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Andrew Sears. Ben Shneiderman. June 1993.
Split menus: Effectively using selection frequency to organize menus. 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 satisfaction 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 field studies and a controlled experiment. In the field study conditions performance times were reduced from 17 or 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 the logarithmic model applies to familiar (high-frequency) items and the linear model applies to unfamiliar (low-frequency) items. (Also cross-referenced as CAR-TR-649) ACM Transactions on Computer-Human Interaction, vol. 1, #1 (March 1994) 27-51 %I Human Computer Interaction Laboratory Center for Automation Research, Dept. of Computer Science, Univ. of Maryland,
Andrew Sears. December 1992.
Layour Appropriateness: A metric for evaluating user interface widget. Numerous methods to evaluate user interfaces have been investigated. These methods vary greatly in the attention paid to the usersŐ tasks. Some methods require detailed task descriptions while others are task-independent. Unfortunately, collecting detailed task information can be difficult. On the other hand, task-independent methods cannot evaluate a design for the tasks users actually perform. The goal of this research is to develop a metric, which incorporates simple task descriptions, that can assist designers in organizing widgets in the user interface. Simple task descriptions provide some of the benefits, without the difficulties, of performing a detailed task analysis. The metric, Layout Appropriateness (LA), requires a description of the sequences of widget-level actions users perform and how frequently each sequence is used. This task description can either be from observations of an existing system or from a simplified task analysis. The appropriateness of a given layout is computed by weighting the cost of each sequence of actions by how frequently the sequence is performed. This emphasizes frequent methods of accomplishing tasks while incorporating less frequent methods in the design. Currently costs are based on the distance users must move the mouse. Other measures such as the number of eye fixations necessary to extract the relevant information or measure like the number of changes in direction may also prove useful, but must be validated before they are made available for use. In addition to providing an comparison of a proposed or existing layouts, an LA-optimal layout is presented to the designer. The designer can compare the LA-optimal and existing layouts or start with the LA-optimal layout and modify it to take additional factors into consideration. Software engineers who occasionally face interface design problems and user interface designers can benefit from the explicit focus on the usersŐ tasks that LA incorporates into automated user interface evaluation. (Also cross-referenced as CAR-TR-603) Human Computer Interaction Laboratory, Center for Automation Research, Dept. of Computer Science, Univ. of Maryland, Institute for Systems Research,
Catherine Plaisant. Andrew Sears. September 1992.
Touchscreen Interfaces for flexible alphanumeric data entry. Touchscreens have been demonstrated as useful for many applications. Although a traditional mechanical keyboard is the device of choice when entering alphanumeric data, it may not be optimal when only limited data must be entered, or when the keyboard layout, character set, or size may be changed. A series of experiments has demonstrated the usability of touchscreen keyboards. The first study indicated that users who type 58 wpm on a traditional keyboard can type 25 wpm using a touchscreen and that the traditional monitor position is suboptimal for touchscreen use. A second study reported on typing rates for keyboards of various sizes (from 6.8 to 24.6 cm wide). Novices typed approximately 10 wpm on the smallest and 20 wpm on the largest of the keyboards. Users experienced with touchscreen keyboards typed 21wpm on the smallest and 32 wpm on the largest. We then report on a recent study done with more representative users and more difficult tasks. Thirteen cashiers were recruited for this study and were required to complete ten trials in which they typed names and addresses with punctuation. Results indicate that the users improved rapidly from 9.5 wpm on the first trial to 13.8 wpm on the last trial, reaching their fastest performance after only 25 minutes. Although custom interfaces will be preferred for special types of data (e.g. telephone numbers, times, dates, colors) there will always be situations when limited quantities of text must be entered. In these situations a touchscreen keyboard can be used. (Also cross-referenced as CAR-TR-585) Human Computer Interaction Laboratory, Center for Automation Research, Dept. of Computer Science, Univ. of Maryland, Institute for Systems Research,
Andrew Sears. Doreen Revis. Janet Swatski. Rob Crittenden. Ben Shneiderman. April 1991.
