Learning and Leveraging VLDS: Connecting Educational Research to Practice

Author: Dr. David B. Knight, Department of Engineering Education Virginia Tech
October 27, 2015

Expanding access, reducing costs, and enhancing quality are among the greatest challenges facing education in the United States to enable opportunities for all citizens to help their communities toward a prosperous future. To address those challenges, the Obama administration emphasizes the need for the entire educational system to become more “data-driven.”[1] As technological tools and data resources have continued to develop, the educational enterprise has access to larger quantities and kinds of data than ever before, which will be “key to transforming student retention, graduation, and success.”  Leveraging such diverse, existing data can provide new “actionable intelligence” to enhance the educational conditions related to student success.[2]  The Virginia Longitudinal Data System—or VLDS—is one example of such a resource that brings together data from disparate sources in a way that can produce new insights on how to help make education in Virginia more effective, efficient, and inclusive.  But analyzing such data from a research perspective stops short of “data-driven” decision-making—engaging users, policymakers, and practitioners is necessary so that systems like the VLDS can realize their full potential.


Prior to my arrival at Virginia Tech, my colleague David Hondula and I at Pavilion Research, a non-profit research organization, were awarded a small grant from the Association for Institutional Research to investigate how the VLDS might be leveraged to help inform the college decision-making and preparedness process. Our project took up the challenge of identifying ways to make more information about postsecondary education available by exploring how college readiness data can be brought directly to guidance counselors, students, and families in an easy-to-use manner to help them make important and difficult decisions. Our approach demonstrates how we might consider using existing data to connect research and practice—guidance counselors, college advisors, and members of the Virginia Department of Education were the individuals who informed our quantitative research process, not vice versa.


Let’s take an example from our project to illustrate how a resource like the VLDS can help alleviate current pain points in the system. We collected open-ended survey data from 48 guidance counselors from across the Commonwealth of Virginia located at 43 unique schools. Nearly half of the respondents said that students do not realize that the total performance (i.e., academic achievement in all four years) in high school impacts available options. Students and their parents tend to understand how GPA and SAT scores were viewed by different colleges, but they didn’t seem to have as strong of a grasp at how high school course taking patterns related to options for college.  Although aggregate admissions data from universities can be helpful, these often times do not include course taking information.  Furthermore, guidance counselors believe localized data (e.g., at the school or district level) would be much more insightful as they assist students in the college planning process. 


With these findings in mind we explored how leveraging the VLDS might be able to shed some insight on this issue and investigated how course taking during the junior and senior years of high school relates to college enrollments. The association between high school course taking and postsecondary institution enrollment can be quantified using VLDS and shared with guidance counselors, students, and parents to provide outcomes-based benchmarks for curricular planning.  Not surprisingly, examining combinations and sequences of course taking can provide a more holistic picture of the pathway through high school to college.  For example, at Virginia’s three Most or More Selective Universities, there were 3–27 times as many students who enrolled in one of several “advanced” high school course combinations we identified compared to a combination of courses that was more representative of standard senior year courses.  VLDS could enable analyses to support guidance counselors in real-time, through benchmarking or longitudinal data about their former students’ successes in college and employment, pervasive majors at different colleges, academic preparation required for each college, and the high school curricular rigor that is associated with different colleges.


At the annual VLDS Insights meeting, I asked the audience to think about their own children and how they tend to plan their class schedules. Most responded that they sit down with a check sheet that lists out different course options and various pre-requisites.  Some think about outcomes like the Advanced Studies Diploma track, which is certainly a start in the right direction toward outcomes-based decision-making.  But what if we presented students and parents with something like the following flow chart, which we produced using VLDS?  Students and parents could very quickly see where students who faced similar course taking decisions ended up going to college.  It links the present-day decision to a future outcome, and such an analysis could be easily done at the school-, district-, or state-level for all potential postsecondary choices using the VLDS.



The VLDS offers a wonderful opportunity to use data to connect the research to practice divide. Ultimately, engaged partnerships between researchers, stakeholders, policymakers, and practitioners are what will be required to face the big challenges facing education in the United States.  Using real data will help us understand the educational system and help us identify workable solutions to existing problems so that education in Virginia becomes more effective, efficient, and inclusive. 


Note: To view the full project report from Pavilion Research, please visit the following website:


Author: David B. Knight, dbknight@vt.edu

Department of Engineering Education

Virginia Tech


[1] U.S. Department of Education (2015). The President’s fiscal year 2015 budget request for education. http://www.ed.gov/budget15.

[2] Baer, L, & Campbell, J. (2012). From metrics to analytics, reporting to action: Analytics’ role in changing the learning environment. In Game changers: Education and information technologies. D.G. Oblinger (Ed.). EDUCAUSE.

Tags: VLDS, Educational Research, localized data, GPA, SAT, Guidance Counselors, curriculum, class schedules, outcomes based decision makers

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