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• 1. [Article] The Predictive Relation of a High School Mathematic GPA to High-Stakes Assessment Achievement Scores in Mathematics

  Course grades, which often include non-achievement factors such as effort and behavior and are subject to individual teacher grading philosophies, suffer from issues of unreliability. Yet, course grades ...

  Citation × Citation Citation Abstract Copy Title: The Predictive Relation of a High School Mathematic GPA to High-Stakes Assessment Achievement Scores in Mathematics Author: West, Suzanne Year: 2013 Course grades, which often include non-achievement factors such as effort and behavior and are subject to individual teacher grading philosophies, suffer from issues of unreliability. Yet, course grades continue to be utilized as a primary tool for reporting academic achievement to students and parents and are used by most colleges and universities as an admissions measure. High-stakes assessment results are also used by schools to convey student achievement, and several states now require students to pass an exam to receive a diploma. What is less clear, however, is the relation between these two measures, GPA and high-stakes assessment results. One purpose of this study was to examine the predictive relation of mathematics GPA to student performance on high-stakes assessments. Multiple regression models were used to analyze the predictive relation between mathematics GPA and performance on the ACT and the Oregon Assessment of Knowledge and Skills (OAKS), two high-stakes assessments. In addition, the regression analyses were used to examine the influence of other student-level variables such as talented and gifted status and math courses taken prior to testing on the relation between mathematics GPA and performance on the two high-stakes assessments. In all, 299 high school students from a single grade-level enrolled in one Oregon suburban school district participated in the study. Results indicate that GPA is a significant variable in a high-stakes assessment outcome. Additionally, results of the multiple regression reveal significant student-level effects on assessment outcomes that reduce explained common variance in both the ACT and OAKS models. Implications for practice and suggestions for future research are discussed. Title: The Predictive Relation of a High School Mathematic GPA to High-Stakes Assessment Achievement Scores in Mathematics Author: West, Suzanne Year: 2013 Course grades, which often include non-achievement factors such as effort and behavior and are subject to individual teacher grading philosophies, suffer from issues of unreliability. Yet, course grades continue to be utilized as a primary tool for reporting academic achievement to students and parents and are used by most colleges and universities as an admissions measure. High-stakes assessment results are also used by schools to convey student achievement, and several states now require students to pass an exam to receive a diploma. What is less clear, however, is the relation between these two measures, GPA and high-stakes assessment results. One purpose of this study was to examine the predictive relation of mathematics GPA to student performance on high-stakes assessments. Multiple regression models were used to analyze the predictive relation between mathematics GPA and performance on the ACT and the Oregon Assessment of Knowledge and Skills (OAKS), two high-stakes assessments. In addition, the regression analyses were used to examine the influence of other student-level variables such as talented and gifted status and math courses taken prior to testing on the relation between mathematics GPA and performance on the two high-stakes assessments. In all, 299 high school students from a single grade-level enrolled in one Oregon suburban school district participated in the study. Results indicate that GPA is a significant variable in a high-stakes assessment outcome. Additionally, results of the multiple regression reveal significant student-level effects on assessment outcomes that reduce explained common variance in both the ACT and OAKS models. Implications for practice and suggestions for future research are discussed. Close