Data Science for Educators
A beginner-friendly knowledge bundle covering five education research questions, their methods, and the data behind them — built on NAEP 2022–2024 data.
Data Science for Educators
A beginner-friendly walkthrough of five real research questions in education, drawn from the 2022–2024 NAEP (National Assessment of Educational Progress) data. Each question shows what you would investigate, how you would design the analysis, what data you would need, and — most importantly — why each step makes sense.
If you are an educator curious about data science but new to the terminology, this is written for you.
Where the data lives
All questions can be answered using the NAEP Data Service API at nationsreportcard.gov — a free, public source of U.S. student assessment data — plus a handful of external sources noted in each section.
Contents
| # | Question | Classification |
|---|---|---|
| 1 | Math vs. reading recovery divergence | Comparative → Causal |
| 2 | Hispanic decline and EL mediation | Causal (mediation) |
| 3 | Digital assessment mode effects | Causal (instrumentation) |
| 4 | Charter penetration and NAEP scores | Comparative → Predictive |
| 5 | IEP gap and state achievement | Comparative |