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Article: Identifying children with persistent low math achievement: The role of number-magnitude mapping and symbolic numerical processing

TitleIdentifying children with persistent low math achievement: The role of number-magnitude mapping and symbolic numerical processing
Authors
KeywordsDyscalculia
Mathematics learning disabilities
Numerical magnitude
Longitudinal predictors
Issue Date2019
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/learninstruc
Citation
Learning and Instruction, 2019, v. 60, p. 29-40 How to Cite?
AbstractAlthough an increasing number of research studies have investigated the cognitive deficits related to difficulties in learning mathematics, little is known about whether these cognitive deficits longitudinally predict low mathematics achievement over time. The current 6-year longitudinal study was conducted to address this issue. A sample of 101 students was tested on various numerical and cognitive competencies when they were in kindergarten and in Grade 1. They were then followed until they were in Grade 6, and their mathematics achievement was assessed bi-annually. A group of persistent low mathematics achievers (PLA) who scored consistently below the 25th percentile was identified. This group of PLA showed difficulties in most of the numerical tasks as early as kindergarten. More importantly, three of the early predictors correctly identified 79% of the PLAs. The current findings provide valuable information concerning the core cognitive deficits underlying difficulties in learning mathematics as well as an important tool for educators for identifying children who are at risk of persistent math learning difficulties in the elementary school years.
Persistent Identifierhttp://hdl.handle.net/10722/271191
ISSN
2021 Impact Factor: 6.636
2020 SCImago Journal Rankings: 2.320
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWong, TTY-
dc.contributor.authorChan, WWL-
dc.date.accessioned2019-06-24T01:05:08Z-
dc.date.available2019-06-24T01:05:08Z-
dc.date.issued2019-
dc.identifier.citationLearning and Instruction, 2019, v. 60, p. 29-40-
dc.identifier.issn0959-4752-
dc.identifier.urihttp://hdl.handle.net/10722/271191-
dc.description.abstractAlthough an increasing number of research studies have investigated the cognitive deficits related to difficulties in learning mathematics, little is known about whether these cognitive deficits longitudinally predict low mathematics achievement over time. The current 6-year longitudinal study was conducted to address this issue. A sample of 101 students was tested on various numerical and cognitive competencies when they were in kindergarten and in Grade 1. They were then followed until they were in Grade 6, and their mathematics achievement was assessed bi-annually. A group of persistent low mathematics achievers (PLA) who scored consistently below the 25th percentile was identified. This group of PLA showed difficulties in most of the numerical tasks as early as kindergarten. More importantly, three of the early predictors correctly identified 79% of the PLAs. The current findings provide valuable information concerning the core cognitive deficits underlying difficulties in learning mathematics as well as an important tool for educators for identifying children who are at risk of persistent math learning difficulties in the elementary school years.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/learninstruc-
dc.relation.ispartofLearning and Instruction-
dc.subjectDyscalculia-
dc.subjectMathematics learning disabilities-
dc.subjectNumerical magnitude-
dc.subjectLongitudinal predictors-
dc.titleIdentifying children with persistent low math achievement: The role of number-magnitude mapping and symbolic numerical processing-
dc.typeArticle-
dc.identifier.emailWong, TTY: terrytyw@hku.hk-
dc.identifier.emailChan, WWL: wlwinnie@hku.hk-
dc.identifier.authorityWong, TTY=rp02453-
dc.identifier.authorityChan, WWL=rp01969-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.learninstruc.2018.11.006-
dc.identifier.scopuseid_2-s2.0-85057346210-
dc.identifier.hkuros298121-
dc.identifier.volume60-
dc.identifier.spage29-
dc.identifier.epage40-
dc.identifier.isiWOS:000461536000003-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0959-4752-

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