EAGER: Addressing the Community College Credit Loss Problem within Four-Year Computer Science Programs

About This Grant

The credit-loss problem is a persistent barrier for students transferring from community colleges (CCs) to four-year universities in STEM fields. Credits often do not transfer cleanly or apply toward major requirements, particularly in STEM, where rigid course sequences and prerequisite structures are common. As a result, students must repeat coursework, delay graduation, and face increased costs—all of which contribute to high attrition rates and student debt. These challenges are compounded by inconsistent articulation agreements, under-resourced advising, and institutional misalignment. Despite efforts to address this issue – such as statewide course-numbering systems and advising initiatives –substantial credit loss remains. The project will conduct a three-university pilot of a competency-based approach. The driving hypothesis is that transfer students often, but unnecessarily, lose all credits associated with a class because they are missing some but not all of the content in the equivalent class at the four-year institution. In this pilot transfer students will complete a placement assessment to identify the appropriate entry point in the Computer Science major at the four-year university. Students who demonstrate partial mastery of a required class will complete a one-credit supplemental course, while those with significant gaps will repeat the course — regardless of course numbering or existing articulation agreements. The goal is to help transfer students identify the appropriate starting point in the computing degree and to do this in a scalable and easy-to-update way. Although this pilot focuses on transfer in computing majors, the credit-loss problem spans all of STEM; thus a successful pilot will open the opportunity to use this approach in other disciplines. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.