Benefitting InfoVis with visual difficulties

IEEE Transactions on Visualization and Computer Graphics

Volumn 17, Issue 12, 2011, Pages 2213-2222

  Hullman, Jessica ^a   Adar, Eytan ^a   Shah, Priti ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

active processing; cognitive efficiency; Desirable difficulites; engagement; individual differences

Indexed keywords

ACTIVE PROCESSING; COGNITIVE EFFICIENCY; DESIRABLE DIFFICULITES; ENGAGEMENT; INDIVIDUAL DIFFERENCES;

DESIGN; EFFICIENCY; INFORMATION ANALYSIS; INFORMATION SYSTEMS; RESEARCH;

VISUALIZATION;

ARTICLE; COGNITION; COMPREHENSION; COMPUTER GRAPHICS; COMPUTER INTERFACE; HUMAN; LEARNING; PSYCHOLOGICAL MODEL; VISION;

COGNITION; COMPREHENSION; COMPUTER GRAPHICS; HUMANS; LEARNING; MODELS, PSYCHOLOGICAL; USER-COMPUTER INTERFACE; VISUAL PERCEPTION;

EID: 80855141831     PISSN: 10772626     EISSN: None     Source Type: Journal    
DOI: 10.1109/TVCG.2011.175     Document Type: Article

References (70)

