Predicting Communication Rates: Efficacy of a Scanning Model

Interaction with the surrounding environment is an essential element of ever day life. For individuals' with severe motor and communicative disabilities, single switch scanning is used as method to control their environment and communicate. Despite being very slow, it is often the only option for individuals who cannot use other interfaces. The alteration of timing parameters and scanning system configurations impacts the communication rate of those using single switch scanning. The ability to select and recommend an efficient configuration for an individual with a disability is essential. Predictive models could assist in the goal of achieving the best possible match between user and assistive technology device, but consideration of an individual's single switch scanning tendencies has not been included in communication rate prediction models. Modeling software developed as part of this research study utilizes scan settings, switch settings, error tendencies, error correction strategies, and the matrix configuration to calculate and predict a communication rate. Five participants with disabilities who use single switch scanning were recruited for this study. Participants were asked to transcribe sentences using an on-screen keyboard configured with settings used on their own communication devices. The participant's error types, frequencies, and correction methods were acquired as well as their text entry rate (TER) during sentence transcription. These individual tendencies and system configuration were used as baseline input parameters to a scanning model application that calculated a TER based upon those parameters. The scanning model was used with the participant's tendencies and at least three varied system configurations. Participants were asked to transcribe sentences with these three configurations The predicted TERs of the model were compared to the actual TERs observed during sentence transcription for accuracy. Results showed that prediction were 90% accurate on average. Model TER predictions were less than one character per minute different from observed baseline TER for each participant. Average model predictions for configuration scenarios were less than one character per minute different from observed configuration TER

Factors Which Influence Key Entry Speed On Hard and Soft Keyboards: Experience, Eye Behaviors and Finger Movements

Soft keyboards have become ubiquitous, especially with the introduction of the iPad. This study aims to determine for experienced touch typists whether there are characteristics of soft QWERTY keyboards that can make them easier to use and why those characteristics provide an advantage. Two characteristics would appear to be of central importance. First, hard keyboards provide home row positioning information that is not as easily provided by soft keyboards. Second, hard keyboards also provide auditory and tactile feedback when a key is depressed, something not generally provided with soft keyboards. In order to test the hypothesis that the absence of home row positioning and key strike feedback information can reduce expert touch typists’ speeds on soft keyboards, expert touch typists were run in two experiments. In Experiment 1, soft and hard keyboards in landscape and portrait mode were evaluated. The hard keyboards had the standard home row positioning and key strike feedback whereas the soft keyboards had neither. If these are important elements in typing speed, then experienced hard keyboard typists should type less quickly when using soft keyboards than when using hard keyboards. Moreover, if reducing the footprint of the keyboard, from landscape to portrait, requires more eye movements, then typists using both hard and soft keyboards should be slower when using the portrait size keyboard than when using the landscape size keyboard. Perhaps not surprisingly, experienced hard keyboard touch typists do less well when entering information on soft keyboards without home row positioning information or auditory feedback. Moreover, both groups appear to type more slowly in keyboards laid out in a portrait format than they do in keyboards laid out in a landscape format. In summary, the results from Experiment 1 suggest that both home row positioning information and auditory key strike feedback should speed performance. In Experiment 2, an attempt was made to determine just how much of a gain can be made in the typing speed of more experienced soft keyboard users if home row positioning information (tactile feedback), auditory feedback, or both are added. Participants were run in four conditions: auditory key strike feedback (with and without) was crossed with tactile home row positioning information (with and without). Participants included expert level hard keypad QWERTY touch typists who have had at least five hours’ typing experience with an iPad. Participants were given four passages to type, all of equal length and all balanced for letter frequency. Participants typed one passage in each of the four conditions. The passage sequence was counterbalanced across participants. Typing speeds for each of the passages was measured and averaged across participants within conditions. A repeated measures analysis of variance was used to determine whether there was a main effect of position or feedback. In order to determine why it is that home row positioning and key strike feedback alters performance, eye behaviors, movement times and task completion times are calculated. If home row position information is important, soft keyboards without this information may have a larger number of glances that a typist directs at the keyboard. These glances will help the typist determine either whether a finger is positioned over the correct home key (the launch key) or whether the location of the key to be typed next (the target key) is in the expected position. If key strike feedback is important, soft keyboards without this information should have longer movement times where the typists do not need to glance at the keyboard. This follows since the typist will process less quickly the fact that a finger has landed on a key. Key press and key release times will be included each time a character, number or spacebar is depressed or releases. The finger movement time between any pair of keys i and j will be derived from the key press and key release times. This time will be measured from the moment the finger leaves the launch key i until the moment that the finger arrives at the target key j. Task completion times were defined as the difference between the first key press in a passage and the last key release. Finger movement times, inter-keystroke intervals and task completion times were recorded using a program developed in JAVA 2SE. Eye movements are recorded with aid of an ASL Mobile EYE tracker. Analyses of the finger movement times and task completions times in Experiment 2 indicated that participants were fastest when both position information and auditory feedback were included. When just finger movement times are considered, there was a significant effect of auditory feedback but not of positioning information. This was what was expected given that the speed of finger movement times is arguably largely a function of how quickly a typist perceives that a movement has been completed, something that auditory feedback, but not positioning information provides. When just the task completion times were analyzed, position information had a significant effect. The effect of auditory feedback was only marginally significant. It was expected that both factors would be significant. Perhaps the power was too small. Finally, when the eye movements were analyzed, the total scanning time was shortest when both position information and auditory feedback were available. The effects of both were statistically significant. In summary, on the basis of the results from Experiment 1 it appeared likely that auditory feedback and positioning information accounted in part for the faster typing times of touch typists on hard keyboards as opposed to soft keyboards. In Experiment 2, this hypothesis was evaluated. Finger movement and task completion times were fastest when both auditory feedback and positioning information were present. The effect of auditory feedback appeared to impact only the finger movement times. The effect of both auditory feedback and positioning information appeared to impact the task completion times. However, the effect of auditory feedback on task completion times was only marginal. Finally, it was clear that much of the reduction in task completion times occurred because the time that the touch typists spent scanning the keyboard was smaller when both auditory feedback and positioning information was available. It is recommended in the future that soft keyboards have both sets of feedback available, auditory (through simulated key clicks) and tactile (through home row positioning information). The gains in typing speed with these additions were models (about 10%), considered over the entire population of users the impact could be considerable

