Daniel Anderson Ph.D.

Daniel Anderson is a Research Assistant Professor in the College of Education at the University of Oregon. His research lies at the intersection of measurement and large-scale policy, with a specific focus on educational inequities. He is particularly interested in computational approaches to educational and social science problems, including leveraging data from a variety of different sources and building predictive models. Much of his work also focuses on large-scale longitudinal data, including descriptive evaluations of student learning trajectories over time, and evaluations of factors influencing these trajectories.

Daniel is currently leading the design, development, and teaching of a data science specialization for the college of education, with a sequence of three courses being piloted during the 2018-19 academic school year.

Achievement gaps have been a near constant in the American educational system dating back to at least the 1960’s, when large disparities were documented in the well-publicized Coleman report. Yet, surprisingly little research has investigated variability in achievement gaps. In a recent conference paper, we documented considerable between-school variance in achievement gaps. Further, the magnitude of the estimated achievement gaps appeared to be geographically correlated (i.e., schools were generally clustered by the magnitude of the estimated achievement gaps). Daniel’s current work focuses on the factors that relate to this between-school and geographic variation in achievement gap magnitude.