{
  "id": 6499,
  "url": "https://arxiv.org/abs/2604.00730v2",
  "title": "A CEFR-Inspired Classification Framework with Fuzzy C-Means To Automate Assessment of Programming Skills in Scratch",
  "summary": "Context: Schools, training platforms, and technology firms increasingly need to assess programming proficiency at scale with transparent, reproducible methods that support personalized learning pathways. Objective: This study introduces a pedagogical framework for Scratch project assessment, aligned with the Common European Framework of Reference (CEFR), providing universal competency levels for students and teachers alongside actionable insights for curriculum design. Method: We apply Fuzzy C-M",
  "authors": "Ricardo Hidalgo-Aragón, Jesús M. González-Barahona, Gregorio Robles",
  "category": "research",
  "topics": "children-education,transparency",
  "orgs": null,
  "regions": "eu",
  "published_at": "2026-04-01T10:42:07.000Z",
  "fetched_at": "2026-07-14T16:32:33.100Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6499",
  "original_url": "https://arxiv.org/abs/2604.00730v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}