ABSTRACT
We describe a mixed-initiative framework designed to support the customization of complex graphical user interfaces. The framework uses an innovative form of online GOMS analysis to provide the user with tailored customization suggestions aimed at maximizing the user's performance with the interface. The suggestions are presented non-intrusively, minimizing disruption and allowing the user to maintain full control. The framework has been applied to a general user-productivity application. A formal user evaluation of the system provides encouraging evidence that this mixed-initiative approach is preferred to a purely adaptable alternative and that the system's suggestions help improve task performance.
- Bunt, A., Conati, C., and McGrenere, J. What Role Can Adaptive Support Play in an Adaptable System? In Proc. of IUI, 2004, pp. 117--124. Google ScholarDigital Library
- Carberry, S. Techniques for plan recognition. User Modeling and User-Adapted Interaction, 11, 1-2 (2001), 31--48. Google ScholarDigital Library
- Card, S. K., Newell, A., and Moran, T. P. The Psychology of Human-Computer Interaction. Lawrence Erlbaum Associates, Inc., Mahwah, NJ 1983. Google ScholarDigital Library
- Cohen, J. Eta-squared and partial eta-squared in communication science. Human Communication Research, 28, (1973), 473--490.Google Scholar
- Cypher, A. EAGER: Programming Repetitive Tasks by Example. In Proc. of CHI, 1991, pp. 33--39. Google ScholarDigital Library
- Czarkowski, M. and Kay, J. How to Give the User a Sense of Control Over the Personalization of Adaptive Hypertext? In Proc. of Adaptive Hypermedia and Adaptive Web-Based Systems (in conjunction with UM'03), 2003, pp. 121--131.Google Scholar
- Debevc, M., Meyer, B., Donlagic, D., and Svecko, R. Design and evaluation of an adaptive icon toolbar. User Modeling and User-Adapted Interaction, 6, 1 (1996), 1--21.Google ScholarCross Ref
- Findlater, L. and McGrenere, J. A Comparison of Static, Adaptive, and Adaptable Menus. In Proc. of CHI, 2004, pp. 89--96. Google ScholarDigital Library
- Gajos, K., Czerwinski, M., Tan, D. S., and Weld, D. S. Exploring the Design Space for Adaptive Graphical User Interfaces. In Proc of AVI, 2006, pp. 201--208. Google ScholarDigital Library
- Gajos, K., D. Christianson, R. Hoffmann, T. Shaked, Henning, K., Long, J. J., and Weld, D. S. Fast and Robust Interface Generation for Ubiquitous Applications. In Proc. of Ubicomp, 2005, pp. 37--55. Google ScholarDigital Library
- Gong, R. and Kieras, D. A Validation of the GOMS Model Methodology in the Development of a Specialized, Commercial Software Application. In Proc. of CHI, 1994, pp. 351--357. Google ScholarDigital Library
- Greenberg, S. and Witten, I. H. Adaptive personalized interfaces - a question of viability. Behaviour and Information Technology, 4, 1 (1985), 31--45.Google ScholarCross Ref
- Greenberg, S. and Witten, I. H. How Users Repeat Their Actions on Computers: Principles for Design of History Mechanisms. In Proc. of CHI, 1988, pp. 171--178. Google ScholarDigital Library
- Hook, K. Steps to take before intelligent user interfaces become real. Interacting with Computers, 12, (2000), 409--426.Google ScholarCross Ref
- Horvitz, E. Principles of Mixed-Initiative User Interfaces. In Proc. of CHI, 1999, pp. 159--166. Google ScholarDigital Library
- Horvitz, E., Herckerman, D., Hovel, D., and Rommelse, R. The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. In Proc. of UAI, 1998, pp. 256--265. Google ScholarDigital Library
- Jameson, A. and Schwarzkopf, E. Pros and Cons of Controllability: An Empirical Study. In Proc. of AH, 2002, pp. 193--202. Google ScholarDigital Library
- Kieras, D. E., Wood, S. D., Abotel, K., and Hornof, A. J. GLEAN: A Computer-Based Tool for Rapid GOMS Model Usability Evaluation of User Interface Designs. In Proc. of UIST, 1995, pp. 91--100. Google ScholarDigital Library
- Linton, F. and Schaefer, H. Recommender systems for learning: building user and expert models through long-term observation of application use. User Modeling and User-Adapted Interaction, 10, 2-3 (2000), 181--207. Google ScholarDigital Library
- Mackay, W. E. Triggers and Barriers to Customizing Software. In Proc. of CHI, 1991, pp. 153--160. Google ScholarDigital Library
- McGrenere, J., Baecker, R. M., and Booth, K. S. An Evaluation of a Multiple Interface Design Solution for Bloated Software. In Proc. of CHI, 2002, pp. 163--170. Google ScholarDigital Library
- McGrenere, J. and Moore, G. Are We All in the Same "Bloat"? In Proc. of GI, 2000, pp. 187--196.Google Scholar
- Mitchell, J. and Shneiderman, B. Dynamic versus static menus: an exploratory comparison. SIGCHI Bull., 20, 4 (1989), 33--37. Google ScholarDigital Library
- Oppermann, R. Adaptively supported adaptability. International Journal of Human-Computer Studies, 40, (1994), 455--472. Google ScholarDigital Library
- Shneiderman, B. and Maes, P. Direct manipulation vs. interface agents. interactions, 4, 6 (1997), 42--61. Google ScholarDigital Library
- St. Amant, R. and Cohen, P. R. Interaction with a Mixed-Initiative System for Exploratory Data Analysis. In Proc. of IUI, 1997, pp. 15--22. Google ScholarDigital Library
- kThomas, C. G. and Krogsoeter, M. An Adaptive Environment for the User Interface of Excel. In Proc. of IUI, 1993, pp. 123--130. Google ScholarDigital Library
Index Terms
- Supporting interface customization using a mixed-initiative approach
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