Dynamic versus static menus: an exploratory comparison

Abstract

Sixty-three subjects completed 24 tasks using a menu driven computer program . The menu items appeared in a fixed (static) order during 12 of the tasks . During the other 12 tasks the menu ite m order changed dynamically such that the mos t frequently selected items always appeared at the top of the menu. All the subjects tried both dynamic and static menus.The subjects that used adaptive dynamic menus fo r the first set of tasks were significantly slower than those who used static menus on the first set of tasks . Subjects' performance during the second se t of tasks was not affected by menu style . Eightyone percent of the subjects preferred working wit h static menus to working with dynamic menus. INTRODUCTIO N

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

“…In the context of mobile devices, there has been a small amount of work on adaptive menu structures for phones [3,25], but evaluations have been informal. The bulk of adaptive GUI research, rather, has been conducted on desktop-sized displays, where evaluations have been inconclusive: in some cases, adaptive menus or toolbars have been faster and preferred to their static counterparts [13,15], whereas other research has shown the opposite [10,22,23]. As a result, adaptive GUIs have been conceptually controversial and very few have appeared in commercial applications.…”

Personalityzation: UI Personalization, Theoretical Grounding in HCI and Design Research

“…For example, Mitchell and Shneiderman (1989) adapted the UI (namely, menu design) based on users' frequency of usage and found that the adaptive interfaces fared poorly when compared to standard non-personalized UI. Several problems and unintended side effects have been noted in the design and use of adaptive interfaces (Höök, 2000;Jameson, 2009;Mitchell & Shneiderman, 1989;Shneiderman & Maes, 1997). In his survey of the field, Jameson (2008) identified five major usability challenges for adaptive interfaces: diminished predictability and comprehensibility, diminished controllability, obtrusiveness, infringement of privacy, and diminished breadth of experience.…”

“…In his survey of the field, Jameson (2008) identified five major usability challenges for adaptive interfaces: diminished predictability and comprehensibility, diminished controllability, obtrusiveness, infringement of privacy, and diminished breadth of experience. Research on adaptive UI has been trying to address these usability issues by proposing a diverse range of strategies (Cockburn, Gutwin, & Greenberg, 2007;Findlater & Gajos, 2009;Gajos, Czerwinski, Tan, & Weld, 2006;Mitchell & Shneiderman, 1989). One approach has proposed to hand users' some control over the adaptation procedure (Bunt, Conati, & McGrenere, 2010).…”

Designing for effective end-user interaction with machine learning

“…For example, many of the areas already described in this chapter (e.g., recommender systems, document classification, and programming by demonstration) are sometimes referred to as specific cases of adaptive or intelligent systems (Jameson, 2008;Ross, 2000). Other examples of intelligent systems include systems that adapt to an individual's skill level (e.g., adapting an interface for accessibility purposes (Gajos et al, 2008) or automatically tailoring support or difficulty levels in educational systems ) or goals (e.g., interface features that are automatically reorganized such that the functions that are most likely to be used next are easily accessible (Mitchell and Shneiderman, 1989;Greenberg and Witten, 1985)). Another class of systems that typically falls under this category is known as interface agents.…”