How R&D Infrastructure for Postsecondary Education Could Unlock New Advances

Despite decades of recognition that postsecondary education lacks a robust empirical research base, systemic barriers—including faculty autonomy, non-standardized assessments, and siloed student data—continue to impede large-scale instructional innovation. While the proliferation of digital learning platforms offers unprecedented data streams, proprietary control and privacy concerns have historically stymied their use for the public good. This paper articulates a vision for a modern postsecondary R&D infrastructure designed to bridge these gaps. By examining initiatives within the SEERNet research network—such as Arizona State University’s Learning@Scale data warehouse and the Terracotta and OpenStax Kinetic experimental tools—the author demonstrates how integrated, multidimensional datasets and open-access research instruments can lower barriers to rigorous experimentation in authentic learning environments. The paper further explores the role of Privacy Enhancing Technologies (PETs) and standardized data taxonomies in balancing student privacy with the need for generalizable insights. Ultimately, the author calls for an ethos of openness and public investment in research infrastructure to prevent the privatization of educational insights and to foster a culture of continuous, evidence-based improvement in higher education.