Shedding light on the graph schema: Perceptual features versus invariant structure

Psychonomic Bulletin and Review

Volumn 15, Issue 4, 2008, Pages 757-762

  Ratwani, Raj M ^a   Trafton, J Gregory ^b  

^a GEORGE MASON UNIVERSITY   (United States)

^b NAVAL RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADOLESCENT; ADULT; ARTICLE; COMPARATIVE STUDY; COMPREHENSION; COMPUTER GRAPHICS; DISCRIMINATION LEARNING; FEMALE; HUMAN; MALE; ORIENTATION; PATTERN RECOGNITION; PROBLEM SOLVING; REACTION TIME; THEORETICAL MODEL;

ADOLESCENT; ADULT; COMPREHENSION; COMPUTER GRAPHICS; DISCRIMINATION LEARNING; FEMALE; HUMANS; MALE; MODELS, THEORETICAL; ORIENTATION; PATTERN RECOGNITION, VISUAL; PROBLEM SOLVING; REACTION TIME; YOUNG ADULT;

EID: 50949117246     PISSN: 10699384     EISSN: 15315320     Source Type: Journal    
DOI: 10.3758/PBR.15.4.757     Document Type: Article

References (16)

1. BERNARDO, A. B. I. (1994). Problem-specific information and the development of problem-type schemata. Journal of Experimental Psychology: Learning, Memory, & Cognition, 20, 379-395.
2. GATTIS, M. (2002). Structure mapping in spatial reasoning. Cognitive Development, 17, 1157-1183.
3. HENDERSON, J. M., & HOLLINGWORTH, A. (1999). High-level scene perception. Annual Review of Psychology, 50, 243-271.
4. KOSSLYN, S. M. (1989). Understanding charts and graphs. Applied Cognitive Psychology, 3, 185-225.
5. LEWANDOWSKY, S., & BEHRENS, J. T. (1999). Statistical graphs and maps. In F. T. Durso, R. S. Nickerson, R. W. Schvaneveldt, S. T. Dumais, D. S. Lindsay, & M. T. H. Chi (Eds.), Handbook of applied cognition (pp. 513-549). Chichester, U.K.: Wiley.
6. LOHSE, G. L. (1993). A cognitive model for understanding graphical perception. Human-Computer Interaction, 8, 353-388.
7. LOS, S. A. (1996). On the origin of mixing costs: Exploring information processing in pure and mixed blocks of trials. Acta Psychologica, 94, 145-188.
8. LOS, S. A. (1999). Identifying stimuli of different perceptual categories in mixed blocks of trials: Evidence for cost in switching between computational processes. Journal of Experimental Psychology: Human Perception & Performance, 25, 3-23.
9. MONSELL, S. (2003). Task switching. Trends in Cognitive Sciences, 7, 134-140.
10. PEEBLES, D., & CHENG, P. C.-H. (2001). Graph-based reasoning: From task analysis to cognitive explanation. In J. D. Moore & K. Stenning (Eds.), Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society (pp. 762-767). Mahwah, NJ: Erlbaum.
11. PEEBLES, D., & CHENG, P. C.-H. (2003). Modeling the effect of task and graphical representation on response latency in a graph reading task. Human Factors, 45, 28-46.
12. PINKER, S. (1990). A theory of graph comprehension. In R. Freedle (Ed.), Artificial intelligence and the future of testing (pp. 73-126). Hillsdale, NJ: Erlbaum.
13. POTTER, M. C. (1993). Very short-term conceptual memory. Memory & Cognition, 21, 156-161.
14. SHAH, P., & CARPENTER, P. A. (1995). Conceptual limitations in comprehending line graphs. Journal of Experimental Psychology: General, 124, 43-61.
15. SIMKIN, D. K., & HASTIE, R. (1987). An information processing analysis of graph perception. Journal of the American Statistical Association, 82, 454-465.
16. ZACKS, J., & TVERSKY, B. (1999). Bars and lines: A study of graphic communication. Memory & Cognition, 27, 1073-1079.