{
  "id": 19115,
  "url": "https://arxiv.org/abs/2608.12362",
  "title": "Strategy-Oriented Feedback for Fostering Systematic Problem-Solving in Machine Learning Education",
  "summary": "arXiv:2608.12362v1 Announce Type: new Abstract: Enabling students to develop systematic problem-solving strategies is a central goal in computing education and of particular relevance in the emerging field of machine learning (ML) education. While exploratory approaches are common in ML learning tasks, fostering the development and persistence of structured problem-solving strategies remains challenging, as these demand considerable metacognitive regulation and persistence, causing learners to o",
  "authors": "Clemens Witt, Thiemo Leonhardt, Erik Marx, Mareen Grillenberger",
  "category": "research",
  "topics": "regulation,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-14T04:00:00.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/19115",
  "original_url": "https://arxiv.org/abs/2608.12362",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}