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Predictability and accuracy in adaptive user interfaces

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Daniel S. WeldAuthors Info & Claims

CHI '08: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1271 - 1274

https://doi.org/10.1145/1357054.1357252

Published: 06 April 2008 Publication History

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Abstract

While proponents of adaptive user interfaces tout potential performance gains, critics argue that adaptation's unpredictability may disorient users, causing more harm than good. We present a study that examines the relative effects of predictability and accuracy on the usability of adaptive UIs. Our results show that increasing predictability and accuracy led to strongly improved satisfaction. Increasing accuracy also resulted in improved performance and higher utilization of the adaptive interface. Contrary to our expectations, improvement in accuracy had a stronger effect on performance, utilization and some satisfaction ratings than the improvement in predictability.

References

[1]

Benyon, D. (1993) Adaptive systems: A solution to usability problems. User Modeling and User-Adapted Interaction 3 (1), 65--87.

Crossref

Google Scholar

[2]

Findlater, L. and McGrenere, J. (2004) A comparison of static, adaptive, and adaptable menus. Proc. CHI'04, 89--96. ACM Press.

Digital Library

Google Scholar

[3]

Findlater, L. and McGrenere, J. (2008) Impact of Screen Size on Performance, Awareness, and User Satisfaction With Adaptive Graphical User Interfaces. Proc. CHI'08, ACM Press.

Digital Library

Google Scholar

[4]

Gajos, K., Czerwinski, M., Tan, D. and Weld, D. (2006) Exploring the design space for adaptive graphical user interfaces. Proc. AVI'06, 201--208. ACM Press.

Digital Library

Google Scholar

[5]

Maes, P. (1994) Agents that reduce work and information overload. Commun. ACM 37 (7), 30--40.

Digital Library

Google Scholar

[6]

Nielsen, J. (1994) Enhancing the explanatory power of usability heuristics. Proc. CHI'94, 152--158. ACM Press.

Digital Library

Google Scholar

[7]

Paymans, T., Lindenberg, J. and Neerincx, M. (2004) Usability trade-offs for adaptive user interfaces: ease of use and learnability. Proc. IUI'04, 301--303.

Digital Library

Google Scholar

[8]

Sears, A. and Shneiderman, B. (1994) Split menus: effectively using selection frequency to organize menus. ACM Trans. Comp.-Hum. Interact. 1 (1), 27--51

Digital Library

Google Scholar

[9]

Shaffer, J. (1995) Multiple Hypothesis-Testing. Annual Review of Psychology 46, 561--584.

Crossref

Google Scholar

[10]

Shneiderman, B. (1997) Direct manipulation for comprehensible, predictable and controllable user inter-faces. Proc. IUI'97, 33--39. ACM Press.

Digital Library

Google Scholar

[11]

Tsandilas, T. and Schraefel. (2005) An empirical assessment of adaptation techniques. CHI '05 extended abstracts, 2009--2012.

Digital Library

Google Scholar

[12]

Winship, C. and Mare, R. (1984) Regression Models with Ordinal Variables. Am. Soc. Rev. 49 (4), 512--525.

Crossref

Google Scholar

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Park GPanda PTankelevitch LRintel S(2024)CoExplorer: Generative AI Powered 2D and 3D Adaptive Interfaces to Support Intentionality in Video MeetingsExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650797(1-10)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650797
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Index Terms

Predictability and accuracy in adaptive user interfaces
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
    2. Interaction paradigms

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Published In

CHI '08: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2008

1870 pages

ISBN:9781605580111

DOI:10.1145/1357054

General Chairs:
Mary Czerwinski
Microsoft Research, USA
,
Arnie Lund
Microsoft, USA
,
Program Chair:
Desney Tan
Microsoft Research, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 April 2008

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April 5 - 10, 2008

Florence, Italy

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CHI '08 Paper Acceptance Rate 157 of 714 submissions, 22%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Eloi DSahraoui AVanderdonckt JLeiva L(2024)User-controlled Form Adaptation by Unsupervised LearningAdjunct Proceedings of the 2024 Nordic Conference on Human-Computer Interaction10.1145/3677045.3685431(1-8)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3677045.3685431
Park GPanda PTankelevitch LRintel S(2024)The CoExplorer Technology Probe: A Generative AI-Powered Adaptive Interface to Support Intentionality in Planning and Running Video MeetingsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661507(1638-1657)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661507
Park GPanda PTankelevitch LRintel S(2024)CoExplorer: Generative AI Powered 2D and 3D Adaptive Interfaces to Support Intentionality in Video MeetingsExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650797(1-10)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650797
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Exploring the design space for adaptive graphical user interfaces

A comparison of static, adaptive, and adaptable menus

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

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Exploring the design space for adaptive graphical user interfaces

A comparison of static, adaptive, and adaptable menus

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

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