Video
BibTex
@inproceedings{Rakhmetulla:2021:10.20380/GI2021.15,
author = {Rakhmetulla, Gulnar and Arif, Ahmed Sabbir and Castellucci, Steven J. and MacKenzie, I. Scott and Seim, Caitlyn E.},
title = {Using Action-Level Metrics to Report the Performance of Multi-Step Keyboards},
booktitle = {Proceedings of Graphics Interface 2021},
series = {GI 2021},
year = {2021},
issn = {0713-5424},
isbn = {978-0-9947868-6-9},
location = {Virtual Event},
pages = {127 -- 137},
numpages = {11},
doi = {10.20380/GI2021.15},
publisher = {Canadian Information Processing Society},
}
Abstract
Computer users commonly use multi-step text entry methods on handheld devices and as alternative input methods for accessibility. These methods are also commonly used to enter text in languages with large alphabets or complex writing systems. These methods require performing multiple actions simultaneously (chorded) or in a specific sequence (constructive) to produce input. However, evaluating these methods is difficult since traditional performance metrics were designed explicitly for non-ambiguous, uni-step methods (e.g., QWERTY). They fail to capture the actual performance of a multi-step method and do not provide enough detail to aid in design improvements. We present three new action-level performance metrics: UnitER, UA, and UnitCX. They account for the error rate, accuracy, and complexity of multi-step chorded and constructive methods. They describe the multiple inputs that comprise typing a single character-action-level metrics observe actions performed to type one character, while conventional metrics look into the whole character. In a longitudinal study, we used these metrics to identify probable causes of slower text entry and input errors with two existing multi-step methods. Consequently, we suggest design changes to improve learnability and input execution.