Aisha's AIRS Cohorts — Schema =================================== Flat, aggregate-only teaching dataset in aisha-airs-cohorts.csv. Columns ------- Column Type Description ----------- ------- ------------------------------------------------------------------------ cohort_id integer Sequential cohort number (1 = earliest, 6 = most recent). semester text Semester the cohort took the course (e.g. Fall 2023, Spring 2024). start_score number Cohort mean AIRS score at the start of the course (0–100). end_score number Cohort mean AIRS score at the end of the course (0–100). gain number end_score minus start_score; positive means the course moved the cohort. Row inventory ------------- - 6 cohort rows (Fall 2023 through Spring 2026), one per semester. Total: 6 rows. Deliberate design choices ------------------------- Unlike the four cross-chapter teaching datasets (CloudRevenue, M365Marketing, SupportInsights, EnterpriseGovernance), this dataset has no injected null-value or naming-inconsistency imperfections. Its purpose is to reproduce Chapter 6’s Aisha figure exactly, and the figure's defects live in the palette-type mismatch and encoding choices, not in the data. The one designed-in tension is the gain gradient across cohorts: Cohort 6 shows a materially larger gain than Cohort 1 (+24 vs +11, roughly 2.2x). That contrast is the Big Idea Aisha's figure is trying to communicate; a chart that hides it (as her brand-palette version does) is failing its audience. License ------- Released for teaching use alongside The Defensible Decision. Use freely.