Effect of the User Input Method on Response Time and Accuracy in a Binary Data Labeling Task

Abstract

This study compares response time and accuracy in a binary data labeling task on two platforms: a desktop computer and a mobile phone. Three methods were used on the computer: a keyboard, a mouse, and a mouse with perceptual variability that was designed to combat vigilance decrement. Three additional methods were used on the mobile phone: a tap, a swipe touch-gesture, and a tap with perceptual variability. Results of the study show that the fastest was the keyboard, which may explain its popularity in labeling tasks. The second fastest was the tap interface, suggesting the unexploited potential of mobile devices for “labeling while waiting for the bus.” In terms of accuracy, we found clear evidence for a speed–accuracy tradeoff, and the advantage of the perceptual variability methods to be more accurate than the matching methods without perceptual variability. The results suggest that different user input methods should be employed depending on whether response time or accuracy is more valued.

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Correction

Correction Statement

This article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/10447318.2022.2135250).

Acknowledgments

We would like to thank the R core team (2014) for providing the R software program. We would also like to thank Douglas Bates and his team for providing the lme4 package (2015), and the teams that built and provided the following packages: dplyr, readxl, multcomp, ggplot2, ggridges, lmerTest, nlme, and summarytools.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Yehuda Nathan

Yehuda Nathan received both his M.Sc.Eng in Industrial Engineering specializing in Ergonomics, and his B.A in Psychology and Cognitive science from Ben-Gurion University of the Negev. His current research interests are the long-term effects of digital marketing in the online world.

Jonathan D. Rosenblatt

Jonathan D. Rosenblatt is currently a senior data scientist with Pagaya Technology. Previously Dr. Rosenblatt served as a senior lecturer of statistics at the Department of Industrial Engineering and Management at Ben-Gurion University of the Negev.

Yuval Bitan

Yuval Bitan is a senior lecturer in the Department of Health Policy and Management at Ben-Gurion University of the Negev, and the founding director of SimReC - The research center for simulation in healthcare. He received his PhD in Industrial Engineering and Management (2003) from Ben-Gurion University of the Negev.