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A field evaluation of an adaptable two-interface design for feature-rich software

Published: 01 May 2007 Publication History

Abstract

Two approaches for supporting personalization in complex software are system-controlled adaptive menus and user-controlled adaptable menus. We evaluate a novel interface design for feature-rich productivity software based on adaptable menus. The design allows the user to easily customize a personalized interface, and also supports quick access to the default interface with all of the standard features. This design was prototyped as a front-end to a commercial word processor. A field experiment investigated users' personalizing behavior and tested the effects of different interface designs on users' satisfaction and their perceived ability to navigate, control, and learn the software. There were two conditions: a commercial word processor with adaptive menus and our prototype with adaptable menus for the same word processor. Our evaluation shows: (1) when provided with a flexible, easy-to-use and easy-to-understand customization mechanism, the majority of users do effectively personalize their interface; and (2) user-controlled interface adaptation with our adaptable menus results in better navigation and learnability, and allows for the adoption of different personalization strategies, as compared to a particular system-controlled adaptive menu system that implements a single strategy. We report qualitative data obtained from interviews and questionnaires with participants in the evaluation in addition to quantitative data.

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Information

Published In

cover image ACM Transactions on Computer-Human Interaction
ACM Transactions on Computer-Human Interaction  Volume 14, Issue 1
May 2007
159 pages
ISSN:1073-0516
EISSN:1557-7325
DOI:10.1145/1229855
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 2007
Published in TOCHI Volume 14, Issue 1

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Author Tags

  1. Human-computer interaction
  2. adaptable interfaces
  3. adaptive interfaces
  4. bloatware
  5. customization
  6. featurism
  7. field experiment
  8. individual differences
  9. personalization

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  • (2021)Towards a Semantic Classification of Possible Human-to-Environment Interactions in IoTDistributed, Ambient and Pervasive Interactions10.1007/978-3-030-77015-0_10(135-152)Online publication date: 24-Jul-2021
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