{
  "id": 18723,
  "url": "https://arxiv.org/abs/2608.11245",
  "title": "Towards Sustainable Learning in Online Education: A Reinforcement Learning Approach",
  "summary": "arXiv:2608.11245v1 Announce Type: cross Abstract: Online education offers unprecedented scalability and accessibility to global learners from diverse backgrounds, but it often suffers from low engagement and poor long term learning effectiveness. To address these challenges, we introduce AI Tutor, a reinforcement learning based model designed to promote sustainable learning by optimizing both short and longterm learning outcomes. In the short term, AI-Tutor draws on cognitive theory to guide lea",
  "authors": "Chaofan Zhai, Yicheng Song, Ravi Bapna, Junyao Ye",
  "category": "research",
  "topics": "children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-13T04:00:00.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "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/18723",
  "original_url": "https://arxiv.org/abs/2608.11245",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}