From Study Tactics to Learning Strategies: An Analytical Method for Extracting Interpretable Representations
From Study Tactics to Learning Strategies: An Analytical Method for Extracting Interpretable Representations
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DOI：
10.1109/tlt.2018.2823317
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发表时间：
2019-01-01
影响因子：
3.7
通讯作者：
Pardo, Abelardo
中科院分区：
文献类型：
--
作者：
Fincham, Ed;Gasevic, Dragan;Pardo, Abelardo
对自我调节学习的研究传统上依赖于自我报告的数据。尽管有大量文献从这些来源中提取了宝贵的信息，但它仍然存在许多缺点。例如，研究表明，调查通常可以深入了解学生对学习的看法，而不是学生实际如何运用学习策略和学习策略。因此，最近的研究试图通过从数字学习环境收集的跟踪数据来评估学生的学习策略，进而评估他们的自我调节学习。许多研究充分证明了教育数据挖掘和学习分析方法在跟踪日志数据中识别指示学习策略的模式的能力。然而，这些方法中的许多方法在描述和解释不同粒度级别提取的潜在表示之间差异的能力方面受到限制（例如，就学生行为和行为的基础数据而言）。为了解决这一局限性，本研究提出了一种新的方法，通过该方法，可以在两个受理论启发的层面上得出学生自我调节行为的可解释表示：学习策略和构成它们的学习策略。
Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature that has extracted invaluable information from such sources, it suffers from a number of shortcomings. For instance, it has been shown that surveys often provide insight into students' perceptions about learning rather than how students actually employ study tactics and learning strategies. Accordingly, recent research has sought to assess students' learning strategies and, by extension, their self-regulated learning via trace data collected from digital learning environments. A number of studies have amply demonstrated the ability of educational data mining and learning analytics methods to identify patterns indicative of learning strategies within trace log data. However, many of these methods are limited in their ability to describe and interpret differences between extracted latent representations at varying levels of granularity (for instance, in terms of the underlying data of student actions and behavior). To address this limitation, the present study proposes a new methodology whereby interpretable representations of student's self-regulating behavior are derived at two theoretically inspired levels: that of learning strategies, and the study tactics that compose them.