R. William Soukoreff

Text entry using soft keyboards

Text entry rates are explored for several variations of soft keyboards. We present a model to predict novice and expert entry rates and present an empirical test with 24 subjects. Six keyboards were examined: the Qwerty, ABC, Dvorak, Fitaly, JustType, and telephone. At 8-10 wpm, novice predictions are low for all layouts because the dominant factor is the visual scan time, rather than the movement time. Expert predictions are in the range of 22-56 wpm, although these were not tested empirically. In a quick, novice test with a representative phrase of text, subjects achieved rates of 20.2 wpm (Qwerty), 10.7 wpm (ABC), 8.5 wpm (Dvorak), 8.0 wpm (Fitaly), 7.0 wpm (JustType), and 8.0 wpm (telephone). The Qwerty rate of 20.2 wpm is consistent with observations in other studies. The relatively high rate for Qwerty suggests that there is skill transfer from users familiarity with desktop computers to the stylus tapping task.

Theoretical upper and lower bounds on typing speed using a stylus and a soft keyboard

Abstract A theoretical model is presented to predict upper-and lower-bound text-entry rates using a stylus to tap on a soft QWERTY keyboard. The model is based on the Hick-Hyman law for choice reaction time, Fitts law for rapid aimed movements, and linguistic tables for the relative frequencies of letter-pairs, or digrams, in common English. The models importance lies not only in the predictions provided, but in its characterization of text-entry tasks using keyboards. Whereas previous studies only use frequency probabilities of the 26 × 26 digrams in the Roman alphabet, our model accommodates the space har—the most common character in typing tasks. Using a very large linguistic table that decomposes digrams by position-within-words, we established start-of-word (space-letter) and end-of-word (letter-space) probabilities and worked from a 27 × 27 digram table. The model predicts a typing rate of 8.9wpm for novices unfamiliar with the QWERTY keyboard, and 30.1wpm for experts. Comparisons are drawn with em...

A two-ball mouse affords three degrees of freedom

We describe a prototype two-ball mouse containing the electronics and mechanics of two mice in a single chassis. Unlike a conventional mouse, which senses x-axis and y-axis displacement only, our mouse also senses z-axis angular motion. This is accomplished through simple calculations on the two sets of x-y displacement data. Our mouse looks and feels like a standard mouse, however certain primitive operations are performed with much greater ease. The rotate tool -- common in most drawing programs -- becomes redundant as objects are easily moved with three degrees of freedom. Mechanisms to engage the added degree of freedom and different interaction techniques are discussed.

Generalized Fitts' law model builder

A tool for designing experiments, capturing data, and building Fitts’ law models is described. The software runs on an IBM or compatible computer equipped with an appropriate graphical display and selection device (e.g., mouse, joystick). Features intended for HCI educational purposes or experimental research are included, making this a very powerful utility for research in input techniques or Fitts’ law. The software is available via anonymous FTP through the internet.

1 thumb, 4 buttons, 20 words per minute: design and evaluation of H4-writer

We present what we believe is the most efficient and quickest four-key text entry method available. H4-Writer uses Huffman coding to assign minimized key sequences to letters, with full access to error correction, punctuation, digits, modes, etc. The key sequences are learned quickly, and support eyes-free entry. With KSPC = 2.321, the effort to enter text is comparable to multitap on a mobile phone keypad; yet multitap requires nine keys. In a longitudinal study with six participants, an average text entry speed of 20.4 wpm was observed in the 10th session. Error rates were under 1%. To improve external validity, an extended session was included that required input of punctuation and other symbols. Entry speed dropped only by about 3 wpm, suggesting participants quickly leveraged their acquired skill with H4-Writer to access advanced features.

A model of scrolling on touch-sensitive displays

Abstract Scrolling interaction is a common and frequent activity allowing users to browse content that is initially off-screen. With the increasing popularity of touch-sensitive devices, gesture-based scrolling interactions (e.g., finger panning and flicking) have become an important element in our daily interaction vocabulary. However, there are currently no comprehensive user performance models for scrolling tasks on touch displays. This paper presents an empirical study of user performance in scrolling tasks on touch displays. In addition to three geometrical movement parameters—scrolling distance, display window size, and target width, we also investigate two other factors that could affect the performance, i.e., scrolling modes—panning and flicking, and feedback techniques—with and without distance feedback. We derive a quantitative model based on four formal assumptions that abstract the real-world scrolling tasks, which are drawn from the analysis and observations of user scrolling actions. The results of a control experiment reveal that our model generalizes well for direct-touch scrolling tasks, accommodating different movement parameters, scrolling modes and feedback techniques. Also, the supporting blocks of the model, the four basic assumptions and three important mathematical components, are validated by the experimental data. In-depth comparisons with existing models of similar tasks indicate that our model performs the best under different measurement criteria. Our work provides a theoretical foundation for modeling sophisticated scrolling actions, as well as offers insights into designing scrolling techniques for next-generation touch input devices.

Exploring and modeling unimanual object manipulation on multi-touch displays

Touch-sensitive devices are becoming increasingly wide-spread, and consequently gestural interfaces have become familiar to the public. Despite the fact that many gestures require frequently dragging, pinching, spreading, and rotating the finger-tips, there currently does not exist a human performance model describing this interaction. In this paper, a novel user performance model is derived for virtual object manipulation on touch-sensitive displays, which involves simultaneous translation, rotation, and scaling of the object. Two controlled experiments with dual-finger unimanual manipulations were conducted to validate the new model. The results indicate that the model fits the experimental data well (with R2 and R values above 0.9), and performs the best among several alternative models. Moreover, based on the analysis of the empirical data, the simultaneity nature of manipulation in the task is explored and several design implications are provided. HighlightsWe propose a quantitative model for unimanual dual-finger multi-touch manipulations.We conduct two formal experiments to explore the task nature and validate the model.Experimental results and comparisons indicate the excellent performance of our model.In-depth analysis and discussion provide insights of the task and implications for design.

The entropy of a rapid aimed movement: Fitts' index of difficulty versus Shannon's entropy

A thought experiment is proposed that reveals a difference between Fitts index of difficulty and Shannons entropy, in the quantification of the information content of a series of rapid aimed movements. This implies that the contemporary Shannon formulation of the index of difficulty is similar to, but not identical to, entropy. Preliminary work is reported toward developing a model that resolves the problem. Starting from first principles (information theory), a formulation for the entropy of a Fitts law style rapid aimed movement is derived, that is similar in form to the traditional formulation. Empirical data from Fitts 1954 paper are analysed, demonstrating that the new model fits empirical data as well as the current standard approach. The novel formulation is promising because it accurately describes human movement data, while also being derived from first principles (using information theory), thus providing insight into the underlying cause of Fitts law.