Multidimensional Pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking

The paper presents a new optimization technique for keyboard layouts based on Pareto front optimization. We used this multifactorial technique to create two new touchscreen phone keyboard layouts based on three design metrics: minimizing finger travel distance in order to maximize text entry speed, a new metric to maximize the quality of spell correction quality by minimizing neighbouring key ambiguity, and maximizing familiarity through a similarity function with the standard Qwerty layout. The paper describes the optimization process and resulting layouts for a standard trapezoid shaped keyboard and a more rectangular layout. Fitts' law modelling shows a predicted 11% improvement in entry speed without taking into account the significantly improved error correction potential and the subsequent effect on speed. In initial user tests typing speed dropped from approx. 21wpm with Qwerty to 13wpm (64%) on first use of our layout but recovered to 18wpm (85%) within four short trial sessions, and was still improving. NASA TLX forms showed no significant difference on load between Qwerty and our new layout use in the fourth session. Together we believe this shows the new layouts are faster and can be quickly adopted by users

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

Multi-touch For General-purpose Computing An Examination Of Text Entry

In recent years, multi-touch has been heralded as a revolution in humancomputer interaction. Multi-touch provides features such as gestural interaction, tangible interfaces, pen-based computing, and interface customization – features embraced by an increasingly tech-savvy public. However, multi-touch platforms have not been adopted as everyday computer interaction devices; that is, multi-touch has not been applied to general-purpose computing. The questions this thesis seeks to address are: Will the general public adopt these systems as their chief interaction paradigm? Can multi-touch provide such a compelling platform that it displaces the desktop mouse and keyboard? Is multi-touch truly the next revolution in human-computer interaction? As a first step toward answering these questions, we observe that generalpurpose computing relies on text input, and ask: Can multi-touch, without a text entry peripheral, provide a platform for efficient text entry? And, by extension, is such a platform viable for general-purpose computing? We investigate these questions through four user studies that collected objective and subjective data for text entry and word processing tasks. The first of these studies establishes a benchmark for text entry performance on a multi-touch platform, across a variety of input modes. The second study attempts to improve this performance by iv examining an alternate input technique. The third and fourth studies include mousestyle interaction for formatting rich-text on a multi-touch platform, in the context of a word processing task. These studies establish a foundation for future efforts in general-purpose computing on a multi-touch platform. Furthermore, this work details deficiencies in tactile feedback with modern multi-touch platforms, and describes an exploration of audible feedback. Finally, the thesis conveys a vision for a general-purpose multi-touch platform, its design and rationale

Attention Demands in Text Entry Interfaces

The rationale for a model of text input that includes perceptual and cognitives processes is given. Reducing keystrokes is fine, but if the design imposes an increased perceptual and/or cognitive load on the user (e.g., shifting attention points or perusing a list of candidate words in a word completion system), then a newinterface may not be as efficient as first thought. This argument as well as others underscoring the need to more thoroughly acknowledge and quantifiy attention demans in text entry interface are developed

An adaptable scan-based text entry for mobile devices: Design, predictive modeling, and empirical evaluation

This paper presents a highly customizable assistive on-screen keyboard for mobile devices, which supports several text entry methods based on row-column and bisection scanning techniques. Text entry can be accomplished using a zone based touch screen interface and/or via hardware keypads, involving configurable input control which can range from single-switch solution up to 5-key design. Apart from the presentation of a novel user interface, the paper contributions are as follows: development of movement models for all scan-based methods involved in text entry solution, computation of related upper-bound text entry speed predictions, and empirical investigation of their validity. In order to assess model predictions, a specific instance of row-column scanning technique was juxtaposed to bisection scanning principle in a user study involving 16 participants. Methods are evaluated against text entry performance, required workload, and general usability attributes. Although theoretical models predicted higher entry speed for bisection scanning, the results obtained from experiment demonstrated the row-column technique as significantly more efficient. This outcome discrepancy is specifically discussed by putting emphasis on factors that affect identified relation.

