Quantifying Proactive and Reactive Button Input

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Standard

Quantifying Proactive and Reactive Button Input. / Kim, Hyunchul; Hornbæk, Kasper; Lee, Byungjoo.

CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2022. 40.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Harvard

Kim, H, Hornbæk, K & Lee, B 2022, Quantifying Proactive and Reactive Button Input. in CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems., 40, Association for Computing Machinery, 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022, Virtual, Online, United States, 30/04/2022. https://doi.org/10.1145/3491102.3501913

APA

Kim, H., Hornbæk, K., & Lee, B. (2022). Quantifying Proactive and Reactive Button Input. In CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems [40] Association for Computing Machinery. https://doi.org/10.1145/3491102.3501913

Vancouver

Kim H, Hornbæk K, Lee B. Quantifying Proactive and Reactive Button Input. In CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2022. 40 https://doi.org/10.1145/3491102.3501913

Author

Kim, Hyunchul ; Hornbæk, Kasper ; Lee, Byungjoo. / Quantifying Proactive and Reactive Button Input. CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2022.

Bibtex

@inproceedings{5e1620a1d6b2426a858eab84a3793fa9,
title = "Quantifying Proactive and Reactive Button Input",
abstract = "When giving input with a button, users follow one of two strategies: (1) react to the output from the computer or (2) proactively act in anticipation of the output from the computer. We propose a technique to quantify reactiveness and proactiveness to determine the degree and characteristics of each input strategy. The technique proposed in this study uses only screen recordings and does not require instrumentation beyond the input logs. The likelihood distribution of the time interval between the button inputs and system outputs, which is uniquely determined for each input strategy, is modeled. Then the probability that each observed input/output pair originates from a specific strategy is estimated along with the parameters of the corresponding likelihood distribution. In two empirical studies, we show how to use the technique to answer questions such as how to design animated transitions and how to predict a player's score in real-time games.",
keywords = "anticipation, Button input, reaction, temporal pointing",
author = "Hyunchul Kim and Kasper Hornb{\ae}k and Byungjoo Lee",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 ; Conference date: 30-04-2022 Through 05-05-2022",
year = "2022",
doi = "10.1145/3491102.3501913",
language = "English",
booktitle = "CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems",
publisher = "Association for Computing Machinery",

}

RIS

TY - GEN

T1 - Quantifying Proactive and Reactive Button Input

AU - Kim, Hyunchul

AU - Hornbæk, Kasper

AU - Lee, Byungjoo

N1 - Publisher Copyright: © 2022 ACM.

PY - 2022

Y1 - 2022

N2 - When giving input with a button, users follow one of two strategies: (1) react to the output from the computer or (2) proactively act in anticipation of the output from the computer. We propose a technique to quantify reactiveness and proactiveness to determine the degree and characteristics of each input strategy. The technique proposed in this study uses only screen recordings and does not require instrumentation beyond the input logs. The likelihood distribution of the time interval between the button inputs and system outputs, which is uniquely determined for each input strategy, is modeled. Then the probability that each observed input/output pair originates from a specific strategy is estimated along with the parameters of the corresponding likelihood distribution. In two empirical studies, we show how to use the technique to answer questions such as how to design animated transitions and how to predict a player's score in real-time games.

AB - When giving input with a button, users follow one of two strategies: (1) react to the output from the computer or (2) proactively act in anticipation of the output from the computer. We propose a technique to quantify reactiveness and proactiveness to determine the degree and characteristics of each input strategy. The technique proposed in this study uses only screen recordings and does not require instrumentation beyond the input logs. The likelihood distribution of the time interval between the button inputs and system outputs, which is uniquely determined for each input strategy, is modeled. Then the probability that each observed input/output pair originates from a specific strategy is estimated along with the parameters of the corresponding likelihood distribution. In two empirical studies, we show how to use the technique to answer questions such as how to design animated transitions and how to predict a player's score in real-time games.

KW - anticipation

KW - Button input

KW - reaction

KW - temporal pointing

UR - http://www.scopus.com/inward/record.url?scp=85130580979&partnerID=8YFLogxK

U2 - 10.1145/3491102.3501913

DO - 10.1145/3491102.3501913

M3 - Article in proceedings

AN - SCOPUS:85130580979

BT - CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

T2 - 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022

Y2 - 30 April 2022 through 5 May 2022

ER -

ID: 309121085