Using Data to Improve Student Success
University of Maryland University College, Montgomery College and Prince George's Community College Share Data to Help Students
Community college transfer students make up 45 percent of all undergraduates in the United States. Now, new data analysis has identified factors that contribute to their success at four-year institutions. The data sharing and analytics were conducted by three Maryland institutions—University of Maryland University College (UMUC), Montgomery College (MC) and Prince George's Community College (PGCC)—and funded by a grant from the Kresge Foundation.
The goal of the project was to build partnerships to better understand and foster student success, which was defined as a function of first-semester GPA, re-enrolling in a subsequent semester and/or re-enrolling within a 12-month period.
Results of the collaboration were presented at the Learner Analytics Summit held July 21–23 at UMUC.
"It's an enormous step for UMUC to go outside the institution and partner with Montgomery College and Prince George's Community College," said Denise Nadasen, associate vice provost for Institutional Research at UMUC, in presenting the results at the summit.
Including data from outside the university was a critical component of the project, Nadasen said. "Data from the community colleges are vitally important in developing models that can predict student success, as well as targeting interventions for students who may be underperforming," she said.
Using learner analytics, the researchers identified a number of positive predictors of success. Those most likely to succeed
- were married
- had successfully completed math and English courses at the community college
- had higher community college GPAs
- had earned more credits at the community college
Using these and other variables, and based on predictive models, UMUC developed a "Success Calculator," a tool that predicts a student's probability of success at UMUC based on data from the community college. The calculator computes a student's probability of earning a GPA of 2.0 or above in their first semester at UMUC—itself a key indicator of later success.
Other models were developed to predict re-enrollment, again factoring in variables like minority status, whether the student received a Federal Pell Grant, marital status, gender, community college GPA, community college cumulative credits and first-term GPA at UMUC.
"These kinds of partnerships are good because we need to share to better understand what students are doing in the full picture," said W. Allan Richman, interim dean of the Office of Planning, Assessment, and Institutional Research at PGCC.
Said Kathleen Wessman, vice president for planning and institutional effectiveness at MC, "We are now starting to work with our school districts to go back deeper in the pipeline."
Based on their findings, all three institutions have now developed new programs, processes and interventions to support student success, particularly for at-risk populations.
"Acting on the data is essential," said Alexandra List, a research associate at UMUC and part of the team that announced the results at the Learner Analytics Summit. "The question becomes how to link the data to interventions."
Together, the three schools provide a huge test bed for doing just that—and one where improvements can yield enormous benefits on a truly global scale.
Prince George's Community College enrolls more than 40,000 diverse students from 103 countries, while Montgomery College also has a diverse population of more than 60,000 students from 75 countries.
UMUC is an open, online university that enrolls more than 90,000 students. The institution's largest population of transfer students comes from Prince George's Community College and Montgomery College.
Today, the world of Big Data is poised to revolutionize higher education, and research is demonstrating that learner analytics can improve student life, academic performance, and college completion. Thanks to the support of the Kresge grant, UMUC, MC and PGCC are several steps closer to developing the cross-institutional analytics that will help them achieve their common goals for student success and completion.
"You have to champion the importance of data," said Richman. "This grant is a good beginning."