“Online Courses and High School Student Experiences”
Associate Professor of Education Policy
University of California, Davis
Wednesday, May 29th
617 Library Place
This talk explores several facets of online course-taking for high school students. A first set of analyses examines performance outcomes for high school students taking online courses in Florida. These analyses use fixed effects models to estimate differences in contemporaneous and downstream academic outcomes for students who take courses virtually and face-to-face—both for initial attempts and for credit recovery. We find that while contemporaneous outcomes are positive for virtual students in both settings, downstream outcomes vary by attempt type. For first-time course takers, virtual course taking is associated with decreases in the likelihood of taking and passing follow-on courses and in graduation readiness (based on a proxy measure). For credit recovery students, virtual course taking is associated with an increased likelihood of taking and passing follow-on courses and being in line for graduation. A second set of analyses looks descriptively at the extent to which online course offerings extend, rather than replace, the course offerings of brick-and-mortar high schools, and examines the characteristics associated with these different uses of online courses.
Cassandra Hart is an associate professor of education policy at the University of California, Davis. Hart’s research has focused on school choice programs, effects of online education on student outcomes, and effects on students of exposure to demographically similar teachers. Her research has been published in education and economics journals including Education Finance and Policy, Educational Evaluation and Policy Analysis, and American Economic Journal: Applied Economics. Hart received her PhD in Human Development and Social Policy from Northwestern University in 2011.
“Moving From What Works To What Replicates:
A New Framework for Evidence-Based Decision-Making”
Assistant Professor of Research, Statistics, and Evaluation
University of Virginia
Monday, May 20th
Library Place 617
Given the central role of replication in the accumulation of scientific knowledge, researchers try to replicate seemingly well-established findings. Mounting evidence, however, suggests that results from many studies are fragile and hard to replicate. The so-called “replication crisis” has important implications for evidence-based decision-making in the health and social sciences. At the same time, there is intense debate about what constitutes a successful replication and why certain types of replication rates are so low. A crucial set of questions for evidence-based decision-making involve questions about external validity and replicability. We need to understand the contexts and conditions under which interventions produce similar outcomes. To address these challenges, I introduce a novel framework that provides a clear definition of replication, and highlights the conditions under which results are likely to replicate (Wong & Steiner, 2018). I present replication as a prospective research design. This makes it possible to define key assumptions for the direct replication of results, and to show how different replication designs can be derived and used to evaluate treatment effect heterogeneity. I argue that replication designs are feasible, desirable, and relevant in real world settings that are important for evidence-based decision-making.
Vivian C. Wong is a research methodologist in the field of Education. Currently, Dr. Wong is an Assistant Professor in Research, Statistics, and Evaluation in the Curry School of Education at the University of Virginia. Her research focuses on evaluating interventions in early childhood and K-12 systems. As a methodologist, her expertise is in improving the design, implementation and analysis of randomized experiments, regression-discontinuity, interrupted time series, and matching designs in field settings. She is currently examining the design, implementation, and analysis of replication studies in field settings, as well as developing innovative methods for evaluating No Child Left Behind. Dr. Wong participated in the Institute for Education Sciences (IES) Predoctoral Training Program at Northwestern University, and received the Outstanding IES Predoctoral Fellow Award in 2010 for her dissertation work on “Addressing Theoretical and Practical Challenges in the Regression-Discontinuity Design.” She is a Principal Member of IES’s Statistics and Methodology review panel.