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A photograph of Professor Alexander in a blue shirt with a grey background.
Faculty
Faculty

Nathan Alexander

Assistant Professor

nathan.alexander@howard.edu
https://professornaite.github.io/

Department/Office

  • Curriculum and Instruction

School/College

  • School of Education
  • Graduate School

Additional Positions

  • Assistant Graduate Director
    Center for Applied Data Science and Analytics

Biography

Nathan Alexander, PhD, is an assistant professor of curriculum and instruction in the Howard University School of Education and the Center for Applied Data Science and Analytics (CADSA). His research focuses on the history and development of quantitative and mathematical literacy, and he examines the role of context in probability theory, statistical data analysis, and mathematical education. He is the founder and faculty director of the Quantitative Histories Workshop, a computational curriculum collective and community-centered teaching and learning lab.

Education & Expertise

Education

PhD, Mathematics and Education
Columbia University
2015

MAT, Mathematics
New York University
2008

BA, Mathematics and Sociology
University of North Carolina at Chapel Hill
2007

Expertise

Probability, statistics and data science education

Quantitative historical studies

Undergraduate and k-12 mathematics education

Academics

Academics

EDUC 315: Principles of Teaching Mathematics & Science II

EDUC 480: International Internship and Special Topics Seminar

DATA 202: Statistically Measuring and Modeling Social Justice

DATA 410: Independent Study

DATA 802: Data Science Practicum/Internship

Research

Research

Funding

National Endowment for the Humanities. The Haynes Project: Exhibiting the Historical Significance of the Philosophical Views of American Mathematicians. Co-Principal Investigator (Co-PI) with John Stigall (PI). Lifelong Learners Division, 2026-2029. (Funded, $148,944)

Open Research Community Accelerator. Expansion of an Open Source Community for Faculty and Students at HBCUs. Principal Investigator (PI). Catalytic Awards Program, 2025-2026. (Funded, $15,000)

Public Interest Technology Network. Integrating Community Knowledge and Equity into Integrated Administrative Data Systems for Research and Education in Data Science for Social Impact. Co-Investigator/Subaward with Francisca Garcia-Cobian (PI) and Patty Dare (Co-PI). University Network, 2025-2026. (Funded, $60,000)

Alfred P. Sloan Foundation. Open Source Workshops and Lesson Development for Faculty and Students at Historically Black Colleges and Universities. Principal Investigator (PI) with Hye Ryeon Jang (Co-PI) and Kari Jordan (Co-PI). Open Source Software Development, 2023-2026. (Funded, $249,705)

New Ventures Fund. Development of Community-based Experiential Learning Programs in Data Science. Principal Investigator (PI), Data.org Capacity Accelerator Network. 2022-2023. (Funded, $115,000)

Group Information

Quantitative Histories Workshop

Accomplishments

Accomplishments

Featured News

Featured News

Creating an ‘all comers’ research group in quantitative history. Nature.

Publications and Presentations

Publications and Presentations

Alexander, N. N., Turner, B. O., Wallace, D., Kyles, C., Leatherwood, D., & Payne, R. (2025). From Theory to Practice: Exploring Critical Orientations in Professional Learning Programs in Mathematics Education. In Zbiek, R. M., Yao, X., McCloskey, A., & Arbaugh, F. (Eds.), Proceedings of the forty-seventh annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, pp. 242–251.

Alexander, N. N., Thompson, B., Piercey, V., & Diaz Eaton, C. (2025). Toward a praxis of critical inquiry in undergraduate mathematics classrooms. Inquiry: Critical Thinking Across the Disciplines, 34(2), 448-479.

Fletcher, N., Alexander, N. N., Kang, B., Kebreab, L., Marshall, B., Martinez, J., Sundrani, A., & Velasco, R. (2025). Programs and Opportunities for Early Career Mathematics Education Scholars. Journal of Mathematics Education at Teachers College, 16(1), 46–57.

Alexander, N. N., Appling, T., Banuelos, M., Bello, G., Brown, A., Century, J., Connor, K., Ji, H., Levy, R., Mitchell, P., Mongeau, D., Mysliwiec, M., Niu, J., Paykin, S., Quarkume, A., Schiffman, J., Skinner, L., Uminsky, D. & Zhong, P. (2024). Data Science for Social Impact in Higher Education: First Steps. Data.org Playbook. Available online.

Jones, Q., Vindas Meléndez, A. R., Mendible, A., Aminian, M., Brooks, H. Z., Alexander, N. N., Diaz Eaton, C., Chodrow, P. (2023). Data science and social justice in the mathematics community. Notices of the American Mathematical Society, 70(9), 1479-1489.

Alexander, N. N. (2023). Real Analysis. In EBSCO Research Starters. Ipswich, MA: EBSCO.

Voigt, M., Hagman, J. E., Gehrtz, J., Ratliff, B., Alexander, N. N., & Levy, R. (Eds.) (2023). Justice through the lens of calculus: Framing new possibilities for diversity, equity, and inclusion. Mathematical Association of America (MAA) Press.

Alexander, N. N. (2022). A Legacy of Literacy: Mathematics Teachers and the Quests for Racial Justice. In D. C. Hucks, Y. S. Ruiz, V. Showunmi, S. C. Carothers, & C. W. Lewis (Eds.), Purposeful Teaching and Learning in Diverse Contexts: Implications for Access, Equity and Achievement (pp. 3-23). Charlotte: IAP.

Alexander, N. N. (2022). Fermat’s Last Theorem. In EBSCO Research Starters. Ipswich, MA: EBSCO.