Batmaz, Anıl UfukMutasim, A.K.Batmaz, A.U.Hudhud Mughrabi, M.Stuerzlinger, W.2023-10-192023-10-1920239781450394222https://doi.org/10.1145/3544549.3585647https://hdl.handle.net/20.500.12469/4947ACM SIGCHI;Apple;Bloomberg;Google;NSF;SIEMENS2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 --23 April 2023 through 28 April 2023 -- --188037To 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 estimate of expert performance. To validate this method, we set up a study where participants were tasked with typing the same phrase 96 times for both OPTI and QWERTY. Results showed that this approach has the potential to estimate expert performance for novel/unfamiliar keyboards faster than the traditional approach with different phrases. Yet, we also found that accurate estimates still require training over several days and, therefore, do not eliminate the need for a longitudinal study. Our findings thus show the need for research on faster, easier, and more reliable empirical approaches to evaluate text entry systems. © 2023 Owner/Author.eninfo:eu-repo/semantics/closedAccessOPTIQWERTYSoft KeyboardsTap TypingText EntryTouch TypingExpert performanceKeyboard layoutLongitudinal studyOPTIPerformanceQWERTYSoft keyboardTap typingText entryTouch typingTapsConference Object10.1145/3544549.35856472-s2.0-85158142414N/AN/A1