Maria Francesca Roig-Maimó, I. Mackenzie, C. Manresa-Yee, Javier Varona Gómez
{"title":"Fitts’ Law: On Calculating Throughput and Non-ISO Tasks","authors":"Maria Francesca Roig-Maimó, I. Mackenzie, C. Manresa-Yee, Javier Varona Gómez","doi":"10.29375/25392115.3226","DOIUrl":null,"url":null,"abstract":"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. \nKeywords: Fitts’ law, throughput, ISO 9241-411, mobile HCI, head-tracking.","PeriodicalId":36389,"journal":{"name":"Revista Colombiana de Computacion","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Colombiana de Computacion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29375/25392115.3226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
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.