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dc.contributor.authorZerpa, Carlos
dc.contributor.authorHachey, Krystal
dc.contributor.authorBarneveld, Christina van
dc.contributor.authorSimon, Marielle
dc.date.accessioned2013-10-17T20:09:39Z
dc.date.available2013-10-17T20:09:39Z
dc.date.issued2011
dc.identifier.urihttps://hdl.handle.net/20.500.12799/2016
dc.descriptionEn: SAGE Open, pp. 1-9es_ES
dc.description.abstractWhen large-scale assessments (LSA) do not hold personal stakes for students, students may not put forth their best effort. Low-effort examinee behaviors (e.g., guessing, omitting items) result in an underestimate of examinee abilities, which is a concern when using results of LSA to inform educational policy and planning. The purpose of this study was to explore the relationship between examinee motivation as defined by expectancy-value theory, student effort, and examinee mathematics abilities. A principal components analysis was used to examine the data from Grade 9 students (n = 43,562) who responded to a self-report questionnaire on their attitudes and practices related to mathematics. The results suggested a two-component model where the components were interpreted as task-values in mathematics and student effort. Next, a hierarchical linear model was implemented to examine the relationship between examinee component scores and their estimated ability on a LSA. The results of this study provide evidence that motivation, as defined by the expectancy-value theory and student effort, partially explains student ability estimates and may have implications in the information that get transferred to testing organizations, school boards, and teachers while assessing students’ Grade 9 mathematics learning.es_ES
dc.language.isoenes_ES
dc.publisherSAGEes_ES
dc.subjectEvaluación de la educaciónes_ES
dc.subjectEnseñanza de las matemáticases_ES
dc.subjectAnálisis de datoses_ES
dc.subjectEvaluación del rendimiento escolares_ES
dc.titleModeling Student Motivation and Students’ Ability Estimates From a Large-Scale Assessment of Mathematicses_ES
dc.typePaperes_ES


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