Modeling Student Motivation and Students’ Ability Estimates From a Large-Scale Assessment of Mathematics

Carlos Zerpa, Krystal Hachey, Christina van Barneveld and Marielle Simon

SAGE Open, 2011, vol. 1, issue 2, 2158244011421803

Abstract: When 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.

Keywords: achievement; educational testing; large-scale assessments; motivation; self-report data (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:1:y:2011:i:2:p:2158244011421803

DOI: 10.1177/2158244011421803

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