Preliminary research suggests that certain student behaviors can be early signals of success or struggle in college and beyond. For example, early enrollment and completion of required courses might indicate favorable prospects, while late registration and switching majors can foreshadow trouble ahead, particularly for first-generation students, students of color and students from low-income backgrounds.

Some states have developed student databases with information from high school through college and into the labor market. But restricted and siloed access to these databases makes it difficult to coordinate research and generalize early indicators of student success across institutions, systems and regions of the country. Without a common set of early indicators, colleges lack insight to prioritize support services and evaluate the impact of their interventions.


Great Lakes and the Bill & Melinda Gates Foundation are funding a networked community of researchers in four states, led by Dr. Paul Attewell at City University of New York (CUNY) Graduate Center. With a combined $955,000 in grants, researchers from New York, Texas, Virginia and Illinois will use data mining techniques to analyze educational data across multiple systems and connect it to state-level data about employment and income.

Using information available at entry to college plus the student's performance in the first college semester, the researchers will develop models for accurately predicting students' likelihood of retention, degree completion and long-term earning potential. A common set of early indicators of student success will help identify which behaviors might lead some students to fall behind, and the earnings consequences of taking different routes through college.

The research consortium will share knowledge gained from this two-year project with other researchers and practitioners, such as student success and institutional research staff. Providing colleges with a set of common early indicators gives them a tool to prioritize students at greatest risk of dropping out for academic support services, which can help increase retention and completion rates.

Equally valuable to the colleges will be the ability to assess the effectiveness of their interventions early on, without waiting years to see if students drop out or graduate. Examining whether interventions move the needle on early indicators of student success would provide rapid feedback and allow for adjustments to be made while students are still in school.


Contact Senior Program Officer Sue Cui at