Parental Characteristics and the Achievement Gap in Mathematics: Hierarchical Linear Modeling Analysis of Longitudinal Study of American Youth (LSAY)
Keywords:Multilevel Modeling, Achievement Gap, Mathematics, Mots clés, modélisation à niveaux multiples, écart de rendement, mathématiques
One of the most salient problems in education is the achievement gap. The researchers investigated the effects of parental education and parental occupations in science, technology, engineering, mathematics, or medical professions (STEMM) on the achievement gap in mathematics. Because students were nested within schools, two-level Hierarchical Linear Modeling (HLM) was the main analysis. Findings were consistent with another Multilevel Modeling analysis, that is, parental characteristics such as parental education had a positive effect on student achievement (Teodorovic, 2012). Moreover, parental occupations in STEMM had a positive effect on student mathematics achievement.
L’écart de rendement constitue un des problèmes les plus importants en éducation. Les chercheurs ont étudié les effets de l’éducation et de la profession des parents en sciences, technologie, ingénierie, mathématiques et médecine (STIMM) sur l’écart de rendement en mathématiques. Puisque les élèves étaient emboités dans les écoles, l’analyse repose sur un modèle de régression linéaire hiérarchique à deux niveaux. Les résultats correspondent à ceux d’une autre analyse basée sur la modélisation à niveaux multiples qui indique que les caractéristiques des parents telles leur éducation a eu un effet positif sur le rendement des élèves (Teodorovic, 2012). De plus, quand la profession des parents est reliée à STIMM, le rendement en mathématiques de leurs enfants a eu meilleur.
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