Advanced SearchSearch Tips
Prediction of Human Performance Time to Find Objects on Multi-display Monitors using ACT-R Cognitive Architecture
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Prediction of Human Performance Time to Find Objects on Multi-display Monitors using ACT-R Cognitive Architecture
Oh, Hyungseok; Myung, Rohae; Kim, Sang-Hyeob; Jang, Eun-Hye; Park, Byoung-Jun;
  PDF(new window)
Objective: The aim of this study was to predict human performance time in finding objects on multi-display monitors using ACT-R cognitive architecture. Background: Display monitors are one of the representative interfaces for interaction between people and the system. Nowadays, the use of multi-display monitors is increasing so that it is necessary to research about the interaction between users and the system on multi-display monitors. Method: A cognitive model using ACT-R cognitive architecture was developed for the model-based evaluation on multi-display monitors. To develop the cognitive model, first, an experiment was performed to extract the latency about the where system of ACT-R. Then, a menu selection experiment was performed to develop a human performance model to find objects on multi-display monitors. The validation of the cognitive model was also carried out between the developed ACT-R model and empirical data. Results: As a result, no significant difference on performance time was found between the model and empirical data. Conclusion: The ACT-R cognitive architecture could be extended to model human behavior in the search of objects on multi-display monitors.. Application: This model can help predicting performance time for the model-based usability evaluation in the area of multi-display work environments.
ACT-R;Cognitive architecture;Model-based evaluation;Multi-display monitors;
 Cited by
Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., Lebiere, C. and Qin, Y., An Integrated Theory of Mind, Psychological Review, 111, 1036-1060, 2004. crossref(new window)

Anderson, J.R. and Matessa, M., The rational analysis of categorization and the ACT-R architecture. In M. Oaksford & N. Chater (Eds.) Rational models of cognition, Oxford: Oxford University Press, 197-217, 1998.

Anderson, J.R., Matessa, M. and Lebiere, C., ACT-R: A theory of higher level cognition and its relation to visual attention. Human Computer Interaction, 12(4), 439-462, 1997. crossref(new window)

Byrne, M.D., ACT-R/PM and Menu Selection: Applying a Cognitive Architecture to HCI, International Journal of Human-Computer Studies, Volume 55, Issue 1, 41-84, 2001. crossref(new window)

Byrne, M.D. and Anderson, J.R., Enhancing ACT-R's Perceptual-Motor Abilities. In Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society, Hillsdale, NJ: Lawrence Erlbaum Associates. 1997.

Byrne, M.D. and Anderson, J.R., Perception and action, In J. Anderson and J. Lebiere (Ed), The Atomic Components of Thought, Mahwah, NJ: Lawrence Erlbaum, 167-200, 1998.

Campbell, G.E. and Bolton, A.E., HBR Validation: Integrating Lessons Learned From Multiple Academic Disciplines, Applied Communities, and the AMBR Project. In K. Gluck and R. Pew (Ed), Modeling Human Behavior with Integrated Cognitive Architectures, Hillsdale, NJ: Lawrence Erlbaum Associates, 2005.

Card, S.K., Moran, T.P. and Newell, A., The Psychology of Human Computer Interaction, L. Erlbaum Associates, 1983.

Chung, Y.K., Case Analysis of Multi Display and A Study on Management Interface. Journal of Korea Design Knowledge. 18, 180-189, 2011.

Ehret, B.D., Learning where to look: The acquisition of location knowledge in display-based interaction. Dissertation Abstracts International: Section B: the Sciences & Engineering, 60(10-B), 5239, 2000.

Fleetwood, M.D. and Byrne, M.D., Modeling icon search in ACT-R/PM. Cognitive Systems Research, 3, 25-33, 2002. crossref(new window)

Goodale, M.A. and Milner, A.D., Separate visual Pathways for Perception and Action, Trends in Neurosciences, 15(1), 20-25, 1992. crossref(new window)


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, 1996a. crossref(new window)

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. crossref(new window)

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, pp. 391-438, 1997. crossref(new window)

Laird, J.E., Newell, A. and Rosenbloom, P.S., SOAR: An architecture for general intelligence, Artificial Intelligence, 33, pp. 1-64, 1987. crossref(new window)

Lim, S., Jo, S., Myung, R., Kim, S., Jang, E. and Park, B., ACT-R Predictive Model of Korean text Entry on Touchscreen, Journal of the Ergonomics Society of Korea, 31(2), 291-298, 2012. crossref(new window)

Min, J., Jo, S. and Myung, R., Prediction of Menu Selection on Touchscreen using a Cognitive Architecture: ACT-R, Journal of the Ergonomics Society of Korea, 29(6), 907-914, 2010. crossref(new window)

Salvucci, D.D., Modeling driver behavior in a cognitive architecture. Human Factors, 48, 362-380, 2006. crossref(new window)

Sanders, M.S. and McCormick, E.J., Human factors in Engineering and design, 7th Edition. McGraw-Hill Book Company, NY. 1993.

St. Amant, R., Horton, T.E. and Ritter, F.E., Model-Based Evaluation of Expert Cell Phone Menu Interaction. ACM Transactions on Computer- Human Interaction, Vol. 14, No. 1, Article 1, 2007.

U.S. Department of Defense, Human Factors Engineering Design for Army Material MIL-HDBK 759A, Washington, DC. 1981.