Strong Start To Finish

Use data effectively.

Every student is supported in staying on track to a postsecondary credential through the institution’s effective use of early momentum metrics and mechanisms to generate, share, and act on finely disaggregated student progression data.

Effective institutions use disaggregated data effectively to monitor student progress, assess the impact of interventions, and determine the professional development needs of faculty and staff. Early momentum metrics include credit momentum (number of credits completed in the first semester and year), gateway course momentum (completion of college-level math and English in the first year), and persistent momentum (fall to spring persistence in the first year). When institutions focus exclusively on data associated with course success as a short-term progress indicator, rather than on broader momentum data, they may be incentivized to restrict rather than expand equitable access to gateway courses.

The use of early momentum metrics requires institutions to situate developmental education reform efforts in the context of a more comprehensive student success strategy. For effective use in equity-minded decision-making, early momentum data should be disaggregated by race and ethnicity, socioeconomic status, high school GPA bands, age, disability status, and/or other populations related to institutional context and mission. In their strategic plans, institutions and systems should set goals for closing the gaps in early momentum metrics as determined by a broader student success strategy. These metrics must be widely communicated and regularly examined.

Providing the proper infrastructure for data collection and use is a necessary foundation for employing data to improve student support, but it is just the beginning. Institutional researchers must also effectively translate the data for faculty, staff, and administrators, and leaders at multiple levels must create the conditions for widespread engagement with the data in the context of collaborative sense-making and action-planning.

Beyond using data to monitor student progress and gauge the effectiveness of interventions, institutions must also regularly deploy resources to cultivate a culture of continuous improvement anchored in the recognition that student needs will shift over time as student demographics change and the world of work continues to evolve. Institutions must commit themselves to becoming learning organizations capable of refining their strategies and approaches in order to achieve significant, equitable, and lasting improvements over time. Particularly effective institutions are using student progression data in real time to identify and provide academic and non-academic supports to students as they are needed. This requires robust cross-functional relationships between institutional research, instructional leadership, and student services.

Next Principle

Sources

Belfield, C.R., Jenkins, D., and Fink, J. (2019). “Early Momentum Metrics: Leading Indicators for Community College Improvement.” CCRC Lessons-From-Research Guide. New York, NY: Columbia University, Teachers College, Community College Research Center.

Fletcher, J. and Karp, M. (2015). “Using Technology to Reform Advising: Insights from Colleges.” CCRC Lessons-From-Research Guide. New York, NY: Columbia University, Teachers College, Community College Research Center.

Yeado, J., Haycock, K., Johnstone, R., and Chaplot, P. (2014). “Learning from High-Performing and Fast-Gaining Institutions.” Washington, DC: The Education Trust.

Implementation Guides

Arizona State University. Pathway Tracker.

Georgia State University. GPS Advising.

University of Georgia. DegreeWorks.