EduGuard: A Safe RAG-Based LLM Tutor for Programming Education
arXiv:2607.15738v1 Announce Type: new Abstract: Generative AI (GenAI) is increasingly used by students for programming explanation, debugging, and assignment support. Yet unrestricted large language model (LLM) tutors can hallucinate, contradict course policy, reveal complete solutions, and foster passive dependence. This paper presents EduGuard, a safe retrieval-augmented generation (RAG) tutoring framework for introductory programming. EduGuard integrates query understanding, instructor-approv
Record details
Published: 20 July 2026
Source: arXiv cs.CY
Category: Research
Topics: Regulation · Children & education
Retrieved: 20 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
EduGuard: A Safe RAG-Based LLM Tutor for Programming Education
arXiv · 17 July 2026
VETTING: A dual-LLM framework for in-loop safety verification via policy isolation in educational AI
Computers and Education: Artificial Intelligence · 20 July 2026
Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education
arXiv · 22 July 2026
AI adoption readiness among Ukrainian education managers: Barriers, typologies, and policy implications
Computers and Education: Artificial Intelligence · 22 July 2026
Balancing public health and individual autonomy: a study of Chinas vaccination policy
Journal of Medical Ethics (BMJ) · 22 July 2026
CADENCE: Closing the Reasoning Gap via Coverage-Adaptive On-Policy Distillation
HuggingFace Daily Papers · 17 July 2026
How to cite this record
ethics.ai (20 July 2026), “EduGuard: A Safe RAG-Based LLM Tutor for Programming Education,” evidence record 11731, https://ethics.ai/record/11731 (originally published by arXiv cs.CY).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.