Comparing static, adaptable, and adaptive menus

• Main Author: Findlater, Leah K.
• Format: Others
• Language: English
• Published: 2009
• Online Access: http://hdl.handle.net/2429/15499

Software applications continue to grow in terms of the number of features they offer, making personalization increasingly important. Research has shown that most users prefer the control afforded by an adaptable approach to personalization rather than a system-controlled adaptive approach. Both types of approaches offer advantages and disadvantages. No study, however, has compared the efficiency of the two approaches. In two controlled lab studies, we measured the efficiency of static, adaptive and adaptable interfaces in the context of pull-down menus. These menu conditions were implemented as a split menus, in which the top four items remained static, were adaptable by the subject, or adapted according to the subject's frequently and recently used items. The results of Study 1 showed that a static split menu was significantly faster than an adaptive split menu. Also, when the adaptable split menu was not the first condition presented to subjects, it was significantly faster than the adaptive split menu, and not significantly different from the static split menu. The majority of users preferred the adaptable menu overall. Several implications for personalizing user interfaces based on these results are discussed. One question which arose after Study 1 was whether prior exposure to the menus and task has an effect on the efficiency of the adaptable menus. A second study was designed to follow-up on the theory that prior exposure to different types of menu layouts influences a user's willingness to customize. Though the observed power of this study was low and no statistically significant effect of type of exposure was found, a possible trend arose: that exposure to an adaptive interface may have a positive impact on the user's willingness to customize. This and other secondary results are discussed, along with several areas for future work. The research presented in this thesis should be seen as an initial step towards a more thorough comparison of adaptive and adaptable interfaces, and should provide motivation for further development of adaptable interaction techniques. === Science, Faculty of === Computer Science, Department of === Graduate