Mapping to GAISE II and PPDAC¶
GAISE II (ASA/NCTM) frames statistics and data science education Pre-K–12 around a four-component investigative process (formulate statistical investigative questions · collect/consider data · analyse data · interpret results) and three developmental Levels A, B, C. We use the PPDAC cycle (Problem · Plan · Data · Analysis · Conclusion) as the student-facing skeleton because it adds an explicit Plan step; it maps onto GAISE II as below.
| PPDAC (ours) | GAISE II component |
|---|---|
| Problem | Formulate statistical investigative questions |
| Plan + Data | Collect / consider data |
| Analysis | Analyse data |
| Conclusion | Interpret results |
| Our grade | Target GAISE II level | Emphasis |
|---|---|---|
| 8 | B (entry) | Variability within groups, comparing groups, fair sampling, question types |
| 9 | B | Associations in tidy tables, rates vs counts, data cleaning |
| 10 | B → C | Distributions, scatterplots, line of best fit, intro to models |
| 11 | C | Sampling variation, bootstrap/permutation, intervals, regression |
| 12 | C | Modelling, prediction, evaluation, communicating with data |
Level descriptions follow the publicly described structure of GAISE II (ASA/NCTM). We cite the framework; we do not copy its text.
Spiral rules¶
- Same five PPDAC headings in every unit and project from Gr 8 to 12.
- Anchor datasets recur (census districts, air quality, climate) at growing size.
- Each year adds one new tool layer: CODAP → SQL → pandas → inference/geo → ML.