Data Everyday: Data Literacy Practices in a Division I College Sports Context
Data Everyday: Data Literacy Practices in a Division I College Sports Context
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日常数据：一级大学体育背景下的数据素养实践
DOI：
10.1145/3313831.3376153
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Jasmine Brunson
中科院分区：
文献类型：
--
作者：
Tamara L. Clegg;Daniel M. Greene;Nate Beard;Jasmine Brunson
数据分析是运动训练的核心。今天，尖端的数字技术被部署来衡量和提高运动员的表现。但研究人员往往把重点放在收集成绩数据的技术上，而忽视了对运动员数据体验的理解。尤其是在大学田径研究不足的背景下，竞争激烈，数据分析工具比比皆是，该机构积极管理运动员的生活。通过调查学生运动员是如何分析他们的成绩数据并依次进行分析的，我们可以更好地理解使数据素养练习在田径中有意义和富有成效的个人和制度因素--或者没有。我们对一所第一师大学的学生运动员进行的试验性访谈研究揭示了一系列学生运动员参与数据分析实践并从中学习的机会。这些机会伴随着一系列背景紧张，应该会为大学体育环境中的新技术设计提供依据。
Data analysis is central to sports training. Today, cutting-edge digital technologies are deployed to measure and improve athletes' performance. But too often researchers focus on the technology collecting performance data at the expense of understanding athletes' experiences with data. This is particularly the case in the understudied context of collegiate athletics, where competition is fierce, tools for data analysis abound, and the institution actively manages athletes' lives. By investigating how student-athletes analyze their performance data and are analyzed in turn, we can better understand the individual and institutional factors that make data literacy practices in athletics meaningful and productive-or not. Our pilot interview study of student-athletes at one Division I university reveals a set of opportunities for student-athletes to engage with and learn from data analytics practices. These opportunities come with a set of contextual tensions that should inform the design of new technologies for collegiate sports settings.
影响因子：
5
作者：
Greene, Daniel;Shilton, Katie
通讯作者：
Shilton, Katie
HistoryTracker：最大限度地减少棒球比赛注释中的人机交互
DOI：
10.1145/3290605.3300293
发表时间：
2019
期刊：
CHI '19 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
影响因子：
--
作者：
One, Jorge Piazentin;Gjoka, Arvi;Salamon, Justin;Dietrich, Carlos;Silva, Claudio T.
通讯作者：
Silva, Claudio T.