Context matters: Evaluating Interaction Techniques with the CIS Model

  • Caroline Appert
  • Michel Beaudouin-Lafon
  • Wendy E Mackay

Abstract

This article introduces the Complexity of Interaction Sequences model (CIS). CIS describes the structure of interaction techniques and the SimCIS simulator uses these descriptions to predict their performance in the context of an interaction sequence. The model defines the complexity of an interaction technique as a measure of its effectiveness within a given context. We tested CIS to compare three interaction techniques: fixed unimanual palettes, fixed bimanual palettes and toolglasses. The model predicts that the complexity of both palettes depends on interaction sequences, while toolglasses are less context-dependent. CIS also predicts that fixed bimanual palettes outperform the other two techniques. Predictions were tested empirically with a controlled experiment and confirmed the hypotheses. We argue that, in order to be generalizable, experimental comparisons of interaction techniques should include the concept of context sensitivity. CIS is a step in this direction as it helps predict the performance of interaction techniques according to the context of use.

Keywords

interaction technique interaction sequence complexity context palette bimanual palette toolglass experimentation performance theory 

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References

  1. Beaudouin-Lafon, M. & Lassen, H. M. [2000], The Architecture and Implementation of CPN2000, A Post-WIMP Graphical Application, in M. Ackerman & K. Edwards (eds.), Proceedings of the 13th Annual ACM Symposium on User Interface Software and Technology, UIST’00, CHI Letters 2(2), ACM Press, pp. 181–90.Google Scholar
  2. Bier, E. A., Stone, M. C., Pier, K., Buxton, W. & DeRose, T. D. [1993], Toolglass and Magic Lenses: The See-through Interface, in J. Kajiya (ed.), Proceedings of SIGGRAPH’93 20th Annual Conference on Computer Graphics and Interactive Techniques, Computer Graphics (Annual Conference Series) 27, ACM Press, pp.73–80.Google Scholar
  3. Card, S. K., Robertson, G. & Mackinlay, J. A. [1991], Morphological Analysis of the Design Space of Input Devices, ACM Transactions on Office Information Systems 9(2), 99–122.CrossRefGoogle Scholar
  4. Dragicevic, P. & Fekete, J. D. [2001], Input Device Selection and Interaction Configuration with ICON, in A. Blandford, J. Vanderdonckt & P. Gray (eds.), People and Computers XV: Interaction without Frontiers (Joint Proceedings of HCI2001 and IHM2001), Springer-Verlag, pp.543–58.Google Scholar
  5. Fitts, P. M. [1954], The Information Capacity of the Human Motor System in Controlling Amplitude of Movement, British Journal of Educational Psychology 47(6), 381–91.Google Scholar
  6. Foley, J. D., Wallace, V. L. & Chan, P. [1984], The Human Factors of Computer Graphics Interaction Techniques, IEEE Computer Graphics and Applications 4(11), 13–48.Google Scholar
  7. Green, T. R. G. [2000], Instructions and Descriptions: Some Cognitive Aspects of Programming and Similar Activities, in V. Di Gesù, S. Levialdi & L. Tarantino (eds.), Proceedings of the Conference on Advanced Visual Interface (AVI2000), ACM Press, pp.21–28.Google Scholar
  8. Hick, W. E. [1952], On the Rate of Gain of Information, Quarterly Journal of Experimental Psychology 4, 11–26.Google Scholar
  9. Jacob, R. J. K., Sibert, L. E., McFarlane, D. C. & Preston Mullen, Jr, M. P. [1994], Integrality and Separability of Input Devices, ACM Transactions on Computer-Human Interaction 1(1), 3–26.CrossRefGoogle Scholar
  10. John, B. E. & Kieras, D. E. [1996a], The GOMS Family of User Interface Analysis Techniques: Comparison and Contrast, ACM Transactions on Computer-Human Interaction 3(4), 320–51.CrossRefGoogle Scholar
  11. John, B. E. & Kieras, D. E. [1996b], Using GOMS for User Interface Design and Evaluation: Which Technique?, ACM Transactions on Computer-Human Interaction 3(4), 287–319.CrossRefGoogle Scholar
  12. John, B., Vera, A., Remington, R. & Freed, M. [2002], Automating CPM-GOMS, in D. Wixon (ed.), Proceedings of SIGCHI Conference on Human Factors in Computing Systems: Changing our World, Changing Ourselves (CHI’02), CHI Letters 4(1), ACM Press, pp. 147–54.Google Scholar
  13. Kabbash, P., Buxton, W. & Sellen, A. [1994], Two-Handed Input in a Compound Task, in B. Adelson, S. Dumais & J. Olson (eds.), Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Celebrating Interdependence (CHI’94), ACM Press, pp.417–23.Google Scholar
  14. Kieras, D. E. & Polson, P. G. [1985], An Approach to the Formal Analysis of User Complexity, International Journal of Man-Machine Studies 22(4), 365–94.CrossRefGoogle Scholar
  15. Mackay, W. E. [2002], Which Interaction Technique Works When? Floating Palettes, Marking Menus and Toolglasses Support Different Task Strategies, in S. Levialdi (ed.), Proceedings of the Conference on Advanced Visual Interface (AVI2002), ACM Press, pp.203–9.Google Scholar
  16. St. Amant, R. & Horton, T. E. [2002], Characterizing Tool Use in an Interactive Drawing Environment, in Proceedings of the International Symposium on Smart Graphics, ACM Press, pp.86–93.Google Scholar

Copyright information

© Springer-Verlag London Limited 2005

Authors and Affiliations

  • Caroline Appert
    • 1
  • Michel Beaudouin-Lafon
    • 1
  • Wendy E Mackay
    • 1
  1. 1.LRI & INRIA FutursUniversité Paris SudOrsayFrance

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