Individual Differences in Fraction Arithmetic Learning

Autor/inn/en	Braithwaite, David W.; Leib, Elena R.; Siegler, Robert S.; McMullen, Jake
Titel	Individual Differences in Fraction Arithmetic Learning
Quelle	(2019), (54 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Individual Differences; Fractions; Arithmetic; Mathematics Instruction; Student Characteristics; Learning Strategies; Behavior; Bias; Error Patterns; Learning Theories; Simulation; Middle School Students; Mathematics Achievement; Pennsylvania (Pittsburgh); Florida + Suchen Sie Ihr Suchwort? Individueller Unterschied; Bruchrechnung; Addition; Arithmetik; Arithmetikunterricht; Rechnen; Mathematics lessons; Mathematikunterricht; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Fehlertyp; Learning theory; Lerntheorie; Simulation program; Simulationsprogramm; Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz
Abstract	Understanding fractions is critical to mathematical development, yet many children struggle with fractions even after years of instruction. Fraction arithmetic is particularly challenging. The present study employed a computational model of fraction arithmetic learning, FARRA (Fraction Arithmetic Reflects Rules and Associations; Braithwaite, Pyke, and Siegler, 2017), to investigate individual differences in children's fraction arithmetic. FARRA predicted four qualitatively distinct patterns of performance, as well as differences in math achievement among the four patterns. These predictions were confirmed in analyses of two datasets using two methods to classify children's performance--a theory-based method and a data-driven method, Latent Profile Analysis. The findings highlight three dimensions of individual differences that may affect learning in fraction arithmetic, and perhaps other domains as well: effective learning after committing errors, behavioral consistency versus variability, and presence or absence of initial bias. Methodological and educational implications of the findings are discussed. [This paper was published in "Cognitive Psychology" v112 p81-98 Apr 2019.] (As Provided).
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01