About: Improving Students’ Problem-Solving Flexibility in Non-routine Mathematics

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Improving Students’ Problem-Solving Flexibility in Non-routine Mathematics
Creator	Nguyen, Huy Stamper, John Guo, Yuqing Mclaren, Bruce
Source	PMC
abstract	A key issue in mathematics education is supporting students in developing general problem-solving skills that can be applied to novel, non-routine situations. However, typical mathematics instruction in the U.S. too often is dominated by rote learning, without exposing students to the underlying reasoning or alternate ways to solve problems. As a first step in addressing this problem, we present a cognitive task analysis study that investigates how students without a mathematics-related background solve novel non-routine problems. We found that most students were able to identify the underlying pattern that yields the final solution in each problem. Furthermore, they tended to use various forms of visualization in their draft work, but occasionally made computational mistakes. Based on these results, we propose our plan for developing an instructional platform that leverages learning science principles to train students in problem-solving abilities.
has issue date	2020-06-10(xsd:dateTime)
bibo:doi	10.1007/978-3-030-52240-7_74
has license	no-cc
sha1sum (hex)	c3c70370a9236a20cd6460e02c3afe7b73752e17
schema:url	https://doi.org/10.1007/978-3-030-52240-7_74
resource representing a document's title	Improving Students’ Problem-Solving Flexibility in Non-routine Mathematics
has PubMed Central identifier	PMC7334732
schema:publication	Artificial Intelligence in Education
resource representing a document's body	covid:c3c70370a9236a20cd6460e02c3afe7b73752e17#body_text
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