Real-Time Scaffolding of Students’ Online Data Interpretation During Inquiry with Inq-ITS Using Educational Data Mining
Real-Time Scaffolding of Students’ Online Data Interpretation During Inquiry with Inq-ITS Using Educational Data Mining
复制标题
使用教育数据挖掘通过 Inq-ITS 查询期间学生在线数据解释的实时支架
DOI：
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发表时间：
2018
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通讯作者：
Rachel Dickler
中科院分区：
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作者：
J. Gobert;Raha Moussavi;Haiying Li;M. S. Pedro;Rachel Dickler
本章讨论学生的数据解释，这是一个关键的NGSS探究实践，学生有几种不同类型的困难。在这项工作中，我们从与保证索赔相关的数据解释中揭示了与数据解释相关的困难。我们在Inq-ITS（探究智能辅导系统）的背景下进行这项工作，这是一个轻量级的LMS，为科学探究实践/技能提供基于计算机的评估和辅导。我们对数据子集进行了系统分析，以确定我们的脚手架是否支持学生获得和转移这些探究技能。我们还描述了另一项研究，该研究使用贝叶斯知识追踪（Corbett和Anderson）。用户模型User- adapt interaction 4(4): 253-278, 1995)，这是一种计算方法，允许对我们的数据解释和保证索赔实践中底层的细粒度子技能进行分析。
This chapter addresses students’ data interpretation, a key NGSS inquiry practice, with which students have several different types of difficulties. In this work, we unpack the difficulties associated with data interpretation from those associated with warranting claims. We do this within the context of Inq-ITS (Inquiry Intelligent Tutoring System), a lightweight LMS, providing computer-based assessment and tutoring for science inquiry practices/skills. We conducted a systematic analysis of a subset of our data to address whether our scaffolding is supporting students in the acquisition and transfer of these inquiry skills. We also describe an additional study, which used Bayesian Knowledge Tracing (Corbett and Anderson. User Model User-Adapt Interact 4(4):253–278, 1995), a computational approach allowing for the analysis of the fine-grained sub-skills underlying our practices of data interpretation and warranting claims.