The Effects of Predictive Features of Mobile Keyboards on Text Entry Speed and Errors

Author:

Alharbi Ohoud1,Stuerzlinger Wolfgang2,Putze Felix3

Affiliation:

1. Simon Fraser University & King Saud University, Vancouver, BC, Canada

2. Simon Fraser University, Vancouver, BC, Canada

3. University of Bremen, Bremen, Germany

Abstract

Mobile users rely on typing assistant mechanisms such as prediction and autocorrect. Previous studies on mobile keyboards showed decreased performance for heavy use of word prediction, which identifies a need for more research to better understand the effectiveness of predictive features for different users. Our work aims at such a better understanding of user interaction with autocorrections and the prediction panel while entering text, in particular when these approaches fail. We present a crowd-sourced mobile text entry study with 170 participants. Our mobile web application simulates autocorrection and word prediction to capture user behaviours around these features. We found that using word prediction saves an average of 3.43 characters per phrase but also adds an average of two seconds compared to actually typing the word, resulting in a negative effect on text entry speed. We also identified that the time to fix wrong autocorrections is on average 5.5 seconds but that autocorrection does not have a significant effect on typing speed.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Typing Behavior is About More than Speed: Users' Strategies for Choosing Word Suggestions Despite Slower Typing Rates;Proceedings of the ACM on Human-Computer Interaction;2023-09-11

2. The Value of Open Data in HCI: A Case Report from Mobile Text Entry Research;Multimodal Technologies and Interaction;2022-08-23

3. Exploring Spatial UI Transition Mechanisms with Head-Worn Augmented Reality;CHI Conference on Human Factors in Computing Systems;2022-04-29

4. Design and Analysis of Intelligent Text Entry Systems with Function Structure Models and Envelope Analysis;Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems;2021-05-06

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