University of Oulu

Mononen, Riikka, et al. “Predicting Mathematical Learning Difficulties Status: The Role of Domain-Specific and Domain-General Skills.” Lnternational Electronic Journal of Elementary Education, Jan. 2022, p. 3. DOI.org (Crossref), https://doi.org/10.26822/iejee.2022.248

Predicting mathematical learning difficulties status : the role of domain-specific and domain-general skills

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Author: Mononen, Riikka1,2; Niemivirta, Markku3; Korhonen, Johan4
Organizations: 1Teachers, Teaching and Educational Communities, University of Oulu, Finland
2Department of Special Needs Education, University of Oslo, Norway
3School of Applied Educational Science and Teacher Education, University of Eastern Finland, Finland
4Faculty of Education and Welfare Studies, Åbo Akademi University, Vaasa, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022092660186
Language: English
Published: KURA Education & Publishing, 2022
Publish Date: 2022-09-26
Description:

Abstract

This study investigated which domain-specific and domain-general skills measured at grade 1 predict mathematical learning difficulties (MLD) status at grade 3. We used different cut-off criteria and measures of mathematics performance for defining the MLD status. Norwegian children’s (N = 206) numeracy, cognitive, and language skills were measured at grade 1 and arithmetic fluency and curriculum-based mathematics (CBM) at grade 3. Logistic regression analyses showed that symbolic numerical magnitude processing, verbal counting, and rapid automatized naming predicted MLD25 status (performance ≤ 25th percentile) based on arithmetic fluency, whereas verbal counting skills and nonverbal reasoning predicted the status based on CBM. The same predictors were found for MLD10 status (performance ≤ 10th percentile), and in addition, rapid automatized naming also predicted the status based on CBM. Only symbolic numerical magnitude processing and verbal counting predicted LOW status (performance between 11–25th percentile) based on arithmetic fluency, whereas nonverbal reasoning and working memory predicted LOW status based on CBM. Different cut-off scores and mathematics measures used for the definition of MLD status are important to acknowledge, as these seem to lead to relatively significant variation in which students are identified as having MLD and which factors contribute to the MLD status.

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Series: International electronic journal of elementary education
ISSN: 1307-9298
ISSN-E: 1307-9298
ISSN-L: 1307-9298
Volume: 14
Issue: 3
Pages: 335 - 352
DOI: 10.26822/iejee.2022.248
OADOI: https://oadoi.org/10.26822/iejee.2022.248
Type of Publication: A1 Journal article – refereed
Field of Science: 516 Educational sciences
Subjects:
Funding: This work was supported by the Norwegian Research Council [Grant number: 283396], for the first author. We thank all the participating children, their teachers and parents, as well as the research assistants involved in the data collections.
Copyright information: © 2022 Published by KURA Education & Publishing. This is an open access article under the CC BY-NC-ND license.
  https://creativecommons.org/licenses/by-nc-nd/4.0/