Permanent but Unequal: A Multilevel Quasi-Experimental Analysis of Online Learning Expansion and Doctoral Completion Trajectories Across U.S. Graduate Education, 2014–2022

The COVID-19 disruption forced the most comprehensive shift to online delivery in U.S. graduate education history. This study examines whether that change represents a permanent restructuring or a transient adjustment, and how it relates to differential doctoral completion outcomes across fields with different research methodologies. We apply a multilevel quasi-experimental design to two federal census-level datasets: the Integrated Postsecondary Education Data System (IPEDS; 18,826 institution-year observations, 2014–2022) and the Survey of Earned Doctorates (SED; 34 subfields, 2012–2022). Each institution serves as its own control in a fixed-effects panel model (institution-level ICC = .702), supplemented by interrupted time-series and sector-disaggregated analysis. The online enrollment surge was not transient: by 2022, online-engaged enrollment remained about 6% points above pre-pandemic projections, with hybrid delivery accounting for the larger share. Within institutions, the pandemic produced a sharp increase of nearly 13% points, roughly half of which persisted into 2022. Doctoral completion trajectories diverged: co-presence-dependent fields (e.g. history, foreign languages, anthropology) experienced sustained declines, while computationally oriented fields (e.g. computer science, engineering) grew. A trend-adjusted model attributes a 20.6% post-pandemic completion advantage to computationally oriented fields beyond preexisting divergence. The post-pandemic environment is a sustained, stratified system rather than a return to baseline. The design documents field-level trajectories but cannot assign them to individual-level modality exposure. Findings inform online doctoral program design, hybrid modality investment, and accreditation monitoring.