Co-Designing for Privacy, Transparency, and Trust in K-12 Learning Analytics

June Ahn, Fabio Campos, Ha Nguyen, Maria Hays, Janina Morrison
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引用次数: 7

Abstract

The process of using Learning Analytics (LA) to improve teaching works from the assumption that data should be readily shared between stakeholders in an educational organization. However, the design of LA tools often does not account for considerations such as data privacy, transparency and trust among stakeholders. Research in human-centered design of LA does attend to these questions, specifically with a focus on including direct input from K-12 educators. In this paper, we present a series of design studies to articulate and refine conjectures about how privacy and transparency might influence better trust-building and data sharing within four school districts in the United States. By presenting the development of four sequential prototypes, our findings illuminate the tensions between designing for existing norms versus potentially challenging these norms by promoting meaningful discussions around the use of data. We conclude with a discussion about practical and methodological implications of our work to the LA community.
K-12学习分析中隐私、透明度和信任的共同设计
使用学习分析(LA)来改进教学工作的过程是基于这样的假设,即数据应该在教育组织的利益相关者之间随时共享。然而,LA工具的设计往往没有考虑到数据隐私、透明度和利益相关者之间的信任等因素。洛杉矶以人为本的设计研究确实关注这些问题,特别是关注包括K-12教育工作者的直接投入。在本文中,我们提出了一系列设计研究,以阐明和完善有关隐私和透明度如何影响美国四个学区更好地建立信任和数据共享的猜想。通过展示四个连续原型的发展,我们的发现阐明了为现有规范设计与通过促进围绕数据使用的有意义的讨论来潜在地挑战这些规范之间的紧张关系。最后,我们讨论了我们的工作对洛杉矶社区的实践和方法意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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