1. C. Ahlberg and E. Wistrand, IVEE: an Information Visualization and Exploration Environment, in Proc. of Vis.'95, 1995.
2. A.L. Alter, D.M. Oppenheimer, N. Epley, and R.N. Eyre, Overcoming intuition: Metacognitive difficulty activates analytic reasoning, J. of Exp. Psych.-Gen., vol. 136, no. 4, 2007.
3. A. L. Alter and D. M. Oppenheimer, Uniting the Tribes of Fluency to Form a Metacognitive Nation, Personality and Social Psychology Review, vol. 13, no. 3, 2009.
4. D. Archambault, H. C. Purchase, and B. Pinaud, Animation, Small Multiples, and the Effect of Mental Map Preservation in Dynamic Graphs, IEEE TVCG, vol. 17, no. 4, 2011.
5. S. Bateman, R. L. Mandryk, C. Gutwin, A. Genest, D. McDine, and C. Brooks, Useful junk?: the effects of visual embellishment on comprehension and memorability of charts, CHI, 2010.
6. G. Beenen et al., Using social psychology to motivate contributions to online communities, in CSCW, 2004.
7. E. Bertini, A. Perer, C. Plaisant, and G. Santucci, BELIV'08: Beyond time and errors: novel evaluation methods for information visualization (Workshop), CHI, 2008.
8. R. A. Bjork. Memory and metamemory considerations in the training of human beings. In J. Metcalfe et al. (Eds.), Metacognition: Knowing about knowing Cambridge, MA: MIT Press, 1994.
9. E.L. Bjork & R.A. Bjork, Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher,et al. (Eds.), Psychology and the real world: Essays illustrating fundamental contributions to society. New York: Worth Publishers, 2011.
10. A. J. Blasio and A. M. Bisantz, A comparison of the effects of data-ink ratio on performance with dynamic displays in a monitoring task, Int.'l J. of Indust. Ergonomics, vol. 30, no. 2, 2002.
11. M. Burton, D. P. Wickham, L. Phelps, K. Spain, J. Crews, and N. Rich, Secondary navigation in software wizards, in CHI '99 extended abstracts on Human factors in computing systems, New York, NY, USA, 1999, p. 294-295.
12. J. T. Cacioppo, R. E. Petty, J. A. Feinstein, and W. B. G. Jarvis, Dispositional Differences in Cognitive Motivation: The Life and Times of Individuals Varying in Need for Cognition, Psych. Bulletin, vol. 119, no. 2, 1996.
13. P. A. Carpenter and P. Shah, A Model of the Perceptual and Conceptual Processes in Graph Comprehension, J. of Exp. Psych.: Appl., vol. 4, no. 2, 1998.
14. C.M. Carswell, S. Frankenberger, and D. Bernhard, Graphing in depth: perspectives on the use of three-dimensional graphs to represent lower-dimensional data, Behav. & Info. Tech., vol. 10, no. 6, 1991.
15. C.M. Carswell, Choosing specifiers: an evaluation of the basic tasks model of graphical perception, Human Factors, vol. 34, no. 5, pp. 535-554, Oct. 1992.
16. S. Casner and J. H. Larkin, Cognitive Efficiency Considerations for Good Graphic Design. Technical Report, 1989.
17. R. Chang, C. Ziemkiewicz, R. Pyzh, and J. Kielman, Learning-Based Evaluation of Visual Analytic Systems. BELIV '08 (CHI), 2008.
18. M.T.H. Chi, M. Bassok, M.W. Lewis, P. Reimann, and R. Glaser, "Self-explanations: How students study and use examples in learning to solve problems, Cog. Sci., vol. 13, no. 2, 1989.
19. M.T.H. Chi, Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in Instructional Psychology, Hillsdale, NJ: Lawrence Erlbaum Associates 2000.
20. W. S. Cleveland and R. McGill, Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods, J.of the Amer. Stat. Assoc., vol. 79, no. 387, 1984.
21. J.L. Davenport, D. Klahr, & K. Koedinger, The influence of external representations on chemistry problem solving. Presented at the Ann. Meeting of the Psychonomic Soc., 2006.
22. N. Diakopoulos, F. Kivran-Swaine, and M. Naaman, Playable Data: Characterizing the Design Space of Game-y Infographics, CHI (forthcoming), 2011.
23. C. Diemand-Yauman, D. M. Oppenheimer, and E. B. Vaughan, Fortune favors the Bold and the Italicized: Effects of disfluency on educational outcomes, Cognition, vol. 118, no. 1, 2011.
24. ESP game. GWAP.com, 2009. http://www.espgame.org.
25. F.L. Fahy, I. P. Riches, and M.W. Brown, Neuronal activity related to visual recognition memory: long-term memory and the encoding of recency and familiarity information in the primate anterior and medial inferior temporal and rhinal cortex, Exp. Brain Research., vol. 96, no. 3, 1993.
26. L. Findlater, K McGrenere, and J. Dawson, Ephemeral adaptation: the use of gradual onset to improve menu selection performance, CHI, 2009.
27. D.J. Gillan & E.H. Richman. Minimalism and the Syntax of Graphs. Human Factors, vol. 36, no. 4, 1994.
28. D. Hammond, Effectiveness of cigarette warning labels in informing smokers about the risks of smoking: findings from the International Tobacco Control (ITC) Four Country Survey, Tobacco Control, vol. 15, no. 3, 2006.
29. J. Heer and G. Robertson, "Animated Transitions in Statistical Data Graphics," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, 2007.
30. M. Hegarty, Representations in the Mind and in the World: How Cognitive Science Can Inform the Design of Visualizations, Keynote presentation, INFOVIS '10, 2010.
31. M. Hegarty and D.Waller. Individual Differences in Spatial Abilities. In P. Shah and A. Miyake (Eds), The Cambridge handbook of visuospatial thinking. Cambridge University Press, 2005.
32. M. Hegarty, S. Kriz, & C. Cate, The roles of mental animations and external animations in understanding mechanical systems. Cognition & Instruction, 21, 2003.
