Data Reporting: Balancing Accreditation Requirements with Student Privacy

Session Abstract: Under regional accreditation standards (e.g., WASC CFR 4.2 or NWCCU 1.D.2), institutions must collect, analyze, and act on disaggregated student outcomes data, including retention and graduation rates, that are broken out by socioeconomic and demographic attributes. Instead of sharing student-level identifiers with third parties to collect socio-demographic and economic student background data, this presentation shows “hands-on” how to use a broad range of public geospatial data (over 200 indicators) as proxy measures to obviate the risk of breaching student privacy through data-sharing with outside entities. Student-level inference estimation is based on triangulation of a vast range of socioeconomic and demographic data at the lowest geospatial level (census block/tract). To capture student diversity, geospatial data are intersected interactively online with student data to measure the relationship descriptively, through correlation analysis, and with causal inference estimation

Keywords: Data Privacy, Student Success, Accreditation, Dashboards, Program Review, Socioeconomics