Impact of screen size on performance, awareness, and user satisfaction with adaptive graphical user interfaces

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Impact of screen size on performance, awareness, and user satisfaction with adaptive graphical user interfaces

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Conference on Human Factors in Computing Systems archive
Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems table of contents

Florence, Italy

SESSION: Adaptation table of contents

Pages 1247-1256

Year of Publication: 2008

ISBN:978-1-60558-011-1

Authors

Leah Findlater	University of British Columbia, Vancouver, Canada
Joanna McGrenere	University of British Columbia, Vancouver, Canada

Sponsors

ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 68, Downloads (12 Months): 374, Citation Count: 1

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ABSTRACT

Adaptive personalization, where the system adapts the interface to a user's needs, has the potential for significant performance benefits on small screen devices. However, research on adaptive interfaces has almost exclusively focused on desktop displays. To explore how well previous findings generalize to small screen devices, we conducted a study with 36 subjects to compare adaptive interfaces for small and desktop-sized screens. Results show that high accuracy adaptive menus have an even larger positive impact on performance and satisfaction when screen real estate is constrained. The drawback of the high accuracy menus, however, is that they reduce the user's awareness of the full set of items in the interface, potentially making it more difficult for users to learn about new features.

REFERENCES

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	1	Baddeley, A. The Psychology of Memory. Basic Books, New York, 1976.
	2	Daniel Billsus , Clifford A. Brunk , Craig Evans , Brian Gladish , Michael Pazzani, Adaptive interfaces for ubiquitous web access, Communications of the ACM, v.45 n.5, May 2002 [doi>10.1145/506218.506240]
	3	Robert Bridle , Eric McCreath, Inducing shortcuts on a mobile phone interface, Proceedings of the 11th international conference on Intelligent user interfaces, January 29-February 01, 2006, Sydney, Australia [doi>10.1145/1111449.1111526]
	4	Andrea Bunt , Cristina Conati , Joanna McGrenere, Supporting interface customization using a mixed-initiative approach, Proceedings of the 12th international conference on Intelligent user interfaces, January 28-31, 2007, Honolulu, Hawaii, USA [doi>10.1145/1216295.1216317]
	5	Andrea Bunt, Mixed-initiative support for customizing graphical user interfaces, University of British Columbia, Vancouver, BC, Canada, 2007
	6	Andy Cockburn , Carl Gutwin , Saul Greenberg, A predictive model of menu performance, Proceedings of the SIGCHI conference on Human factors in computing systems, April 28-May 03, 2007, San Jose, California, USA [doi>10.1145/1240624.1240723]
	7	Cohen, J. Eta-squared and partial eta-squared in communication science. Human Communication Research, 28, Oxford Journals, (1973), 473--490.
	8	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(1994), 1--21.
	9	Dillon, A., Richardson, J., and McKnight, C. The effects of display size and text splitting on reading length text from screen. Behaviour and Information Technology 9, 3(1990), 215--227.
	10	Leah Findlater , Joanna McGrenere, A comparison of static, adaptive, and adaptable menus, Proceedings of the SIGCHI conference on Human factors in computing systems, p.89-96, April 24-29, 2004, Vienna, Austria [doi>10.1145/985692.985704]
	11	Findlater, L. and McGrenere, J. Evaluating reduced-functionality interfaces according to feature findability and awareness. Proc. IFIP Interact 2007, (2007), 592--605.
	12	Gajos, K., Christianson, D., Hoffmann, R., Shaked, R., Henning, K., Long, J.J., and Weld, D.S.. Fast And Robust Interface Generation for Ubiquitous Applications. Proc. UBICOMP '05, 2005), 37--55.
	13	Krzysztof Z. Gajos , Mary Czerwinski , Desney S. Tan , Daniel S. Weld, Exploring the design space for adaptive graphical user interfaces, Proceedings of the working conference on Advanced visual interfaces, May 23-26, 2006, Venezia, Italy [doi>10.1145/1133265.1133306]
	14	Saul Greenberg, The computer user as toolsmith: the use, reuse, and organization of computer-based tools, Cambridge University Press, New York, NY, 1993
	15	Greenberg, S. and Witten, I. Adaptive personalized interfaces: A question of viability. Behaviour and Information Technology 4, 1(1985), 31--45.
	16	Greenberg S. and Witten, I. Directing the user interface: how people use command-based computer systems. Proc. 3rd IFAC Conference on Man-Machine Systems, (1988), 349--356.
	17	Stephen José Hanson , Robert E. Kraut , James M. Farber, Interface design and multivariate analysis of UNIX command use, ACM Transactions on Information Systems (TOIS), v.2 n.1, p.42-57, Jan. 1984 [doi>10.1145/357417.357421]
	18	Höök, K. Steps to take before intelligent user interfaces become real. Journal of Interacting with Computers 12, 4(2000), 409--426.
	19	Jones, M., Buchanan, G., and Thimbleby, H. Improving web search on small screen devices. Interacting with Computers 15, (2003)4, 479--495.
	20	Linton, F., Joy, D., Schaefer, H.-P., and Charron, A. Owl: A recommender system for organization-wide learning. Educational Technology & Society 3, 1(2000).
	21	McGrenere, J. and Moore, G. Are we all in the same "bloat"? Proc. of GI 2000, (2000), 187--196.
	22	McGrenere, J., Baecker, R., and Booth, K. An evaluation of a multiple interface design solution for bloated software. CHI Letters 4, 1(2002), 163--170.
	23	J. Mitchell , B. Shneiderman, Dynamic versus static menus: an exploratory comparison, ACM SIGCHI Bulletin, v.20 n.4, p.33-37, April 1989 [doi>10.1145/67243.67247]
	24	Antti Oulasvirta , Sakari Tamminen , Virpi Roto , Jaana Kuorelahti, Interaction in 4-second bursts: the fragmented nature of attentional resources in mobile HCI, Proceedings of the SIGCHI conference on Human factors in computing systems, April 02-07, 2005, Portland, Oregon, USA [doi>10.1145/1054972.1055101]
	25	Robert St. Amant , Thomas E. Horton , Frank E. Ritter, Model-based evaluation of expert cell phone menu interaction, ACM Transactions on Computer-Human Interaction (TOCHI), v.14 n.1, p.1-es, May 2007 [doi>10.1145/1229855.1229856]
	26	Andrew Sears , Ben Shneiderman, Split menus: effectively using selection frequency to organize menus, ACM Transactions on Computer-Human Interaction (TOCHI), v.1 n.1, p.27-51, March 1994 [doi>10.1145/174630.174632]
	27	Smyth, B., and Cotter, P. Personalized adaptive navigation for mobile portals. Proc. ECAI'02, (2002), 608--612.
	28	Smyth, B., Cotter, P., and Oman, S. Enabling intelligent content discovery on the mobile internet. Proc. AAAI, (2007), 1744--1751.
	29	Theophanis Tsandilas , m. c. schraefel, An empirical assessment of adaptation techniques, CHI '05 extended abstracts on Human factors in computing systems, April 02-07, 2005, Portland, OR, USA [doi>10.1145/1056808.1057079]