Mid-Scale RI-2: SafeInsights: A National Research Infrastructure for Large-Scale Learning Science and Engineering

Research and development (R&D) plays a pivotal role in advancing education, but it remains difficult to conduct large-scale research that yields the strongest results for students and teachers. SafeInsights is a national R&D infrastructure that will support transformational learning research by coordinating research across an initial set of more than a dozen securely connected digital learning platforms (DLPs).

SafeInsights’ privacy model keeps student information secure while allowing researchers to leverage learning data from individuals across multiple DLPs. Such data may span years and different educational institutions, thus enabling researchers to undertake longitudinal studies to investigate, for example, how conceptual understanding develops over time.

With its unique privacy-protecting approach, its large scale, and its emphasis on the inclusion of students, educators, and researchers from diverse and representative backgrounds, SafeInsights will unlock discoveries about learning that lead to predictors of academic success and persistence. Such findings will eventually benefit tens of millions of students across all educational levels in the United States, as more DLPs are connected.

This infrastructure is supported by the U.S. National Science Foundation (NSF) Directorate for STEM Education through the NSF Mid-scale Research Infrastructure-2 Program.

SafeInsights will enable secure data analysis and controlled research studies within authentic learning environments and will leverage learner data from diverse platforms to address scientific inquiries with greater depth and breadth than previously achievable. To support scientists and data stewards in answering important questions about STEM learning, this pioneering scientific cyberinfrastructure will build shared technical and logistical capabilities as well as secure enclave infrastructure deployed inside its collaborating DLPs.

By enabling the combination of individual outcome and performance data from multiple DLPs with additional information (e.g., demographics, past and current course performance, enrollment, and completion pathways) provided by Student Information Systems (SISs), the envisioned research infrastructure enables education researchers to initiate large cross-sectional and longitudinal studies of student learning and achievement across a range of content areas, contexts, and with different demographic groups. Enclaves enable researchers to ask and answer equity-centered learning questions because their analyses can account for socio-demographic variables in large-scale datasets from real-world learning applications.

SafeInsights aims to lower the cost and expand the scale and scope of learning research, increase its agility, accelerate research-to-practice conversion, and democratize access to STEM research opportunities, particularly for scholars from underrepresented groups and minority-serving institutions. As SafeInsights uncovers advanced understandings of human learning, educators will be able to respond through new personalized programs, pedagogies, and policies with the goal of providing each learner with the knowledge, skills, and support they need to succeed in today’s classroom and tomorrow’s workforce.

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.