://doi.org/10.5143/JESK.2013.32.2.179
  2. A Unit Touch Gesture Model of Performance Time Prediction for Mobile Devices vol.35, pp.4, 2016, https://doi.org/10.5143/JESK.2016.35.4.277