{
  "id": 5064,
  "url": "https://arxiv.org/abs/2606.11215v1",
  "title": "The Environmental Cost of LLMs in AIED: Reporting and Practices",
  "summary": "Large Language Model (LLM) usage in recent years has become increasingly widespread in the Artificial Intelligence in Education (AIED) community. While LLMs offer unique avenues for learners and educators, using LLMs comes with computational and environmental costs. These costs are mostly hidden due to a lack of standardised procedures to measure and report these impacts. To address this gap, we first conducted a literature review of all papers published as part of the AIED 2025 conference proce",
  "authors": "Sabrina C. Eimler, Lukas Erle, Daniel Flood, Aditi Haiman, Luca Häckert, André Helgert et al.",
  "category": "research",
  "topics": "children-education,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-03T00:50:27.000Z",
  "fetched_at": "2026-07-14T16:31:31.208Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5064",
  "original_url": "https://arxiv.org/abs/2606.11215v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}