Predicting and Reducing the Impact of Errors in Character-Based Text Entry

This dissertation focuses on the effect of errors in character-based text entry techniques. The effect of errors is targeted from theoretical, behavioral, and practical standpoints. This document starts with a review of the existing literature. It then presents results of a user study that investigated the effect of different error correction conditions on popular text entry performance metrics. Results showed that the way errors are handled has a significant effect on all frequently used error metrics. The outcomes also provided an understanding of how users notice and correct errors. Building on this, the dissertation then presents a new high-level and method-agnostic model for predicting the cost of error correction with a given text entry technique. Unlike the existing models, it accounts for both human and system factors and is general enough to be used with most character-based techniques. A user study verified the model through measuring the effects of a faulty keyboard on text entry performance. Subsequently, the work then explores the potential user adaptation to a gesture recognizer’s misrecognitions in two user studies. Results revealed that users gradually adapt to misrecognition errors by replacing the erroneous gestures with alternative ones, if available. Also, users adapt to a frequently misrecognized gesture faster if it occurs more frequently than the other error-prone gestures. Finally, this work presents a new hybrid approach to simulate pressure detection on standard touchscreens. The new approach combines the existing touch-point- and time-based methods. Results of two user studies showed that it can simulate pressure detection more reliably for at least two pressure levels: regular (~1 N) and extra (~3 N). Then, a new pressure-based text entry technique is presented that does not require tapping outside the virtual keyboard to reject an incorrect or unwanted prediction. Instead, the technique requires users to apply extra pressure for the tap on the next target key. The performance of the new technique was compared with the conventional technique in a user study. Results showed that for inputting short English phrases with 10% non-dictionary words, the new technique increases entry speed by 9% and decreases error rates by 25%. Also, most users (83%) favor the new technique over the conventional one. Together, the research presented in this dissertation gives more insight into on how errors affect text entry and also presents improved text entry methods

Predictive text-entry in immersive environments

Virtual Reality (VR) has progressed significantly since its conception, enabling previously impossible applications such as virtual prototyping, telepresence, and augmented reality However, text-entry remains a difficult problem for immersive environments (Bowman et al, 2001b, Mine et al , 1997). Wearing a head-mounted display (HMD) and datagloves affords a wealth of new interaction techniques. However, users no longer have access to traditional input devices such as a keyboard. Although VR allows for more natural interfaces, there is still a need for simple, yet effective, data-entry techniques. Examples include communicating in a collaborative environment, accessing system commands, or leaving an annotation for a designer m an architectural walkthrough (Bowman et al, 2001b). This thesis presents the design, implementation, and evaluation of a predictive text-entry technique for immersive environments which combines 5DT datagloves, a graphically represented keyboard, and a predictive spelling paradigm. It evaluates the fundamental factors affecting the use of such a technique. These include keyboard layout, prediction accuracy, gesture recognition, and interaction techniques. Finally, it details the results of user experiments, and provides a set of recommendations for the future use of such a technique in immersive environments

The effect of typewriting vs. handwriting lecture notes on learning: a systematic review and meta-analysis.

This study is a systematic review and meta-analysis of studies examining the effect of note-taking modality during lecture, that is, taking notes by hand using pen and paper vs. taking notes using a keyboard and computer, on learning among secondary and postsecondary students. I begin with a review of the literature and theoretical introduction to the theories and terms used. From a theoretical standpoint, there are strong reasons to believe that taking notes by hand might offer recall benefits relative to taking notes using a computer and keyboard. At the same time, I point out that one problem, which I term the “fundamental problem of modality research”, is that when researchers randomly assign participants to a note-taking modality they are also, indirectly, assigning them to a note-taking style. Furthermore, most studies do not consider factors such as participant transcription capacity that might serve as theoretically important moderators. I then describe the methods used for the systematic review and meta-analysis. These included a robust literature search, double screening of all potentially eligible studies, and double coding of all eligible studies. The meta-analytic methods involved multilevel applications of standard meta-analytic methods. The systematic review resulted in identification of 33 eligible reports containing 42 independent samples and 88 effect sizes, all evaluating whether there are recall differences — almost always operationalized as scores on a quiz given after exposure to lecture material — between participants taking notes by handwriting vs. typewriting, that is, the modality effect. A statistically significant overall meta-analytic average was found g = +0.144 [0.023, 0.265], p = .021, benefiting handwriters over typewriters. This is a small effect; on average, in the typical study typewriters scored about 50% on the recall quiz. The effect size of g = +0.14 translates into an average percent correct of about 57% in the handwriting group. There is some evidence that providing participants with an opportunity to review their notes might substantially reduce the observed advantage for handwriters