Degree Name

Doctor of Philosophy (PhD)

Document Type



Feinstein School of Education and Human Development

Department (Manual Entry)

Education Doctoral Program


Since 2001 , No Child Left Behind (N CLB) legislation has mandated that every state test students' educational progress annually, allowing each state to choose among many different instruments (Hoff, 2008). This demand for educational testing of all students has enabled the growth and availability of raw achievement data for subject areas tested and created an opportunity for a wide range of knowledge discovery. Not all states report testing results disaggregated by gender but in 2008, Hyde, Lindberg, Linn, Ellis, and Williams conducted research on data from I 0 states that do. They found the weighted mean achievement scores in mathematics showed no statistical difference between males and females for all tested grades (2 through 11) for those states' data (Hyde, Lindberg, Linn, Ellis, & Williams, 2008). This finding aligns with research showing increasing parity for females in mathematics achievement (National Center for Education Statistics, 2003a).

In the current study, a northeastern state's annual NCLB test results for students in 4th, 6th, and 8th grades, during the 2010-2011 school year, are the source of data. An examination of mean scores for this population shows no gender differences in mathematics achievement. Reporting achievement results solely based on the statistical mean of test scores potentially overlooks information that other examinations of the distribution may provide especially when the area of interest is high achieving students (Koerselman, 201 0). The purpose of this study is to examine extremes in high mathematics achievement testing data to determine whether inequitable patterns exist along gendered lines. The following research questions are be addressed in this research:

• Are there meaningful differences between males and females in mathematics achievement in grades 4, 6, and 8 at the upper extremes of the distribution?

• How do race, socioeconomic status, and limited proficiency in English intersect with gender at the upper extremes of achievement?

Gender issues surrounding equity in mathematics achievement have important implications for both educational systems and society. Although many elements influence the underrepresentation of women in the STEM pipeline, achievement in mathematics is positively linked to entrance into the fields of science, technology, engineering and mathematics (Steen, 1987; Tai, Liu, Maltese, & Fan, 2006; Miller & Kimmel, 201 0). By delving deeply into one state's mathematical achievement data, early evidence of concealed but influential disparities in male and female performance in mathematics may be described. This study's goal is to add quantitatively to the conversation about gender and mathematics achievement. By using regression methods to unravel the extremes of achievement data by gender, it is hoped that potentially overlooked inequities will be illuminated, and in time, addressed in curricula and instructional reforms.

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