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[workshop-sim] Repair: Fix CHECKPOINT_RE regex to match :white_check_mark: shortcode so checkpoint_quality is scored correctly

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Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
84/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Attiva
Stack tecnologico
python
Ambito
testing-qa, tooling

Direzione di ricerca

Inizia da .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py e ispeziona CHECKPOINT_RE e il relativo flusso di valutazione. Esegui la valutazione sulla directory workshop/, aggiungi o aggiorna la copertura della suite di test dello script di valutazione per ✅ e verifica che tutti i 30 passaggi vengano ricalcolati senza regressioni, mantenendo invariato il contenuto di workshop/.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

feedback simulation workshop

Problem statement

The shared curriculum quantitative assessment script (.github/skills/curriculum-quantitative-assessment/curriculum_assessment.py) detects checkpoints using CHECKPOINT_RE = re.compile(r"##\s+✅\s*Checkpoint", re.IGNORECASE), which only matches a literal ✅ Unicode character. Every workshop step actually uses the GitHub Markdown emoji shortcode ## :white_check_mark: Checkpoint (per repository convention documented in .github/workflows/guidelines.md). As a result, has_checkpoint evaluates False and checkpoint_quality scores 0.0 for all 30 main workshop steps, even though every step has a well-formed checkpoint section with checklist items. This silently depresses overall_score and the Learning KPI index for every step in the curriculum, masking real signal about which steps actually need checkpoint improvements.

Proposed change

Update CHECKPOINT_RE to also match the :white_check_mark: shortcode form, e.g.:

CHECKPOINT_RE = re.compile(r"##\s+(?:✅|:white_check_mark:)\s*Checkpoint", re.IGNORECASE)

Re-run the assessment script against the full workshop/ directory and confirm checkpoint_quality scores now reflect each step's actual checklist quality (checklist item count, presence of recovery/troubleshooting guidance, etc.) rather than a uniform 0.0.

Failure mode classification

Learning barrier (measurement defect) — this is not a learner-facing instructional gap; it is a rubric detection bug that misrepresents real instructional quality. Fixing it corrects the Learning KPI index measurement itself rather than changing any workshop content.

Quantitative guardrail

Current cohort-wide impact:

  • checkpoint_quality mean across all 30 steps: 0.0/10 (should reflect real variation once fixed)
  • Cohort-wide Learning KPI index: 2.88/10 — abnormally low because 2.0× weight is applied to a dimension that is uniformly zero
  • Example step 07d-confirm-model-access.md: overall_score 6.25/10, learning KPI index currently 3.65/10 using the incorrect checkpoint_quality=0.0

This change should raise checkpoint_quality (and therefore overall_score and the Learning KPI index) for every step whose checkpoint section already has real content — it must not be used as a pretext to avoid separately improving steps whose checkpoints are genuinely weak (e.g., steps lacking any recovery guidance, per the companion 04-github-actions-intro.md issue).

Acceptance criteria

  • The shared curriculum quantitative assessment overall_score stays flat or improves for every step after the regex fix (no step should regress)
  • The Learning KPI index (2.0 × active_learning + 2.0 × checkpoint_quality + 1.5 × scaffolding) / 5.5 is recomputed for all 30 steps and the cohort mean rises to reflect real checkpoint quality, no longer uniformly suppressed by the detection bug
  • Existing checkpoint checklists, hands-on practice, and scaffolding content are left unchanged — this issue only touches the measurement script, not workshop content
  • Unit test added/updated in the assessment script's test suite covering the :white_check_mark: shortcode form

Suggested owner

copilot coding agent (contained, mechanical regex fix with clear acceptance criteria)
Related to #4172

Generated by 🔬 Workshop Student Simulator · copilot · auto · 223.6 AIC · ⌖ 20.5 AIC · ⊞ 15.1K · ◷

  • expires on Oct 5, 2026, 7:37 AM UTC
Lingua principale
JavaScript
Stelle
51
Fork
23
Merge medio
11h 32m
PR unite (30g)
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