Pedagogical safety — ensuring AI tutors cannot mislead or harm learners — is studied in hazra-safetutors-pedagogical-safety-2026, eduguard-safe-rag-llm-tutor, petechat-guardrailed-ai-tutor, and vetting-dual-llm-safety-education: safety requires layered guardrails, evaluation, and human oversight (ethics, human-in-the-loop).
Related Pages
- eduzone-llm-safety-k12 — EduZone: an evaluation framework for LLM safety in K-12 education
📎 14 other pages tagged pedagogical-safety
- AI Tutor Safety and Pedagogical Harms
- Balancing AI responsibility with privacy, safety, and utility: Unlearning in large language models for mathematics education
- Child Safety in Generative AI: An Expert-Guided and Incident-Grounded Evaluation Framework
- Design Principles and Observable Indicators for AI-Enabled Pedagogical Accompaniment: Evidence from the Amico Dual-Mode Prototype in Italy and China
- Educational VLM Evaluation
- EduQwen: Pedagogical RL
- EduZone: A Framework for Evaluating LLM Safety for K-12 Students and Teachers
- Formative Assessment in AI Education
- Human-in-the-Loop AI for Education
- Multi-Agent Systems for Instructional Design
- Neural-Symbolic Knowledge Tracing
- Pedagogical Safety in Educational Reinforcement Learning
- SafeTutors: Pedagogical Safety in AI Tutoring
- VETTING: A dual-LLM framework for in-loop safety verification via policy isolation in educational AI