SDP and user-contributed analyses are housed in repositories on Github. Each topic-based repository includes web guides with code and supports in Stata or R. The Stata and R guides below are based on the Strategic Data Project Toolkit for Effective Data Use, modified to work with OpenSDP synthetic data. The synthetic data for the College-Going Pathways guides is generated by the OpenSDP simulation engine, while some of the Human Capital Analysis guides use a synthetic dataset developed using the synthpop. The guides and code will also work with college-going or human capital analysis files prepared to the SDP Toolkit data specification.

Newest Analysis

Beating the Odds

School leaders often want to identify promising practices that distinguish high-performing schools from their counterparts and facilitate the transfer of some of these practices to struggling schools. A BTO analysis is one approach school leaders can take to identify schools that perform better or worse than expected, given the unique student populations they serve. In general, BTO analyses predict school performance based on the demographic make up of schools’ student populations and then compare these predictions with actual school performance.

Similar Schools

Identify schools that are similar to each other in terms of student enrollment, faculty and staff characteristics, programs, spending and funding, and other school indicators that are publicly available on state and district report cards. Using data from the Kentucky school report card, this guide shows how unsupervised machine learning methods can be applied to publicly available data to gain insights into schools and districts across a state.

Achievement Gaps

Explore gaps in student achievement, specifically along lines of race, socioeconomic status, gender, English language learner status, special education status, and migrancy status, among others.

College-Going Pathways

Answer questions about students’ on-track status in ninth grade, high school graduation, college enrollment, and college persistence. Identify patterns and trends along the education pipeline to and through college for students as a group and as subgroups.

Human Capital Analysis

Use data to examine teacher workforce patterns and generate data visualizations illuminating the different stages of the human capital pipeline: recruitment, placement, development, evaluation, and retention.