generative ai

CardioDiT: Latent Diffusion Transformers for 4D Cardiac MRI Synthesis

VolDiT: Controllable Volumetric Medical Image Synthesis with Diffusion Transformers

Teacher agency and generative AI: A cultural-historical analysis of contradictions in planning, instruction, and assessment

AI Control Model v1.0: A Tri-Phase Generative Control Framework

AI Control Model v1.0 presents a minimal generative‑control framework derived from the Tri‑Phase Generative Structure Model (Nomura, 2026). The model formalizes generative AI behavior as a recursive cycle of Dynamic (expansion), Static (contraction), and Breathing (reintegration) phases acting on an internal deep‑state...

STUDENT TEACHERS’ VIEWS ON AI-GENERATED SCIENCE LESSON PLANS: BALANCING PERCEIVED OPPORTUNITIES AND CRITICAL JUDGMENT

This study investigates student teachers’ evaluations of artificial intelligence (AI)-generated science lesson plans, with an emphasis on perceived usefulness and critical judgment. Data were collected from 124 student teachers who used generative AI (GenAI) to design lesson plans and subsequently evaluated these plans...

AUGMENTED INTELLIGENCE AND THE PURPLE EDUCATOR: HUMAN-CENTERED LEARNING IN THE AGE OF ACCELERATED TRANSFORMATION

In the age of accelerated transformation, higher education faculty are facing the reality that artificial intelligence is part of the educational context. The article introduces the Purple Educator Model as a descriptive faculty role focused on developing soft skills alongside technical competencies. Additionally, the...

AI Control Model v1.0: A Tri-Phase Generative Control Framework

AI Control Model v1.0 presents a minimal generative‑control framework derived from the Tri‑Phase Generative Structure Model (Nomura, 2026). The model formalizes generative AI behavior as a recursive cycle of Dynamic (expansion), Static (contraction), and Breathing (reintegration) phases acting on an internal deep‑state...

The Plausibility Trap: Using Probabilistic Engines for Deterministic Tasks

The ubiquity of Large Language Models (LLMs) is driving a paradigm shift where user convenience supersedes computational efficiency. This article defines the "Plausibility Trap": a phenomenon where individuals with access to Artificial Intelligence (AI) models deploy expensive probabilistic engines for simple determini...

Laboratory 4.0: on the path to the fourth generation of laboratory medicine

Abstract Laboratory medicine has witnessed three generational paradigm shifts over the past 75 years – from manual work to early automation, from batch processing to patient-oriented selective analysis, and from human perianalytics to Total Laboratory Automation (TLA). Drawing on a personal trajectory spanning half a c...

ChatGPT and Generative AI in Physical Education: Applications, Benefits, Limitations, and Risks for Teachers, Students, Coaches, and Professionals

The article proposes the Human-Supervised Generative AI Framework for Physical Education and Sport, which classifies tasks by consequence and requires source grounding, data minimization, professional review, disclosure, and outcome monitoring.

AI-Assisted Writing and Presenting in English, by A. Wallwork

The widespread integration of Generative Artificial Intelligence (GenAI) into higher education has transformed conventional practices for drafting, revising, translating, and presenting academic work.For multilingual researchers, large language models (or LLMs) provide immediate linguistic support, but their use also r...

A Cross-sectional Dataset on Technology Acceptance, Academic AI-Integration, Behavioral and Self Directed Learning Readiness among Law Students in Bangladesh

This dataset contains cross-sectional survey data from 412 enrolled law students at a private university in Bangladesh, collected between 10 January and 10 July 2026 using a structured online questionnaire. Participants were recruited through purposive sampling. The dataset was developed to support research on generati...