菲茨定律:计算吞吐量和非iso任务

Q4 Computer Science
Maria Francesca Roig-Maimó, I. Mackenzie, C. Manresa-Yee, Javier Varona Gómez
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引用次数: 0

摘要

我们使用目标选择任务来评估头部跟踪作为移动设备的输入法。首先,通过一个原始数据的详细实例描述了计算菲茨吞吐量的方法。然后,讨论了非iso任务的吞吐量计算方法,因为过程目标是随机定位的。由于每个试验序列的振幅不恒定,因此使用两种数据聚合方法计算吞吐量:第一种方法是使用平均振幅的试验序列,第二种方法是使用常见的a - w条件。对于每个数据集,我们使用了四种方法来计算吞吐量。吞吐量的大平均值(通过平均值划分和精度调整计算)为0.74 bps,比使用ISO任务获得的值低45%。我们建议使用均值除法加上精度调整来计算吞吐量,并避免使用回归模型的倒数斜率。我们对非iso任务提出了各种设计建议,例如:i)在每个试验序列中保持振幅和恒定的目标,以及ii)使用策略来避免或消除反应时间。关键词:Fitts定律,吞吐量,ISO 9241-411,移动HCI,头部跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fitts’ Law: On Calculating Throughput and Non-ISO Tasks
We used a target-selection task to evaluate head-tracking as an input method for mobile devices. First, the method of calculating Fitts’ throughput is described by means of a raw data detailed example. Then, the method of calculating throughput is discussed for non-ISO tasks, since the procedure targets were randomly positioned from trial to trial. Due to a non-constant amplitude within each sequence of trials, throughput was calculated using two methods of data aggregation: the first one, by sequence of trials using the mean amplitude, and the second one, by common A-W conditions. For each data set, we used four methods for calculating throughput. The grand mean for throughput (calculated through the division of means and the adjustment for accuracy) was of 0.74 bps, which is 45 % lower than the value obtained using an ISO task. We recommend to calculate throughput using the division of means plus the adjustment for accuracy, and to avoid using the reciprocal slope of the regression model. We present various design recommendations for non-ISO tasks, such as: i) to keep amplitude and constant target within each sequence of trials, and ii) to use strategies to avoid or remove reaction time. Keywords: Fitts’ law, throughput, ISO 9241-411, mobile HCI, head-tracking.
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来源期刊
Revista Colombiana de Computacion
Revista Colombiana de Computacion Computer Science-Computer Science (all)
CiteScore
0.90
自引率
0.00%
发文量
6
审稿时长
13 weeks
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