Investigating Touchscreen Typing: the Effect of Keyboard Size on. Two studies investigated the effect keyboard size has on typing speed and error rates for touchscreen keyboards using the lift-off strategy. A cursor appeared when users touched the screen and a key was selected when they lifted their finger from the screen. Four keyboard sizes were investigated ranging from 24.6 cm to 6.8 cm wide. Results indicate that novices can type approximately 10 words per minute (WPM) on the smallest keyboard and 20 WPM on the largest. Experienced users improved to 21 WPM on the smallest keyboard and 32 WPM on the largest. These results indicate that, although slower, small touchscreen keyboards can be used for limited data entry when the presence of a regular keyboard is not practical. Applications include portable pocket-sized or palmtop computers, messaging systems, and personal information resources. Results also suggest the increased importance of experience on these smaller keyboards. Research directions are suggested. (Also cross-referenced as CAR-TR-553) Human Computer Interaction Laboratory, Center for Automation Research, Dept. of Computer Science, Univ. of Maryland, Institute for Systems Research,
Andrew Sears. March 1991.
Improving Touchscreen Keyboards:. This study explored touchscreen keyboards using high precision touchscreen strategies. Phase one evaluated three possible monitor positions: 30, 45, and 75 degrees from horizontal. Results indicate that the 75 degree angle, approximately the standard monitor position, resulted in more fatigue and lower preference ratings. Phase two collected touch bias and key size data for the 30 degree angle. Subjects consistently touched below targets, and touched to the left of targets on either side of the screen. Using these data, a touchscreen keyboard was designed. Phase three compared this keyboard with a mouse activated keyboard, and the standard QWERTY keyboard for typing relatively short strings of 6, 19, and 44 characters. Results indicate that users can type approximately 25 words per minute with the touchscreen keyboard, compared to 17 WPM using the mouse, and 58 WPM when using the keyboard. Possible improvements to touchscreen keyboards are suggested. (Also cross-referenced as CAR-TR-515) Human Computer Interaction Laboratory, Center for Automation Research, Dept. of Computer Science, Univ. of Maryland, Institute for Systems Research,
Andrew Sears. Catherine Plaisant. Ben Shneiderman. June 1990.
A new era for high-precision touchscreens. While many input devices allow interfaces to be customized, increased directness distinguishes touchscreens. Touchscreens are easy to learn to use, fast, and result in low error rates when interfaces are designed carefully. Many actions which are difficult with a mouse, joystick, or keyboard are simple when using a touchscreen. Making rapid selections at widely separated locations on the screen, signing your name, dragging the hands of a clock in a circular motion are all simple when using a touchscreen, but may be awkward using other devices. This paper presents recent empirical research which can provide a basis for theories of touchscreen usage. We believe recent improvements warrant increased use of touchscreens. (Also cross-referenced as CAR-TR-506) Human Computer Interaction Laboratory, Center for Automation Research, Dept. of Computer Science, Univ. of Maryland,
Andrew Sears. Ben Shneiderman. June 1989.
High Precision Touchscreens:. Three studies were conducted comparing speed of performance, error rates, and user preference ratings for three selection devices. The devices tested were a touchscreen, a touchscreen with stabilization (stabilization software filters and smooths raw data from hardware), and a mouse. The task was the selection of rectangular targets 1, 4, 16, and 32 pixels per side (0.4x0.6, 1.7x2.2, 6.9x9.0, 13.8x17.9 mm respectively). Touchscreen users were able to point at single pixel targets, thereby countering widespread expectations of poor touchscreen resolution. The results show no difference in performance between the mouse and touchscreen for targets ranging from 32 to 4 pixels per side. In addition, stabilization significantly reduced the error rates for the touchscreen when selecting small targets. These results imply that touchscreens, when properly used, have attractive advantages in selecting targets as small as 4 pixels per size (approximately one-quarter of the size of a single character). A variant of Fitts' Law is proposed to predict touchscreen pointing times. Ideas for future research are also presented. (Also cross-referenced as CAR-TR-450) Human Computer Interaction Laboratory, Center for Automation Research, Dept. of Computer Science, Univ. of Maryland, Institute for Systems Research,
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