Medical Benefits from Space Research

Medical benefits resulting from utilization of devices and techniques of space research within NASA progra

FlexType: Flexible Text Input with a Small Set of Input Gestures

In many situations, it may be impractical or impossible to enter text by selecting precise locations on a physical or touchscreen keyboard. We present an ambiguous keyboard with four character groups that has potential applications for eyes-free text entry, as well as text entry using a single switch or a brain-computer interface. We develop a procedure for optimizing these character groupings based on a disambiguation algorithm that leverages a long-span language model. We produce both alphabetically-constrained and unconstrained character groups in an offline optimization experiment and compare them in a longitudinal user study. Our results did not show a significant difference between the constrained and unconstrained character groups after four hours of practice. As expected, participants had significantly more errors with the unconstrained groups in the first session, suggesting a higher barrier to learning the technique. We therefore recommend the alphabetically-constrained character groups, where participants were able to achieve an average entry rate of 12.0 words per minute with a 2.03% character error rate using a single hand and with no visual feedback

Keystroke Saving in a Language with Highly Transparent Orthography

This paper proposes a pseudo-syllabic soft keyboard for the Croatian language. The orthogonal keyboard layout makes it possible to improve typing efficiency in terms of keystroke saving, and is based on a highly ordered arrangement of pseudo-syllabic keys. The positions of the consonant and vowel graphemes that constitute a pseudo-syllable are used to access it orthogonally and independently each other. This allows the user to input a pseudo-syllable with a lower cognitive load than with non-orthogonal 2-D layouts. Moreover, due to the almost perfect transparency of the language, a pseudo-syllable to be input can be accessed fast and with a reduced cognitive load starting from its phonetic sounds. The results of the present study show that the obtainable keystroke savings are comparable with those scored by word prediction tools with one suggestion, i.e., those requiring only a moderate cognitive load by the user

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use

The Current Utilization of Graphic Data Processing in Industry and Education with Implications for Industrial Arts

A thesis presented to the faculty of the School of Education at Morehead State University in partial fulfillment of the requirements for the Degree of Master of Arts in Education by Chester Steven Rzonca in May of 1967

Who Uses Inferior Voting Technology?

In this article, we report on the incidence of punch-card and other voting equipment by ethnicity, incomes and other variables, combining county-level demographic data from the Census Bureau with county-level data on voting equipment collected by Election Data Services, Inc. Our findings, widely reported in the national print and electronic media in late January and February of 2001, provide remarkably little support for the view that resource constraints cause poorer counties with large minority populations to retain antiquated or inferior voting equipment.voting, elections