Sorting-based menu categories

Hayhoe, Douglas

doi:10.1016/s0020-7373(05)80069-0

Cited by 18 publications

(5 citation statements)

References 32 publications

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“…As demonstrated in previous research, (Hayhoe, 1990;McDonald & Schvaneveldt, 1988;Roske-Hofstrand & Paap, 1986), the findings from both the current study and the previous study (Covas et al, 2010) provide support for organizing menu systems based on user knowledge. Designers, engineers and programmers are likely experts in design and engineering; however, they are rarely experts in the domain they design for.…”

Section: Discussionsupporting

confidence: 82%

“…It has been shown that menu organization is enhanced by user input (Hayhoe, 1990;Roske-Hofstrand & Paap, 1986). Previous research by Covas, Jackson, Branaghan, and Eidman (2010) redesigned one menu structure in the XCITE interface (the "declutter" menu; as depicted in Figure 1) using knowledge elicitation via card sorting and representation as well as hierarchical cluster analysis (HCA).…”

Section: Introductionmentioning

confidence: 99%

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Menu Design Based on Expert Knowledge Structures: A Validation

Covas-Smith

Jackson

Branaghan

et al. 2010

Proceedings of the Human Factors and Ergonomics Society Annual

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This project evaluated the effectiveness gained by redesigning a user interface based on the knowledge structure of domain experts. Scenario-based simulation enables realistic training in synthetic environments. As the instructor remains essential to facilitating effective scenario-based training, their user interface should be efficient. Previous research modeled knowledge structures used to redesign a menu within a scenario generation interface. The current research evaluated the redesigned menu based on the ascertained knowledge structures. To evaluate the redesigned menu, participants were timed as they selected target items in the original and redesigned menus. Results indicated that experienced users selected items in the redesigned menu significantly faster, and preferred the redesigned menu to the original. Thus, this result demonstrates tangible benefits to organizing menus according to expert knowledge, even when users are familiar with a menu structure. Using methods that follow the general principles presented here will enable designers to uncover expert knowledge and efficiently configure user interfaces, thereby improving training effectiveness.

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Menu Design Based on Expert Knowledge Structures: A Validation

Covas-Smith

Jackson

Branaghan

et al. 2010

Proceedings of the Human Factors and Ergonomics Society Annual

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show abstract

“…Some usability professionals use subjective ratings, while others use objective measures, and still others use a combination. Several studies have examined the extent of agreement between both types of measures [3,4,5]. The results of these studies have been mixed suggesting the iniluence of other factors.…”

Section: Introductionmentioning

confidence: 99%

The effect of computer experience on subjective and objective software usability measures

Kissel

1995

Conference Companion on Human Factors in Computing Systems - CHI '95

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In the user-centered approach to software design and development, end-users act as evaluators in usability tests at various points during the development life-cycle.Some usability professionals argue that these usability tests simply reflect the preferences of the participants and should not be used in place of objective performance measures. In an attempt to strengthen the validity of the user-centered approach, the present study examined the association between subjective preference measures and objective performance measures in relation to the user's hardware and software use and familiarity. The resultssuggest that not only do the subjective ratings of enduser evaluators often ditTer from objective performance measures, but also that this relationship is dependent on the user's past computer experience.

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“…In addition to these general sources of ambiguity, specific mechanisms of misclassification of causes might be sought. For instance, the literature on categories might be explored (e.g., Carlson & Dulany, 1985; Hayhoe, 1990). The specific mechanisms of ambiguity and links to related ambiguity-based phenomena remain to be pursued.…”

Section: Discussionmentioning

confidence: 99%

Where is the fault in fault trees?

Russo¹,

Kolzow²

1994

Journal of Experimental Psychology: Human Perception and Perfor

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When branches of a fault tree are pruned, their probabilities are not fully transferred to the "all other" branch. We test 3 explanations for this underestimation of the "all other" probability: availability, ambiguity, and credibility. In an experiment, we varied the credibility of a cover story and separately observed the generation of a fault's causes to isolate availability, and the categorization of causes to assess ambiguity. The results identify biased availability as a broad threat to the validity of likelihood estimates. Ambiguity adds to the problem whenever tree designers are unable to eliminate it from causes or categories. Finally, though subjects had clear expectations for what constitutes a credible fault tree, none of the "all other" underestimation could be traced to credibility factors. The discussion covers both underlying mechanisms and corrective techniques.

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Sorting-based menu categories

Cited by 18 publications

References 32 publications

Menu Design Based on Expert Knowledge Structures: A Validation

Menu Design Based on Expert Knowledge Structures: A Validation

The effect of computer experience on subjective and objective software usability measures

Where is the fault in fault trees?

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