arXiv:2606. 18548v1 Announce Type: cross Abstract: Adaptive AI ethics instruction in graduate research training benefits from intake measures that reflect differences in prior LLM experience.
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The study examined the impact of expert‑verified AI‑generated study materials on first‑year university economics students. In a two‑cohort difference‑in‑differences design, half of the 170 students received podcasts, FAQs, and quiz‑based guides that were produced by a source‑grounded model and checked by a graduate teaching assistant. The intervention produced a 2.34‑mark advantage on a 50‑mark component, reduced the share of marks below the upper‑second classification boundary by 24.7 percentage points, and had the largest gains for students in the bottom quintile. Interviews with 36 students suggested that the verification label encouraged engagement while preserving critical scrutiny of the AI output.
arXiv:2607. 20461v1 Announce Type: cross Abstract: Present implementations of artificial intelligence (AI) ethics do not adequately take feelings, or affect, into account.
arXiv:2607. 01934v1 Announce Type: cross Abstract: This work introduces AIriskEval-edu-db2, a new dataset designed to train and evaluate auditors based on LLMs for an explainable pedagogical risk assessment in instructional content for grades K-12.
arXiv:2605. 03217v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in settings that require nuanced ethical reasoning, yet existing bias evaluations treat model outputs as simply "biased" or "unbiased.
arXiv:2603. 00048v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive applications including psychological support, healthcare, and high-stakes decision-making.
This work introduces AIriskEval-edu-db2, a new dataset designed to train and evaluate auditors based on LLMs for an explainable pedagogical risk assessment in instructional content for grades K-12. The dataset comprises 1,639 explanations from 170 curated ScienceQA questions, covering science, language arts, and social sciences.