Higher education institutions are mining and analyzing student data to effect educational, political, and managerial outcomes. Done under the banner of “learning analytics,” this work can—and often does—surface sensitive data and information about, inter alia, a student's demographics, academic performance, offline and online movements, physical fitness, mental wellbeing, and social network. With these data, institutions and third parties are able to describe student life, predict future behaviors, and intervene to address academic or other barriers to student success (however defined). Learning analytics, consequently, raise serious issues concerning student privacy, autonomy, and the appropriate flow of student data. We argue that issues around privacy lead to valid questions about the degree to which students should trust their institution to use learning analytics data and other artifacts (algorithms, predictive scores) with their interests in mind. We argue that higher education institutions are paradigms of information fiduciaries. As such, colleges and universities have a special responsibility to their students. In this article, we use the information fiduciary concept to analyze cases when learning analytics violate an institution's responsibility to its students.

中文翻译：

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信任问题：高等教育机构作为教育数据挖掘和学习分析时代的信息受托人

高等教育机构正在挖掘和分析学生数据以影响教育、政治和管理成果。在“学习分析”的旗帜下进行的这项工作可以——而且经常会——暴露敏感数据和信息，尤其是关于学生的人口统计、学习成绩、离线和在线活动、身体健康、心理健康和社交网络。有了这些数据，机构和第三方就能够描述学生的生活、预测未来的行为，并进行干预以解决学生成功的学业或其他障碍（无论如何定义）。因此，学习分析会引发有关学生隐私、自主性和学生数据适当流动的严重问题。我们认为，围绕隐私的问题会引发关于学生应该在多大程度上信任他们的机构以根据他们的兴趣使用学习分析数据和其他工件（算法、预测分数）的有效问题。我们认为高等教育机构是信息受托人的典范。因此，学院和大学对学生负有特殊的责任。在本文中，我们使用信息受托概念来分析学习分析违反机构对其学生的责任的案例。