{
  "id": 11947,
  "url": "https://arxiv.org/abs/2510.15936",
  "title": "Large Language Models in Architecture Studio: A Framework for Learning Outcomes",
  "summary": "arXiv:2510.15936v3 Announce Type: replace Abstract: The study explores the role of large language models (LLMs) in the context of the architectural design studio, understood as the pedagogical core of architectural education. Traditionally, the studio has functioned as an experiential learning space where students tackle design problems through reflective practice, peer critique, and faculty guidance. However, the integration of artificial intelligence (AI) in this environment has been largely f",
  "authors": "Juan David Salazar Rodriguez, Sam Conrad Joyce, Nachamma Sockalingam, Khoo Eng Tat, Julfendi",
  "category": "research",
  "topics": "children-education,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-21T04:00:00.000Z",
  "fetched_at": "2026-07-21T05:10:12.656Z",
  "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/11947",
  "original_url": "https://arxiv.org/abs/2510.15936",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}