{
  "id": 19444,
  "url": "https://arxiv.org/abs/2608.13409v1",
  "title": "Jointly Predicting Courses and Grades Using a Transformer-Based Model",
  "summary": "Existing predictive models in learning analytics often treat student academic history as a simple sequence, overlooking the concurrent nature of courses taken within a semester. This simplification can lead to inaccurate performance predictions, particularly for students with heavy or challenging course loads. This paper introduces a TRansformer for Academic Course-grade Estimation (TRACE) that addresses this limitation by jointly predicting both the set of courses a student will take and their",
  "authors": "Paul Savala",
  "category": "research",
  "topics": "children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-13T16:05:22.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/19444",
  "original_url": "https://arxiv.org/abs/2608.13409v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}