Modeling the effect of task and graphical representation on response latency in a graph reading task

Human Factors

Volumn 45, Issue 1, 2003, Pages 28-46

  Peebles, David ^a   Cheng, Peter C H ^b  

^a UNIVERSITY OF HUDDERSFIELD   (United Kingdom)

^b UNIVERSITY OF SUSSEX   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COSTS; HUMAN ENGINEERING; RESEARCH; VISION;

GRAPH-READING TASK;

EYE MOVEMENTS;

ARTICLE; CALCULATION; LATENT PERIOD; MEDICAL INFORMATION; MEDICAL PRACTICE; READING; TASK PERFORMANCE; VISUAL DISPLAY UNIT;

EID: 0037477688     PISSN: 00187208     EISSN: None     Source Type: Journal    
DOI: 10.1518/hfes.45.1.28.27225     Document Type: Article

References (36)

1. Anderson, J. R. (1993). Rules of the mind. Hillsdale, NJ: Erlbaum.
2. Anderson, J. R., & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Erlbaum.
3. Byrne, M. D. (2001). ACT-R/PM and menu selection: Applying a cognitive architecture to HCI. International Journal of Human-Computer Studies, 55, 41-84.
4. Byrne, M. D., & Anderson, J. R. (1998). Perception and action. In J. R. Anderson & C. Lebiere (Eds.), The atomic components of thought (pp. 167-200). Mahwah, NJ: Erlbaum.
5. Card, S. K., Moran, T. P., & Newell, A. (1983). The psychology of human-computer interaction. Hillsdale, NJ: Erlbaum.
6. Carpenter, P. A., & Shah, P. (1998). A model of the perceptual and conceptual processes in graph comprehension. Journal of Experimental Psychology: Applied, 4, 75-100.
7. Casner, S. M. (1991). A task-analytic approach to the automated design of graphic presentations. ACM Transactions on Graphics, 10, 111-151.
8. Chong, R. S., & Laird, J. E. (1997). Identifying dual-task executive process knowledge using EPIC-Soar. In Proceedings of the 19th Annual Conference of the Cognitive Science Society (pp. 107-112). Mahwah, NJ: Erlbaum.
9. Cleveland, W. S., & McGill, R. (1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79, 531-554.
10. Doane, S. M., & Sohn, Y. W. (2000). ADAPT: A predictive cognitive model of user visual attention and action planning. User Modeling and User-Adapted Interaction, 10, 1-45.
11. Ehret, B. D. (2000). Learning where to look: The acquisition of location knowledge in display-based interaction (Doctoral dissertation. George Mason University, 1999). Dissertation Abstracts International: Section B: Sciences and Engineering, 60, 5239.
12. Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381-391.
13. Gattis, M., & Holyoak, K. (1996). Mapping conceptual to spatial relations in visual reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 231-239.
14. Gray, W. D. (2000). The nature and processing of errors in interactive behavior. Cognitive Science, 11, 205-248.
15. Gray, W. D., & Altmann, E. M. (2001). Cognitive modeling and human-computer interaction. In W. Karwowski (Ed.), International encyclopedia of ergonomics and human factors (pp. 387-391). New York: Taylor & Francis.
16. Gray, W. D., & Boehm-Davis, D. A. (2000). Milliseconds matter: An introduction to microstrategies and to their use in describing and predicting interactive behavior. Journal of Experimental Psychology: Applied, 6, 322-335.
17. John, B. E. (1990). Extensions of GOMS analyses to expert performance requiring perception of dynamic visual and auditory information. In Proceedings of ACM CHI'90 Conference on Human Factors in Computing Systems (pp. 107-115). New York: Association for Computing Machinery.
18. John, B. E., & Kieras, D. E. (1994). The GOMS family of analysis techniques: Tools for design and evaluation (Tech. Report CMU-HCII-94-106). Pittsburgh: Carnegie Mellon University, Human-Computer Interaction Institute.
19. Kieras, D. E., & Meyer, D. E. (1997). An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Human-Computer Interaction, 12, 391-438.
20. Kintsch, W. (1988). The use of knowledge in discourse processing: A construction-integration model. Psychological Review, 95, 163-182.
21. Kintsch, W. (1998). Comprehension: A paradigm for cognition. Cambridge, England: Cambridge University Press.
22. Kosslyn, S. M. (1989). Understanding charts and graphs. Applied Cognitive Psychology, 3, 185-226.
23. Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65-100.
24. Lohse, G. L. (1993). A cognitive model for understanding graphical perception. Human-Computer Interaction, 8, 353-388.
25. Olson, J. R., & Olson, G. M. (1990). The growth of cognitive modeling in human-computer interaction since GOMS. Human-Computer Interaction, 5, 221-265.
26. Peebles, D., & Cheng, P. C.-H. (2001). Graph-based reasoning: From task analysis to cognitive explanation. In Proceedings of the 23rd Annual Conference of the Cognitive Science Society (pp. 762-767). Mahwah, NJ: Erlbaum.
27. Peebles, D., & Cheng, P. C.-H. (2002). Extending task analytic models of graph-based reasoning: A cognitive model of problem solving with Cartesian graphs in ACT-R/PM. Cognitive Systems Research, 3, 77-86.
28. Peebles, D., Cheng, P. C.-H., & Shadbolt, N. (1999). Multiple processes in graph-based reasoning. In Proceedings of the 21st Annual Conference of the Cognitive Science Society (pp. 531-536). Mahwah, NJ: Erlbaum.
29. Pinker, S. (1990). A theory of graph comprehension. In R. Freedle (Ed.), Artificial intelligence and the future of testing (pp. 73-126). Mahwah, NJ: Erlbaum.
30. Savucci, D. D. (2001a). An integrated model of eye movements and visual encoding. Cognitive Systems Research, 1, 201-220.
31. Savucci, D. D. (2001b). Predicting the effects of in-car interface use on driver performance: An integrated model approach. International Journal of Human-Computer Studies, 55, 85-107.
32. Schoelles, M. J., & Gray, W. D. (2000). Argus Prime: Modelling emergent microstrategies in a complex simulated task environment. In Proceedings of the 3rd International Conference on Cognitive Modelling (pp. 260-270). Veenendal, Netherlands: Universal.
33. Shah, P., & Carpenter, P. A. (1995). Conceptual limitations in comprehending line graphs. Journal of Experimental Psychology: General, 124, 43-62.
34. Tufte, E. R. (1983). The visual display of quantitative information. Cheshire, CT: Graphics.
35. Zhang, J. (1996). A representational analysis of relational information displays. International Journal of Human-Computer Studies, 45, 59-74.
36. Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science, 21, 179-217.