Hallucination risk — fabricated content from LLMs — is a documented failure mode in educational settings: llm-cognitive-diagnosis-handwritten-math, eduguard-safe-rag-llm-tutor, vetting-dual-llm-safety-education, and llm-fallacy-misattribution examine detection, mitigation, and the misattribution of model errors to students (over-reliance, trust-calibration).
LLM hallucination risks in educational contexts
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📎 11 other pages tagged hallucination-risk
- Stuck in a Spiral": Shame and Guilt as Social Regulators of AI Use in Computing Education
- AI as a Partner in Learning about, Doing, and Engaging with Science: Vigilance as the Key to Productive Augmentation
- Benchmarking Large Language Models for Diagnosing Students' Cognitive Skills from Handwritten Math Work
- Confirming Correct, Missing the Rest: LLM Tutoring Agents Struggle Where Feedback Matters Most
- EduGuard: A Safe RAG-Based LLM Tutor for Programming Education
- Evaluating Prompt Injection Defenses for Educational LLM Tutors: Security-Usability-Latency Trade-offs
- Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education
- Simulating Students or Sycophantic Problem Solving? On Misconception Faithfulness of LLM Simulators
- Sycophancy is an Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks
- The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaboration
- Warning About AI Fallibility Increases Help-Seeking in an Intelligent Tutoring System