{
  "id": 6203,
  "url": "https://arxiv.org/abs/2604.06898v1",
  "title": "Are LLMs Ready for Computer Science Education? A Cross-Domain, Cross-Lingual and Cognitive-Level Evaluation Using Professional Certification Exams",
  "summary": "Large language models (LLMs) are increasingly applied in computer science education for tasks such as tutoring, content generation, and code assessment. However, systematic evaluations aligned with formal curricula and certification standards remain limited. This study benchmarked four recent models, including GPT-5, DeepSeek-R1, Qwen-Plus, and Llama-3.3-70B-Instruct, using a dataset of 1,068 questions derived from six certification exams covering networking, office applications, and Java progra",
  "authors": "Chen Gao, Chi Liu, Zhengquan Luo, Dongfu Xiao, Maiying Sui, Sheng Shen et al.",
  "category": "research",
  "topics": "children-education",
  "orgs": "openai,deepseek",
  "regions": null,
  "published_at": "2026-04-08T09:56:31.000Z",
  "fetched_at": "2026-07-14T16:32:20.054Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6203",
  "original_url": "https://arxiv.org/abs/2604.06898v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}