{
  "id": 18735,
  "url": "https://arxiv.org/abs/2603.00056",
  "title": "How effective are VLMs in assisting humans in inferring the quality of mental models from Multimodal short answers?",
  "summary": "arXiv:2603.00056v2 Announce Type: replace Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what students know but also into how effectively they can apply, relate to, and integrate concepts across various contexts. Thus, students' responses are critical markers of the quality of their understanding and not entities that should be merely graded. However, inferring these mental models from student an",
  "authors": "Pritam Sil, Durgaprasad Karnam, Vinay Reddy Venumuddala, Pushpak Bhattacharyya",
  "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/18735",
  "original_url": "https://arxiv.org/abs/2603.00056",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}