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[curriculum-eval] side-quest-01-02-environment-reference.md: checkpoint_quality — checkpoint invisible to rubric due to shortcode heading mismatch

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Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
75/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
markdown, python
Ambito
documentation, tooling

Direzione di ricerca

Iniziate in .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py leggendo CHECKPOINT_RE e la logica correlata di rilevamento dei checkpoint. Aggiornate il riconoscimento del formato di intestazione ✅, quindi eseguite nuovamente la rubrica del curriculum sul corpus del workshop e verificate che le sezioni di checkpoint valide non ricevano più un punteggio checkpoint_quality pari a zero. I suggerimenti separati sui contenuti del workshop rientrano nell’ambito facoltativo di un’attività successiva.

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

Descrizione

curriculum documentation quality

File: workshop/side-quest-01-02-environment-reference.md
Overall Score: 4.93 / 10.0 (corpus mean: 6.09 / 10.0)

Flagged Dimensions:

Dimension Score Benchmark Delta
checkpoint_quality 0.0 ≥ 4 items → ≥10 (has_checkpoint required) −10.0
active_learning 2.1 ≥ 3.0 density (10.0 cap) −0.9
cognitive_load 6.3 ≤ 800 words (10.0) −3.7

Root Cause (≤ 2 sentences):
The rubric's CHECKPOINT_RE only matches a literal ✅ emoji heading (## ✅ Checkpoint), but this file (like 90 of 93 workshop files) uses the :white_check_mark: shortcode instead, so has_checkpoint evaluates to False and checkpoint_quality is forced to 0.0 even though the page has a real, well-formed checkpoint with 7 checklist items. Separately, at 1,433 words this reference page is nearly double the 800-word cognitive-load ceiling and its 0.63 activity density (2 code blocks + 7 checklist items per ~1,430 words) is far below the ideal density of 3.

Evidence (quoted from the file):

✅ Checkpoint

  • You can name each environment and tool used in this workshop and describe its role

Learning Science Rationale:
Mayer's Signaling Principle holds that clear, consistently recognized structural cues (like a checkpoint heading) help learners self-assess progress; a checkpoint that exists in the markdown but is invisible to the scoring tool represents a measurement gap, not a content gap, and should be fixed at the rubric level, not by rewriting a correct heading. Independently, Sweller's Cognitive Load Theory predicts that a 1,433-word single-pass reference page with low activity density forces learners into passive reading rather than active retrieval, increasing extraneous load and reducing retention — the page would benefit from being split or from adding retrieval-practice checkboxes throughout, not just at the end.

Improvement Prompt (for an agent):

In .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py, update CHECKPOINT_RE (and any related prereq/checkpoint detection regex) to also match the ":white_check_mark:" shortcode heading format used across the workshop (e.g. "## :white_check_mark: Checkpoint"), in addition to the literal "✅" emoji. Re-run the rubric against the workshop corpus and confirm checkpoint_quality scores are no longer zero for files that have a valid checkpoint section. Separately, in workshop/side-quest-01-02-environment-reference.md, consider adding 2-3 short "quick check" checklist items or mini code snippets distributed through the glossary and screenshot sections (not just at the end) to raise activity_density above 3, and evaluate whether the glossary table and the conceptual-screenshots section could be split into two shorter pages to bring word_count under 800.

Expected Score After Fix: 7.0 / 10.0 (assuming rubric regex fix restores checkpoint_quality to ~10 and activity density improves modestly)

Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · 125.2 AIC · ⌖ 7.43 AIC · ⊞ 9K · ◷

  • expires on Sep 30, 2026, 1:09 PM UTC
Lingua principale
JavaScript
Stelle
51
Fork
23
Merge medio
8h 37m
PR unite (30g)
23

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