{
  "id": 2242,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1842542",
  "title": "PaSTO-GNN: prompt-aware spatio-temporal graph neural networks for automatic essay scoring",
  "summary": "Automatic Essay Scoring (AES) aims to evaluate the quality of written essays automatically, providing fast, consistent, and objective assessments of students' writing ability. Existing deep learning approaches—including recurrent, convolutional, and transformer-based models—primarily focus on textual semantics, yet they often overlook the spatio-temporal nature of essay composition, where meaning evolves across sentences and paragraphs through discourse progression. To address this gap, this stu",
  "authors": "Areej Alhothali",
  "category": "research",
  "topics": "children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-08T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:11:46.979Z",
  "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/2242",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1842542",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}