{
  "id": 10472,
  "url": "https://arxiv.org/abs/2607.12221v1",
  "title": "From Chaos to Clarity: A Framework for Program-Level AI Learning Outcomes",
  "summary": "Industry is leaning into generative artificial intelligence (GenAI), and higher education is under pressure to prepare graduates for a GenAI-augmented workforce. Yet, there is still no clear structure for defining AI readiness across disciplines, programs, courses, and assignments. Current approaches often rely on broad institutional policies or individual course-level decisions, which can also create mixed messages for students, fragmented expectations across programs, and limited visibility fo",
  "authors": "Grace Barkhuff, Ian Pruitt, William Gregory Johnson, Rodrigo Borela, Ben Rydal Shapiro, Anu G. Bourgeois",
  "category": "research",
  "topics": "jobs-economy,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-13T23:45:40.000Z",
  "fetched_at": "2026-07-15T05:10:55.633Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/10472",
  "original_url": "https://arxiv.org/abs/2607.12221v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}