摘要
There has been increasing interest in data enclaves in recent years, both in education and other fields. Data enclaves make it possible to conduct analysis on large-scale and higher-risk data sets, while protecting the privacy of the individuals whose data is included in the data sets, thus mitigating risks around data disclosure. In this article, we provide a post-mortem on the MORF (MOoc Replication Framework) 2.1 infrastructure, a data enclave expected to sunset and be replaced in the upcoming years, reviewing the core factors that reduced its usefulness for the community. We discuss challenges to researchers in terms of usability, including challenges involving learning to use core technologies, working with data that cannot be directly viewed, debugging, and working with restricted outputs. Our post-mortem discusses possibilities for ways that future infrastructures could get past these challenges.
摘要译文
近年来，人们对教育和其他领域的数据飞地越来越感兴趣。 数据包使对大规模和高风险数据集进行分析成为可能，同时保护数据被纳入数据集的个人的隐私，从而降低数据披露的风险。 在本文中，我们提供了 MORF（MOoc Replication Framework）2.1 基础结构的事后分析，并回顾了降低其对社区有用性的核心因素。 我们讨论了在可用性方面对研究人员的挑战，包括学习使用核心技术、使用无法直接查看的数据、调试以及使用受限输出等方面的挑战。 我们的事后分析讨论了未来基础架构如何克服这些挑战的可能性。
Ryan Baker[1];Stephen Hutt[2]. MORF: A Post-Mortem[C]//LAK '25: Proceedings of the 15th International Learning Analytics and Knowledge Conference, Dublin Ireland, March 3 - 7, 2025, IE: ACM, 2025: 797 - 802