Predicting Mathematical Learning Difficulties Status: The Role of Domain-Specific and Domain-General Skills

Riikka Mononen; Markku Niemivirta; Johan Korhonen

Vol. 14 No. 3 (2022) Special Issue: Typical and Atypical Mathematics Learning: What do We Learn from Recent Studies?

Predicting Mathematical Learning Difficulties Status: The Role of Domain-Specific and Domain-General Skills

Riikka Mononen
Markku Niemivirta
Johan Korhonen

Published March 16, 2022 | Pages: 335-352 | Views: 1627

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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 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 when the status was based on CBM. Different cut-off scores and mathematics measures used for the definition of MLD status are important to acknowledge, as those seem to lead to different early domain-specific and domain-general predictors of MLD.

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 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 when the status was based on CBM. Different cut-off scores and mathematics measures used for the definition of MLD status are important to acknowledge, as those seem to lead to different early domain-specific and domain-general predictors of MLD.

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References

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Keywords

arithmetic, counting, mathematical learning difficulties, nonverbal reasoning, rapid automatized naming

Affiliations

Riikka Mononen

University of Oslo

Markku Niemivirta

University of Eastern Finland and University of Helsinki

Johan Korhonen

Åbo Akademi University

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Mononen, R., Niemivirta, M., & Korhonen, J. (2022). Predicting Mathematical Learning Difficulties Status: The Role of Domain-Specific and Domain-General Skills. International Electronic Journal of Elementary Education, 14(3), 335–352. Retrieved from https://iejee.com/index.php/IEJEE/article/view/1731