Using Visual Models to Identify Student Pathways to College
Project Leads Justin Ronca
Lead Mathematical Statistician, Office of Research, Evaluation, and Statistics Elizabeth Vaade
United States Social Security Administration
University of Wisconsin-Madison
Policy Analyst, WISCAPE
University of Wisconsin-Madison
Scholarship from the last decade shows that first-generation students, socioeconomically disadvantaged students, and racial minorities are far less likely to participate in postsecondary education than their continuing generation, socioeconomically advantaged, white counterparts. While the literature provides a great deal of guidance about particular points of intervention that are effective for increasing postsecondary participation among specific student groups, there has been little initiative to coordinate these findings into a national policy framework that enables effective integration of postsecondary access programs.
In this study, researchers Justin Ronca and Beth Stransky Vaade propose using classification and regression tree methodology in conjunction with the NELS:88 database to build a coarse, data-driven policy framework that can then be enhanced by the findings in the academic literature. Using this method, they will establish guidelines for data-collection protocols that isolate and call for the collection of the appropriate data at the appropriate time so as to make clear which types of interventions work best for which types of students, and when. They will also compare this method with parametric models typically used in education data analysis.
Ronca’s and Vaade's ultimate goal is to produce a visual model that will help researchers and practitioners identify the most relevant data for predicting student pathways to college and help institutions interested in promoting student success allocate already scarce resources more efficiently.
Ronca began this study as a WISCAPE project assistant and is now lead mathematical statistician at the United States Social Security Administration. Vaade is currently a WISCAPE policy analyst.
Related Papers and Presentations
- Ronca, J. M., & Stransky, E. N. (April 7, 2009) Using visual models to identify student pathways to college. Brown bag forum presentation for the Wisconsin Center for the Advancement of Postsecondary Education (WISCAPE), Madison, Wis. Download presentation slides.
- Ronca, J.M., & Stransky Vaade, E. N. (November 6, 2009). Nonparametric classification and regression tree models for data-driven policy. Presented at the 34th Annual Conference of the Association for the Study of Higher Education (ASHE), Vancouver, BC. Download paper. Download presentation slides.
- Ronca, J.M. & Vaade, E.S. (June 5, 2012). Using big data: Scalable, visually interpretable methods for institutional research. Presented at the Annual Forum for the Association for Institutional Research (AIR), New Orleans, LA. Download paper. Download presentation slides.
- Ronca, J.M. & Vaade, E.S. (June 4, 2012). Big metadata: A key to efficient big data analysis. Presented at the Annual Forum for the Association for Institutional Research (AIR), New Orleans, LA. Download poster. Download handout.