{
  "id": 11066,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1841682",
  "title": "Designing AI-resilient assessment in higher education: a four-pillar conceptual framework",
  "summary": "Generative AI tools can produce polished academic text on demand, undermining the validity of assessments that treat written submissions as evidence of individual learning. Detection-based countermeasures have demonstrated variable accuracy and equity concerns. This paper does not report empirical outcomes or validation data. It proposes a framework for AI-resilient assessment that shifts evaluation from product quality to demonstrable reasoning, decision-making, and ownership of learning. The f",
  "authors": "Dragan Nikolić",
  "category": "research",
  "topics": "bias-fairness,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-16T00:00:00.000Z",
  "fetched_at": "2026-07-17T05:10:53.887Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/11066",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1841682",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}