LLM Use, Cheating, and Academic Integrity in Software Engineering Education

Collection of recent research (arXiv) documenting both beneficial and risky real-world uses of large language models (LLMs). Key findings: student misuse of LLMs in programming and coursework complicates academic integrity; BiasRecBench demonstrates that LLMs used as recommender agents (paper review, e‑commerce, recruitment) are readily manipulated by contextual biases; GUIDE describes LLM‑aided IP piracy and classroom projects that enabled LLM-assisted hardware‑Trojan insertion; an EHR‑integrated LLM triage tool (SCM Navigator) achieved high sensitivity but exposed edge misclassification and‑