Date of Award


Degree Type


Degree Name

Doctor of Philosophy in Education



First Advisor

Betty Young


The issue of underrepresentation of women in science, technology, engineering, and mathematics (STEM) careers is especially important to the future of the United States in current times when STEM careers play an increasingly important role in the global economy (Toulmin & Groome, 2007; United States Department of Labor, 2007). The pool of students who enter careers in science, technology, engineering, or mathematics first appear in elementary school and overwhelmingly come from those with high achievement in mathematics (Berryman, 1983; Tai, Liu, Maltese, & Fan, 2006).

This study examined mathematics achievement data for students in grades 4, 6, and 8 in one northeastern state to determine whether inequitable patterns exist along gendered lines. This study used quantile regression methodology to examine mathematics achievement as a function of gender and other student characteristics to reveal if differences exist in the top percentiles of achievement densities for this population. The use of a quantile model enabled the capture of any percentile of the distribution to reveal changes by student characteristics, allowing a more precise picture of achievement in mathematics than could be revealed by means-based methods.

Results of the analyses required a rejection of the null hypothesis there is no difference in mathematics achievement by gender in this population. Further, the point advantages and disadvantages revealed are potentially important for both males and females and may reflect impactful patterns of achievement at both the high and low ends of achievement in mathematics. Additionally, patterns of lower mathematics achievement were revealed for students with limited proficiency in English, lower socioeconomic status, and/or membership in a racial minority group.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.



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