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

Autor/inn/en	Mononen, Riikka; Niemivirta, Markku; Korhonen, Johan
Titel	Predicting Mathematical Learning Difficulties Status: The Role of Domain-Specific and Domain-General Skills
Quelle	In: International Electronic Journal of Elementary Education, 14 (2022) 3, S.335-352 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Mononen, Riikka) ORCID (Niemivirta, Markku) ORCID (Korhonen, Johan)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1307-9298
Schlagwörter	Mathematics Skills; Grade 1; Grade 3; Learning Problems; Prediction; Foreign Countries; Numeracy; Thinking Skills; Language Skills; Arithmetic; Nonverbal Ability; Computation; Mathematical Logic; Short Term Memory; Executive Function; Naming; Low Achievement; Norway + Suchen Sie Ihr Suchwort? Mathmatics achievement; Mathematics ability; Mathematische Kompetenz; School year 01; 1. Schuljahr; Schuljahr 01; School year 03; 3. Schuljahr; Schuljahr 03; Lernproblem; Vorhersage; Ausland; Rechenkompetenz; Denkfähigkeit; Language skill; Sprachkompetenz; Addition; Arithmetik; Arithmetikunterricht; Rechnen; Mathematical logics; Mathematische Logik; Kurzzeitgedächtnis; Unterdurchschnittliche Leistung; Norwegen
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 [less than or equal to] 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 [less than or equal to] 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. (As Provided).
Anmerkungen	International Electronic Journal of Elementary Education. T&K Akademic Rosendalsvein 45, Oslo 1166, Norway. e-mail: iejee@iejee.com; Web site: https://www.iejee.com/index.php/IEJEE/index
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01