AIMC Topic: Learning

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Investigation and analysis of maker education curriculum from the perspective of artificial intelligence.

Scientific reports
As an education model that focuses on the cultivation of students' creativity and practical ability, the integration of maker education and the development of artificial intelligence is of great significance. In order to analyze and study the applica...

A checklist for reporting, reading and evaluating Artificial Intelligence Technology Enhanced Learning (AITEL) research in medical education.

Medical teacher
Advances in Artificial Intelligence (AI) have led to AI systems' being used increasingly in medical education research. Current methods of reporting on the research, however, tend to follow patterns of describing an intervention and reporting on resu...

Challenge, integration, and change: ChatGPT and future anatomical education.

Medical education online
With the vigorous development of ChatGPT and its application in the field of education, a new era of the collaborative development of human and artificial intelligence and the symbiosis of education has come. Integrating artificial intelligence (AI) ...

ChatGPT sits the DFPH exam: large language model performance and potential to support public health learning.

BMC medical education
BACKGROUND: Artificial intelligence-based large language models, like ChatGPT, have been rapidly assessed for both risks and potential in health-related assessment and learning. However, their applications in public health professional exams have not...

Contrastive learning of graphs under label noise.

Neural networks : the official journal of the International Neural Network Society
In the domain of graph-structured data learning, semi-supervised node classification serves as a critical task, relying mainly on the information from unlabeled nodes and a minor fraction of labeled nodes for training. However, real-world graph-struc...

Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior.

PLoS computational biology
Reinforcement learning (RL) models are used extensively to study human behavior. These rely on normative models of behavior and stress interpretability over predictive capabilities. More recently, neural network models have emerged as a descriptive m...

Probabilistic Motion Prediction and Skill Learning for Human-to-Cobot Dual-Arm Handover Control.

IEEE transactions on neural networks and learning systems
In this article, we focus on human-to-cobot dual-arm handover operations for large box-type objects. The efficiency of handover operations should be ensured and the naturalness as if the handover is going on between two humans. First of all, we study...

From Staining Techniques to Artificial Intelligence: A Review of Colorectal Polyps Characterization.

Medicina (Kaunas, Lithuania)
This review article provides a comprehensive overview of the evolving techniques in image-enhanced endoscopy (IEE) for the characterization of colorectal polyps, and the potential of artificial intelligence (AI) in revolutionizing the diagnostic accu...

Applying ChatGPT to tackle the side effects of personal learning environments from learner and learning perspective: An interview of experts in higher education.

PloS one
This paper investigates the capacity of ChatGPT, an advanced language model created by OpenAI, to mitigate the side effects encountered by learners in Personal Learning Environments (PLEs) within higher education. A series of semi-structured intervie...

Dyad motor learning in a wrist-robotic environment: Learning together is better than learning alone.

Human movement science
OBJECTIVE: Dyad motor practice is characterized by two learners alternating between physical and observational practice, which can lead to better motor outcomes and reduce practice time compared to physical practice alone. Robot-assisted therapy has ...