33. .T. Höffler & D. Leutner, Instructional Animation Versus Static Pictures: A Meta-Analysis. Learning and Instruction, vol. 17, 2007.
34. W. Huang et al. (Eds.), Measuring effectiveness of graph visualizations: A cognitive load perspective, Information Visualization, vol. 8, no. 3, 2009.
35. O. Inbar, N. Tractinsky, and J. Meyer, Minimalism in information visualization: attitudes towards maximizing the data-ink ratio, in Proc. of the Euro. Conf. on Cog. Ergonomics, 2007
36. R. Kosara, Visualization Criticism-The Missing Link Between Information Visualization and Art, IV '07, 2007.
37. S. M. Kosslyn, Understanding charts and graphs, Applied Cognitive Psychology, vol. 3, no. 3, 1989.
38. H. Lam, A Framework of Interaction Costs in Information Visualization, IEEE TVCG, 2008.
39. H. Lam, E. Bertini, P. Isenberg, C. Plaisant, & S. Carpendale. Seven Guiding Scenarios for Information Visualization Evaluation. Technical Report, 2010.
40. J. H. Larkin and H. A. Simon, Why a Diagram is (Sometimes) Worth Ten Thousand Words, Cog. Sci., vol. 11, no. 1, 1987.
41. E. Levy, J. Zacks, B. Tversky, and D. Schiano, Gratuitous graphics? Putting preferences in perspective, in CHI'96, 1996.
42. G.L. Lohse, The role of working memory on graphical information processing, Behaviour & Information Technology, vol. 16, no. 6, 1997.
43. G.L. Lohse, A cognitive model for the perception and understanding of graphs, CHI'91, 1991.
44. Z. Liu and J. T. Stasko, Mental models, visual reasoning and interaction in information visualization: a top-down perspective, IEEE TVCG, vol. 16, no. 6, 2010.
45. R.E. Mayer, M. Hegarty, S. Mayer, and J. Campbell, When static media promote active learning: annotated illustrations versus narrated animations in multimedia instruction, J. of Exp. Psych.: Appl., vol. 11, no. 4, 2005.
46. T. Munzner, A Nested Model for Visualization Design and Validation. IEEE TVCG, vol. 15, no. 6, 2009.
47. H. M. Natter and D. C. Berry, Effects of active information processing on the understanding of risk information, Appl. Cog. Psych., vol. 19, no. 1, 2005.
48. C. North. Visualization viewpoints: Toward measuring visualization insight. IEEE Comp. Graphics and Applic., vol. 26 no. 3, 2006.
49. O. Pagliano and D. M. Bajzek, Improving Animation Tutorials by Integrating Simulation, Assessment, and Feedback to Promote Active Learning, in T. Bastiaens & S. Carliner (Eds.), Proc. of World Conf. on E-Learning in Corp., Gov't, Healthcare, and Higher Educ., 2007.
50. A. Perer and B. Shneiderman, Systematic yet flexible discovery: guiding domain experts through exploratory data analysis, in Proc. on Intelligent User Interfaces, 2008.
51. S. Pinker. A theory of graph comprehension. In R. Friedle (Ed.), Artificial intelligence and the future of testing. Hillsdale, NJ: Erlbaum, 1990.
52. H. Purchase, E. Hoggan, and C. Gorg. How important is the Mental map? an empirical investigation of a dynamic graph layout algorithm. In Graph Drawing, 2006.
53. G. G. Robertson, S. K. Card, and J. D. Mackinlay, Information visualization using 3D interactive animation, Comm. of the ACM, vol. 36, 1993.
54. G. Robertson, R. Fernandez, D. Fisher, B. Lee, and J. Stasko, Effectiveness of Animation in Trend Visualization, IEEE TVCG, vol. 14, Nov. 2008.
55. M. Roy & M.T.H. Chi. The self-explanation principle. In R.E. Mayer (Ed.) Cambridge Handbook of Multimedia Learning, 2005.
56. L. Rozenblit and F. Keil, The misunderstood limits of folk science: an illusion of explanatory depth, Cog. Sci.,vol. 26, 2002.
57. S.H. Schwartz and W. Bilsky, Toward A Universal Psychological Structure of Human Values, J. of Personality and Social Psych. vol. 53, no. 3, 1987.
58. P. Shah and P. A. Carpenter, Conceptual Limitations in Comprehending Line Graphs, J. of Exp. Psych.: General, vol. 124, no. 1, 1995.
59. P. Shah & E. Freedman, Bar and line graph comprehension: An interaction of top-down and bottom-up processes. Topics in Cog. Sci., 2009.
60. P. Shah, R.E. Mayer, & M. Hegarty. Graphs as aids to knowledge construction: Signaling techniques for guiding the process of graph comprehension. J. of Educ. Psych., vol 91, 1991.
61. M. Siegrist, The use or misuse of three-dimensional graphs to represent lower-dimensional data, Behav. & Info. Tech, vol. 15, no. 2, 1996.
62. C.S. Skinner, V.J. Strecher, and H. Hospers, Physicians' recommendations for mammography: do tailored messages make a difference? Amer. J. of Pub. Health, vol. 84, no. 1, 1994.
63. D. Sprague & M. Tory. Motion in Casual InfoVis and the Interrelation between Personality, Performance, and Preference. Technical Report, 2009.
64. Tableau, Tabeau Software Inc., http://www.tableausoftware.com/.
65. J. G. Trafton, S. B. Trickett, and F. E. Mintz, Connecting Internal and External Representations: Spatial Transformations of Scientific Visualizations. Foundations of Science, vol. 10 no. 1, 2005.
66. E. R. Tufte, The Visual Display of Quantitative Information, 2nd ed. Graphics Press, 2001.
67. H. Wainer, Picturing the Uncertain World: How to Understand, Communicate, and Control Uncertainty through Graphical Display. Princeton University Press, 2009.
68. C. Ware, Visual Thinking: for Design, First Edition. Morgan Kaufmann, 2008.
69. K. Yee and D. Fisher, Animated Exploration of Dynamic Graphs with Radial Layout, INFOVIS, 2001.
70. J. Zacks, E. Levy, B. Tversky, and D. J. Schiano, Reading Bar Graphs: Effects of Extraneous Depth Cues and Graphical Context, J. of Exp. Psych.: Applied, vol. 4, no. 2, 1998.