Modeling the Endpoint Uncertainty in Crossing-based Moving Target Selection

要旨

Modeling the endpoint uncertainty of moving target selection with crossing is essential to understand factors such as speed-accuracy trade-off and interaction efficiency in crossing-based user interfaces with dynamic contents. However, there have been few studies looking into this research topic in the HCI field. This paper presents a Quaternary-Gaussian model to quantitatively measure the endpoint uncertainty in crossing-based moving target selection. To validate this model, we conducted an experiment with discrete crossing tasks on five factors, i.e., initial distance, size, speed, orientation, and moving direction. Results showed that our model fit the data of ? and ? accurately with adjusted R2 of 0.883 and 0.920. We also demonstrated the validity of our model in predicting error rates in crossing-based moving target selection. We concluded with a set of implications for future designs.

受賞
Honorable Mention
キーワード
Crossing-based Selection
Moving Target Selection
Endpoint Distribution
Error Rate
著者
Jin Huang
Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijin, China
Feng Tian
Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China
Xiangmin Fan
Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China
Huawei Tu
La Trobe University, Melbourne, VIC, Australia
Hao Zhang
Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China
Xiaolan Peng
Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China
Hongan Wang
Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China
DOI

10.1145/3313831.3376336

論文URL

https://doi.org/10.1145/3313831.3376336

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: Models & measurement

Paper session
316C MAUI
5 件の発表
2020-04-30 23:00:00
2020-05-01 00:15:00
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