An empirical assessment of adaptation techniques

Tsandilas, Theophanis; schraefel, m.c.

doi:10.1145/1056808.1057079

Cited by 50 publications

(44 citation statements)

References 10 publications

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“…We use the term accuracy to refer to the percentage of times the system proposes correct and relevant suggestions to the user. Accuracy in adaptive interfaces was found to have a significant impact on user performance (Gajos et al, 2006;Tsandilas & Schraefel, 2005;Findlater & McGrenere, 2008b). Gajos et al (2008) explored the relative effects of accuracy on the usability of adaptive interfaces using split menus and concluded that improvement in accuracy positively effects performance, utilization and some satisfaction ratings.…”

Section: Key Factors For Adaptive Assistancementioning

confidence: 99%

“…These two components of system's reliability (accuracy and trust) also affect each other. Low accuracy levels affect user's trust in the system's suggestions (Tsandilas & Schraefel, 2005).…”

Section: 2)mentioning

confidence: 99%

“…Graphical adaptation reduces a visual search time by using graphical techniques such as background colors (Gajos et al, 2006;Tsandilas & schraefel, 2005;Findlater & McGrenere, 2008b) and transparency without changing the structure of the interface (Findlater et al, 2009). …”

Section: Adaptive Menus and Toolbarsmentioning

confidence: 99%

“…Few former studies have examined highlighting techniques and different accuracy levels using menus and toolbars in the context of adaptive menus and toolbars (Findlater et al, 2009;Gajos et al, 2006;Tsandilas & Schraefel, 2005. A summary of these studies is presented in Table 1.…”

Section: Adaptive Menus and Toolbarsmentioning

confidence: 99%

“…This method is similar to the one used by Tsandilas and Schraefel (2005) and Park et al (2007), however, they have highlighted items in a single menu list to facilitate the selection of items.…”

Section: Adaptive Menus and Toolbarsmentioning

confidence: 99%

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Highlighting items as means of adaptive assistance

Antwarg

Lavie

Rokach

et al. 2013

Behaviour & Information Technology

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Providing adaptive help during interaction with the system can be used to assist users in accomplishing their tasks. We propose providing guidance by highlighting the steps required for performing a task that the user intends to complete according to the prediction of a system. We present a study aimed at examining whether highlighting intended user steps in menus and toolbars as a means of assisting users in performing tasks is useful in terms of user response and performance. We also examined the effects of different accuracy levels of the relevancy of the provided help and the help format on user response and performance. An experiment was conducted in which 64 participants performed tasks using menus and toolbars of a simulated email application. Participants were offered a highlighted guidance of the required steps in varying levels of accuracy (100%, 80%, 60%, and no guidance). Our results support the benefits of highlighted help both in user performance times and in user satisfaction from receiving such assistance. Users found the assistance necessary and helpful and by the same token not unduly intrusive. Additionally, users felt that such assistance generally helped in reducing performance time on tasks. We did not find a significant difference when users receiving help at 80% accuracy was compared to those receiving help at 100% accuracy; however, such a difference does appear for 2 those receiving 60% accuracy. In such cases we found that the user's satisfaction level, perceived usefulness and trust in the system decreased while their notion of perceived intrusiveness increased. We conclude that assisting users by highlighting the required steps is useful so long as the minimal accuracy level is higher than 60%.Our study has implications on the implementation of highlighting next steps as a means of adaptive help and on integrating probability-based algorithms such as intention prediction to adaptive assistance systems.

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