User-adaptive information visualization - Using eye gaze data to infer visualization tasks and user cognitive abilities

International Conference on Intelligent User Interfaces, Proceedings IUI

Volumn , Issue , 2013, Pages 317-328

  Steichen, Ben ^a   Carenini, Giuseppe ^a   Conati, Cristina ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Adaptation; Adaptive information visualization; Eye tracking; Machine learning

Indexed keywords

ADAPTATION; ADAPTIVE INFORMATION VISUALIZATIONS; EYE-TRACKING; INFORMATION VISUALIZATION; INFORMATION VISUALIZATION SYSTEM; RECENT RESEARCHES; VERBAL WORKING MEMORY; VISUALIZATION SYSTEM;

INFORMATION ANALYSIS; INFORMATION SYSTEMS; LEARNING SYSTEMS; VISUALIZATION;

DATA VISUALIZATION;

EID: 84875872693     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2449396.2449439     Document Type: Conference Paper

References (32)

1. Amar, R.A., Eagan J., & Stasko, J.T. Low-Level Components of Analytic Activity in Information Visualization. In 16th IEEE Visualization Conference, (2005), 15-21.
2. Casner, S. M. A task-analytic approach to the automated design of graphic presentations. ACM Trans. on Graph., 10(2), (1991), 111-115.
3. Conati, C., & Maclaren, H. Exploring the Role of Individual Differences in Information Visualization. In Proceedings of the working conference on Advanced visual interfaces (AVI'08). ACM, New York, NY, USA, (2008), 199-20.
4. Conati, C., & Merten, C. Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation. Know.-Based Syst., 20(6), (2007), 557-574.
5. Courtemanche, F., Aïmeur, E., Dufresne, A., Najjar, M., & Eboa, F.H.M. Activity recognition using eye-gaze movements and traditional interactions. In Proceedings of In-teracting with Computers, (2011), 202-213.
6. Dillon, A., & Shaap, D. Expertise and the perception of structure in discourse. Journal of the American Society for Information Science, 47(10), (1996), 786-788.
7. Eivazi, S., Bednarik, R. Predicting Problem-Solving Behavior and Performance Levels from Visual Attention Data. In the proceedings of 2nd Workshop on Eye Gaze in Intelligent Human Machine Interaction at IUI 2011, (2011), 9-16.
8. Ekstrom, R., French, J., Harman, H. and Dermen, D, Manual from Kit of Factor-References Cognitive Tests. Educational Testing Service (1976), Princeton, NJ.
9. Elzer, S., Carberry, S., & Zukerman, I. The automated understanding of simple bar charts. Artif. Intell. 175(2), (2011), 526-555.
10. Few, S. Keep Radar Graphs Below the Radar - Far Below: Information Management Magazine, (2005).
11. Fukuda, K., & Vogel, E.K. Human variation in overriding attentional capture. Journal of Neuroscience, (2009), 8726-8733.
12. Goldberg, J.H. & Helfman, J.I. Comparing Information Graphics: A Critical Look at Eye Tracking, BELIV'10, (2010), 182-195.
13. Goldberg, J.H. & Helfman, J.I. Eye tracking for visualization evaluation: Reading values on linear versus radial graphs. Information visualization 10(3), (2011), 182-195.
14. Gotz D., & Wen, Z. Behavior-Driven Visualization Recommendation. ACM Int. Conf. on Intelligent User Interfaces, (2009), 315-324.
15. Grawemeyer, B. Evaluation of ERST - an external representation selection tutor. In Proc. of the 4th int. conf. on Diagrammatic Representation and Inference (Diagrams'06), (2006), 154-167.
16. Green, T. M. & Fisher, B. Towards the personal equation of interaction: The impact of personality factors on visual analytics interface interaction. In IEEE Visual Analytics Science and Technology (VAST), (2010), 203-210.
17. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I.H. The WEKA Data Mining Software: An Update, SIGKDD Explor., 11 (1), (2009).
18. Iqbal, S.T., & Bailey, B.P. Using eye gaze patterns to identify user tasks. In: The Grace Hopper Celebration of Women in Computing, (2004).
19. Jameson, A. (2008). Adaptive Interfaces and Agents. The human-computer interaction handbook: Fundamentals, evolving technologies and emerging applications (2nd ed.), pp. 433-458.
20. Kardan, S., Conati, C.: Exploring Gaze Data for Determining User Learning with an Inter-active Simulation. Proc. 19th intl. conf. on user modeling, adaptation, and personalization, (2012), 126-138.
21. Keith, R. Eye movements and cognitive processes in reading, visual search, and scene perception. Eye Movement Research Mechanisms, Processes, and Applications. North-Holland Press, (1995).
22. Mackinlay, J. Automating the design of graphical presentations of relational information. ACM Trans. on Graph., 5(2), (1986), 110-141.
23. Plumlee, M.D., & Ware, C. Zooming versus multiple window interfaces: Cognitive costs of visual comparisons. ACM Trans. Comput.-Hum. Interact, 13, 2, (2006), 179-209.
24. Rayner, K. Eye movements in reading and information processing: 20 years of research. Psychological Bulletin 124, (1998), 372-422.
25. Sesma, L., Villanueva, A., & Cabeza, R. Evaluation of pupil center-eye corner vector for gaze estimation using a web cam. In Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA'12), (2012), 217-220.
26. Simola, J., Salojarvi, J., & Kojo, I. Using hidden Markov model to uncover processing states from eye movements in information search tasks. Cognitive Systems Research. 9, (2008), 237-251.
27. Steichen, B., Ashman, H., & Wade, V. A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques. Information Processing & Management, 48 (4), (2012), 698-724.
28. Toker D., Conati C., Steichen B., & Carenini G. Individual User Characteristics and Information Visualization: Connecting the Dots through Eye Tracking. In Proc. of the ACM SIGCHI Conference on Human Factors in Computing Systems, (CHI 2013), (2013), (to appear).
29. Toker, D., Conati, C., Carenini, G., & Haraty, M. Towards Adaptive Information Visualization: On the Influence of User Characteristics. In Proc. of the 19th international conference on user modeling, adaptation, and personalization, UMAP, (2012), 274-285.
30. Turner, M. L., & Engle, R.W. Is working memory capacity task dependent? Journal of Memory and Language, 28(2), (1989), 127-154.
31. Velez, M.C., Silver, D., & Tremaine, M. Understanding visualization through spatial ability differences. Proceedings of Visualization, (2005), 511-518.
32. Ziemkiewicz, C., et al. How Locus of Control Influences Compatibility with Visualization Style. Proc. IEEE VAST, (2011), 81-90.