在线教育数据的基本事件时间分析

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引用次数: 0

摘要

本章介绍了使用基本的时间到事件分析(“生存分析”的一种变体)从学习管理系统(LMS)数据门户数据集中识别时间序列模式,以实现基于经验的理论化和解释。这种方法解决了以下问题:在特定事件发生之前通常需要多长时间?在经验数据中可以看到什么样的时间模式?从时间模式中可以理解什么样的分析和决策?本章使用多个数据集来演示这个过程,这些数据集与作业提交和评分时间、学习者注册和这些注册的更新、小组成员和小组持续的时间以及其他数据有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Basic Time-to-Event Analyses of Online Educational Data
This chapter introduces the use of basic time-to-event analysis (a variation of “survival analysis”) to identify time-series patterns from learning management system (LMS) data portal datasets to enable empirical-based theorizing and interpretation. This approach addresses questions such as How long does it usually take before a particular event occurs? What time patterns may be seen in empirical data? What sorts of analysis and decision making can be understood from the time patterns? This chapter uses multiple datasets—related to assignment submittals and their time to grading, learner enrollments and the updates to those enrollments, and group membership and how long groups last, and other data—to demonstrate this process.
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