Thu, 07 Aug 2008 21:52:55 BST CiteULike: brusilovsky's adaptive-interface http://www.citeulike.org/user/brusilovsky/tag/adaptive-interface CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/brusilovsky/article/2862354 <i>(2008), pp. 1271-1274.</i><br /><br />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. Predictability and accuracy in adaptive user interfaces Krzysztof Gajos Katherine Everitt Desney Tan Mary Czerwinski Daniel Weld doi:10.1145/1357054.1357252 (2008), pp. 1271-1274. 2008-06-04T19:28:05-00:00 2008 1271 1274 ACM adaptive-interface empirical-study en http://www.citeulike.org/user/brusilovsky/article/2931514 <i>(2008), pp. 1267-1270.</i><br /><br />Coarse-grained approaches to customization allow the user to enable or disable groups of features at once, rather than individual features. While this may reduce the complexity of customization and encourage more users to customize, the research challenges of designing such approaches have not been fully explored. To address this limitation, we conducted an interview study with 14 professional software developers who use an integrated development environment that provides a role-based, coarse-grained approach to customization. We identify challenges of designing coarse-grained customization models, including issues of functionality partitioning, presentation, and individual differences. These findings highlight potentially critical design choices, and provide direction for future work. Evaluation of a role-based approach for customizing a complex development environment Leah Findlater Joanna Mcgrenere David Modjeska doi:10.1145/1357054.1357251 (2008), pp. 1267-1270. 2008-06-26T17:44:52-00:00 2008 1267 1270 ACM adaptability adaptive-interface empirical-study http://www.citeulike.org/user/brusilovsky/article/2862084 <i>(2008), pp. 1247-1256.</i><br /><br />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. Impact of screen size on performance, awareness, and user satisfaction with adaptive graphical user interfaces Leah Findlater Joanna Mcgrenere doi:10.1145/1357054.1357249 (2008), pp. 1247-1256. 2008-06-04T17:42:28-00:00 2008 1247 1256 ACM adaptive-interface empirical-study en mobile-computing http://www.citeulike.org/user/brusilovsky/article/2008955 <i>(2007), pp. 3-12.</i> Pillows as adaptive interfaces in ambient environments Frank Nack Thecla Schiphorst Zeljko Obrenovic Michiel Kauwatjoe Simon de Bakker Angel Rosillio Lora Aroyo doi:10.1145/1290128.1290131 (2007), pp. 3-12. 2007-11-29T01:12:59-00:00 2007 3 12 ACM adaptive-interface ambient-interface http://www.citeulike.org/user/brusilovsky/article/1988966 <i>IEEE Intelligent Systems, Vol. 18, No. 2. (March 2003), pp. 52-57.</i><br /><br />In human-computer interaction, user interface events and frequencies can be recorded and organized into episodes. By computing episode frequencies and implication relations, we can automatically derive application-specific episode associations and therefore enable an application interface to adaptively provide just-in-time assistance to a user. The authors identify five issues related to designing an adaptive user interface: interaction tracking, episodes identification, user pattern recognition, user intention prediction, and user profile update. In particular, they demonstrate how to identify episodes and associate them with an interface that can act on a user's behalf to interact with an application based on certain recognized plans. To adapt to different users' needs, the interface can personalize its assistance by learning user profiles. For example, by detecting and analyzing users' behavior patterns in using Microsoft Word, the interface can automatically assist users in several Word tasks. The authors' Word interface provides episode associations at two levels: text-level (phrase association) and paragraph-level (formatting automation). They conducted two pilot experiments to evaluate the interface's performance. The suggestions it provided and its ease of use were well received by users, and the interface can to a certain extent increase the productivity of type-setting. An Adaptive User Interface Based On Personalized Learning Jiming Liu Chi Wong Ka Hui doi:10.1109/MIS.2003.1193657 IEEE Intelligent Systems, Vol. 18, No. 2. (March 2003), pp. 52-57. 