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To identify if novel/unfamiliar keyboard layouts like OPTI can outperform QWERTY, lengthy training through longitudinal studies is typically required. To reduce this logistical bottleneck, a popular approach in the literature requires participants to type the same phrase repeatedly. However, it is still unknown whether this approach provides a good...
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... The outcomes of a first repeated phrase typing study show that this approach does not accurately estimate trained user-level text entry performance within a single day's training. Still, this approach can potentially produce good estimates, but only through a longitudinal study that takes multiple days [32]. We then investigate the approach of repeated word typing. ...
... However, as speculated by Jokinen et al. [18], while repeatedly typing the same word on an unfamiliar keyboard layout "may" demonstrate performance that outperforms QWERTY, typing the same phrase over and over may not exhibit the same results. Recently, we verified Jokinen et al.'s speculation that the approach of repeatedly typing the same phrase on an unfamiliar layout like OPTI does not outperform QWERTY within a single day's training [32]. That work also indicated that this approach is able to provide a good estimate of trained user performance and can do so faster than traditional training with different phrases [32]. ...
... Recently, we verified Jokinen et al.'s speculation that the approach of repeatedly typing the same phrase on an unfamiliar layout like OPTI does not outperform QWERTY within a single day's training [32]. That work also indicated that this approach is able to provide a good estimate of trained user performance and can do so faster than traditional training with different phrases [32]. Yet, doing this still requires training participants over several days, which is still equivalent to a longitudinal study, albeit a comparatively shorter one. ...
To determine in a user study whether proposed keyboard layouts, such as OPTI, can surpass QWERTY in performance, extended training through longitudinal studies is crucial. However, addressing the challenge of creating trained users presents a logistical bottleneck. A common alternative involves having participants type the same word or phrase repeatedly. We conducted two separate studies to investigate this alternative. The findings reveal that both approaches, repeatedly typing words or phrases, have limitations in accurately estimating trained user performance. Thus, we propose the Guided Evaluation Method (GEM), a novel approach to quickly estimate trained user performance with novices. Our results reveal that in a matter of minutes, participants exhibited performance similar to an existing longitudinal study -- OPTI outperforms QWERTY. As it eliminates the need for resource-intensive longitudinal studies, our new GEM thus enables much faster estimation of trained user performance. This outcome will potentially reignite research on better text entry methods.
Integrated hand-tracking on modern virtual reality (VR) headsets can be readily exploited to deliver mid-air virtual input surfaces for text entry. These virtual input surfaces can closely replicate the experience of typing on a Qwerty keyboard on a physical touchscreen, thereby allowing users to leverage their pre-existing typing skills. However, the lack of passive haptic feedback, unconstrained user motion, and potential tracking inaccuracies or observability issues encountered in this interaction setting typically degrades the accuracy of user articulations. We present a comprehensive exploration of error-tolerant probabilistic hand-based input methods to support effective text input on a mid-air virtual Qwerty keyboard. Over three user studies we examine the performance potential of hand-based text input under both gesture and touch typing paradigms. We demonstrate typical entry rates in the range of 20 to 30 wpm and average peak entry rates of 40 to 45 wpm.
