[curriculum-eval] curriculum_assessment.py: checkpoint_quality — regex misses :white_check_mark: shortcode, 92/94 pages scored as having no checkp

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Evaluación

Dificultad
2/5
Tiempo estimado
1-3 horas
Aptitud para principiantes
62/100
Tipo de issue
Error
Claridad
Bien especificado
Estado de actividad
Activo
Stack tecnológico
github-actions, markdown, python
Área
documentation, tooling

Línea de trabajo

Empieza en .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py y localiza CHECKPOINT_RE y la expresión regular has_prereq_section, que solo coinciden con emojis literales. Después revisa la pista de Bloom activity:checkpoint y NUMBERED_HDR_RE para ver si siguen el mismo patrón. Para verificarlo, usa workshop/04-github-actions-intro.md: la línea 138 usa el shortcode ✅ y debería puntuar has_checkpoint=true. Está terminado cuando pasa una prueba unitaria con un fixture de shortcode y, al volver a ejecutar la evaluación, esta informa que el checkpoint está presente.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

curriculum documentation quality

File: .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py (affects every workshop/*.md)
Overall Score: 6.06 / 10.0 corpus mean (threshold 5.52)

Flagged Dimensions:

Dimension Score Benchmark Delta
checkpoint_quality 0.0 on 92/94 pages ≥ 4 items → 10 −10
scaffolding 5.0 on nearly all pages 10 when section present −5

Root Cause (≤ 2 sentences):
CHECKPOINT_RE = r"##\s+✅\s*Checkpoint" and the scaffolding regex ##\s+📋\s*Before You Start only match literal emoji, but the workshop (per AGENTS.md conventions) writes ## :white_check_mark: Checkpoint and ## :clipboard: Before You Start. Pages are therefore scored as lacking checkpoints and prerequisites despite having them, cutting ~2–3 points from each overall score.

Evidence (quoted from the file):

workshop/04-github-actions-intro.md line 138: ## :white_check_mark: Checkpoint followed by 5 checklist items (scored has_checkpoint: false, checkpoint_quality: 0.0); line 21: ## :clipboard: Before You Start (scored has_prereq_section: false).

Learning Science Rationale:
Valid measurement is a precondition for applying Bloom's, Cognitive Load, or Mayer-based feedback. A false-negative checkpoint metric hides the real signal (retrieval-practice checkpoints, per the testing effect, are present) and sends agents to "fix" pages that are fine, while masking real weaknesses such as low activity density and word count over 800 on side-quest-01-02-environment-reference.md and 05-agentic-workflows-intro.md.

Improvement Prompt (for an agent):

In .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py, update CHECKPOINT_RE to match "## ✅ Checkpoint" OR "## :white_check_mark: Checkpoint" (e.g. r"##\s+(?:✅|:white_check_mark:)\s*Checkpoint", re.IGNORECASE), and update the has_prereq_section regex to accept "## 📋 Before You Start" OR "## :clipboard: Before You Start" OR "## Prerequisites". Also check NUMBERED_HDR_RE/other emoji-dependent patterns and the Bloom "activity:checkpoint" cue use the same updated regex. Add a unit test with a fixture using the shortcode form. Re-run the assessment and confirm that pages like workshop/04-github-actions-intro.md report has_checkpoint=true and checkpoint_quality=10.

Expected Score After Fix: 8.0 / 10.0 corpus mean (up from 6.06)

Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · ~48 AIC · ⌖ ~1 AIC · ⊞ 5K · ◷

  • expires on Nov 14, 2026, 6:04 AM UTC
Lenguaje dominante
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