2007-11-26T22:39:59-00:00 2003 IEEE Intelligent Systems 1541-1672 18 2 52 57 IEEE Educational Activities Department adaptive-interface http://www.citeulike.org/user/brusilovsky/article/1263375 <i>(2006), pp. 309-318.</i> User interface fa&\#231;ades: towards fully adaptable user interfaces Wolfgang Stuerzlinger Olivier Chapuis Dusty Phillips Nicolas Roussel doi:10.1145/1166253.1166301 (2006), pp. 309-318. 2007-04-28T14:05:47-00:00 2006 309 318 ACM Press 2470-072 2470-081 adaptability adaptive-interface en http://www.citeulike.org/user/brusilovsky/article/852698 <i>(2006), pp. 751-760.</i> A goal-oriented web browser Alexander Faaborg Henry Lieberman doi:10.1145/1124772.1124883 (2006), pp. 751-760. 2006-09-21T12:24:45-00:00 2006 751 760 ACM Press 2470-081 adaptive-interface agents www http://www.citeulike.org/user/brusilovsky/article/1106142 <i>(2007), pp. 92-101.</i> Supporting interface customization using a mixed-initiative approach Andrea Bunt Cristina Conati Joanna Mcgrenere doi:10.1145/1216295.1216317 (2007), pp. 92-101. 2007-02-14T00:28:42-00:00 2007 92 101 ACM Press adaptability adaptive-interface en http://www.citeulike.org/user/brusilovsky/article/210859 <i>(2004), pp. 89-96.</i> A comparison of static, adaptive, and adaptable menus Leah Findlater Joanna Mcgrenere doi:10.1145/985692.985704 (2004), pp. 89-96. 2005-05-25T20:45:59-00:00 2004 89 96 ACM Press adaptability adaptive-interface end http://www.citeulike.org/user/brusilovsky/article/960041 <i>(2005), pp. 2009-2012.</i> An empirical assessment of adaptation techniques Theophanis Tsandilas Schraefel doi:10.1145/1056808.1057079 (2005), pp. 2009-2012. 2006-11-24T00:48:19-00:00 2005 2009 2012 ACM Press adaptive-interface empirical-study http://www.citeulike.org/user/brusilovsky/article/960014 <i>(2006), pp. 201-208.</i> Exploring the design space for adaptive graphical user interfaces Krzysztof Gajos Mary Czerwinski Desney Tan Daniel Weld doi:10.1145/1133265.1133306 (2006), pp. 201-208. 2006-11-23T23:18:02-00:00 2006 201 208 ACM Press 2470-072 2470-081 adaptive-interface empirical-study http://www.citeulike.org/user/brusilovsky/article/163216 <i>interactions, Vol. 4, No. 6. (1997), pp. 42-61.</i> Direct manipulation vs. interface agents Ben Shneiderman Pattie Maes doi:10.1145/267505.267514 interactions, Vol. 4, No. 6. (1997), pp. 42-61. 2005-04-17T23:46:39-00:00 1997 interactions 1072-5520 4 6 42 61 ACM Press adaptive-interface agents http://www.citeulike.org/user/brusilovsky/article/274045 <i>(2004), pp. 117-124.</i><br /><br />As computer applications become larger with every new version, there is a growing need to provide some way for users to manage the interface complexity. There are three different potential solutions to this problem: 1) an adaptable interface that allows users to customize the application to suit their needs; 2) an adaptive interface that performs the adaptation for the users; or 3) a combination of the adaptive and adaptable solutions, an approach that would be suitable in situations where users are not customizing effectively on their own. In this paper we examine what it means for users to engage in effective customization of a menu-based graphical user interface. We examine one aspect of effective customization, which is how characteristics of the users' tasks and customization behaviour affect their performance on those tasks. We do so by using a process model simulation based on cognitive modelling that generates quantitative predictions of user performance. Our results show that users can engage in customization behaviours that vary in efficiency. We use these results to suggest how adaptive support could be added to an adaptable interface to improve the effectiveness of the users' customization. What role can adaptive support play in an adaptable system? Andrea Bunt Cristina Conati Joanna Mcgrenere doi:10.1145/964442.964465 (2004), pp. 117-124. 2005-08-04T19:12:33-00:00 2004 117 124 ACM Press adaptability adaptive-interface en http://www.citeulike.org/user/brusilovsky/article/430254 <i>(2004), pp. 93-100.</i> SUPPLE: automatically generating user interfaces Krzysztof Gajos Daniel Weld doi:10.1145/964442.964461 (2004), pp. 93-100. 2005-12-08T01:06:32-00:00 2004 93 100 ACM Press adaptive-interface en mobile-computing