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

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment
Creator	Allen, Laura Hinze, Scott Mccarthy, Kathryn
Source	PMC
abstract	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.
has issue date	2020-06-10(xsd:dateTime)
bibo:doi	10.1007/978-3-030-52240-7_36
has license	no-cc
sha1sum (hex)	b65ab6adadca8149a4e41024782dfb6c97ce8c5d
schema:url	https://doi.org/10.1007/978-3-030-52240-7_36
resource representing a document's title	Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment
has PubMed Central identifier	PMC7334719
schema:publication	Artificial Intelligence in Education
resource representing a document's body	covid:b65ab6adadca8149a4e41024782dfb6c97ce8c5d#body_text
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