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Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment

机译:从构造的反应中预测阅读理解:解释性检索作为隐身评估

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Open-ended constructed responses promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes. College students (N = 75) produced self-explanations during reading and explanatory retrievals after reading. The Constructed Response Assessment Tool (CRAT) was used to analyze these responses across multiple dimensions of language and relate these textual features to comprehension performance. Results indicate that the linguistic features of post-reading explanatory retrievals were more predictive of comprehension outcomes than self-explanations. Further, these models relied on different indices to predict performance.
机译:不限成员名额的构建式回应促进了课程材料的更深层次处理。此外,对这些解释的评估可以提供有关学生认知的重要信息。这项研究检查了学生在学习过程中不同点产生的构造反应如何与他们后来的理解结果相关。大学生(N = 75)在阅读过程中产生了自我解释,并在阅读后进行了解释性检索。建构回应评估工具(CRAT)用于分析语言各个维度的回应,并将这些文字特征与理解能力联系起来。结果表明,阅读后解释性检索的语言特征比自我解释更能预测理解结果。此外,这些模型依赖于不同的指标来预测性能。

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