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

SAGE Open

Carlos Zerpa¹ 

关键词: achievement;    educational testing;    large-scale assessments;    motivation;    self-report data;   

DOI  :  10.1177/2158244011421803

学科分类：社会科学、人文和艺术（综合）

来源: Sage Journals

【 摘 要 】

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.

【 授权许可】

CC BY