{
  "id": 6684,
  "url": "https://arxiv.org/abs/2604.20870v2",
  "title": "Learning AI Without a STEM Background: Mixed-Methods Evidence from a Diverse, Mixed-Cohort AIED Program",
  "summary": "Despite growing interest in AI education, most AIED initiatives remain narrowly targeted toward STEM-prepared students, limiting participation by non-STEM learners and adults seeking to engage with AI in public-interest, policy, or workforce contexts. This paper presents and evaluates an NSF-funded, innovative mixed-cohort AI education model that intentionally integrates non-STEM undergraduates and adult learners into a shared learning environment centered on ethical reasoning, socio-technical j",
  "authors": "Valentina Kuskova, Dmitry Zaytsev, Richard Johnson",
  "category": "research",
  "topics": "regulation,jobs-economy,children-education,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-27T01:29:36.000Z",
  "fetched_at": "2026-07-14T16:32:41.665Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6684",
  "original_url": "https://arxiv.org/abs/2604.20870v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}