TY - JOUR
T1 - Split Menus
T2 - Effectively Using Selection Frequency to Organize Menus
AU - Sears, Andrew
AU - Shneiderman, Ben
PY - 1994/1/3
Y1 - 1994/1/3
N2 - When some items in a menu are selected more frequently than others, as is often the case, designers or individual users may be able to speed performance and improve preference ratings by placing several high-frequency items at the top of the menu. Design guidelines for split menus were developed and applied. Split menus were implemented and tested in two in situ usability studies and a controlled experiment. In the usability studies performance times were reduced by 17 to 58% depending on the site and menus. In the controlled experiment split menus were significantly faster than alphabetic menus and yielded significantly higher subjective preferences. A possible resolution to the continuing debate among cognitive theorists about predicting menu selection times is offered. We conjecture and offer evidence that, at least when selecting items from pull-down menus, a logarithmic model applies to familiar 1994 items, and a linear model to unfamiliar (low-frequency) items.
AB - When some items in a menu are selected more frequently than others, as is often the case, designers or individual users may be able to speed performance and improve preference ratings by placing several high-frequency items at the top of the menu. Design guidelines for split menus were developed and applied. Split menus were implemented and tested in two in situ usability studies and a controlled experiment. In the usability studies performance times were reduced by 17 to 58% depending on the site and menus. In the controlled experiment split menus were significantly faster than alphabetic menus and yielded significantly higher subjective preferences. A possible resolution to the continuing debate among cognitive theorists about predicting menu selection times is offered. We conjecture and offer evidence that, at least when selecting items from pull-down menus, a logarithmic model applies to familiar 1994 items, and a linear model to unfamiliar (low-frequency) items.
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U2 - 10.1145/174630.174632
DO - 10.1145/174630.174632
M3 - Article
AN - SCOPUS:0343269137
SN - 1073-0516
VL - 1
SP - 27
EP - 51
JO - ACM Transactions on Computer-Human Interaction (TOCHI)
JF - ACM Transactions on Computer-Human Interaction (TOCHI)
IS - 1
ER -