generative ai

AI-induced labour market shocks and inclusive labour market resilience: an LLM-assisted rapid causal evidence synthesis using directed acyclic graphs (ESC-DAGs)

Protocol of a rapid systematic review that synthesises causal evidence on how AI-related technology shocks (industrial robots, software automation, machine learning and generative AI) affect inclusive labour market resilience: resistance, recovery, re-orientation and renewal of employment, hours, hiring, wages and real...

Modular Synthetic Clinical Environment Qualification: Public Comment to FDA Docket FDA-2026-N-7874

This public comment proposes Modular Synthetic Clinical Environment Qualification (MSCEQ), a framework for independently qualifying reusable synthetic clinical environments before using them to evaluate generative AI-enabled medical devices. Environments would represent specific clinical settings, including changing pa...

Governing the Use of Generative AI Applications in Developing Independent Skills for Students with Autism: A Proposed Model for Achieving School Quality of Life

Generative AI and Scientific Publishing: Preserving Accountability, Trust, and Governance

An extended theory of planned behavior model of generative AI use intention for music composition among Chinese music students

Findings suggest that educators could support students in developing calibrated judgments of GenAI reliability, evaluating its suitability for specific composition tasks, and addressing AI-related anxiety while preserving authorship and creative agency.

LACO-GAI: A Laplace Copula Generative AI Network Model for Accurate Stroke Disease Prediction

Stroke is major wellbeing condition which creates serious hazard to human health and cause of bereavement and disability universal. Several risk factors contribute to its development, including hypertension, diabetes, tobacco use, raised cholesterol levels, and obesity. Conventional methods have been used to predict st...

Enhancing PISA-aligned argumentation skills of prospective biology teachers through generative artificial intelligence

Despite scientific argumentation being a fundamental competency of the PISA assessment framework, prospective biology teachers often demonstrate insufficient development in evidence-based reasoning and rebuttal construction skills. Considering the limitations of large-scale implementation of individualized approaches i...

Digital translation practices in university English learning: adoption, disciplinary variation, and AI-assisted revision

Introduction Machine translation and generative artificial intelligence (AI) are now common resources in English as a foreign language learning, yet evidence from Latin American higher education remains limited and often conflates tool use with learning impact. This study characterized translation practices, tool prefe...

Charting the rise of artificial intelligence in medical education: a global bibliometric and network analysis, 2000–2026

Artificial intelligence has moved from a peripheral curiosity to a core feature of modern medical education through adaptive learning, simulation-based training, automated assessment, and large language models such as ChatGPT. Publication activity has accelerated rapidly, but the structure of this expanding literature...

AI in Chemistry Education: A Thematic Narrative Review of Opportunities, Limitations, and Equity Gaps (2020–2026)

Generative artificial intelligence (AI) has prompted rapidly growing body of scholarship on the role in chemistry education since the public release of ChatGPT in the late of 2022. This thematic narrative review synthesizes 40 English-language sources including empirical studies, curriculum reports, and stakeholder sur...

The Hidden Curriculum of Generative AI: Institutional AI Policies and the Potential for Student Inequality

Generative artificial intelligence (GenAI) is increasingly integrated into higher education, prompting institutions to develop policies governing its use in teaching, learning, and assessment. Although existing discussions have emphasized academic integrity, assessment practices, and technological access, less attentio...

Generative AI-Powered Interdisciplinary Chemistry Practice in Junior High: Exploring Matter Composition and Structure

To address persistent issues in junior high chemistry teaching of Composition and Structure of Substances—including fragmented disciplinary perspectives, highly abstract micro-level concepts, and underdeveloped macro-submicro-symbolic triple representation thinking—this study constructs a four-stage interdisciplinary p...