AIMC Topic: Learning

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Federated TriNet-AQ: Explainable english proficiency classification in augmented and virtual reality learning.

PloS one
AR/VR and other immersive technologies are creating dynamic, learner-centred, and engaging language-learning environments. In these ever-changing situations, judging someone's language abilities is difficult. Managing multimodal learner inputs, under...

Learning robot behavior from human-human interactions.

Science robotics
A model trained by observing human-human interactions produces more natural robot behavior during human-robot interaction.

Spiking world model with multicompartment neurons for model-based reinforcement learning.

Proceedings of the National Academy of Sciences of the United States of America
Brain-inspired spiking neural networks (SNNs) have garnered significant research attention in algorithm design and perception applications. However, their potential in the decision-making domain, particularly in model-based reinforcement learning, re...

Evaluating AI-Generated Podcasts Versus Traditional Reading for Learning From Medical Articles: Protocol for a Mixed-Design Study Among Resident Physicians.

JMIR research protocols
BACKGROUND: Podcasts have emerged as a popular medium in medical education over the past decade. Audio learning allows flexibility and may help residents engage with content in new ways. Reading scientific literature is a core skill for residents, ye...

Culturally-attuned AI: Implicit learning of altruistic cultural values through inverse reinforcement learning.

PloS one
Constructing a universal moral code for artificial intelligence (AI) is challenging because human cultures have different values, norms, and social practices. We therefore argue that AI systems should adapt to culture based on observation: Just as a ...

A gamification training system designed according to a mental model structure: A case study of universal robots.

Scientific reports
As part of the industrial revolution, the collaborative robot (cobot) has become increasingly important in Industry 5.0. However, the most significant barrier for the industry to adopt the cobot is a lack of knowledge and skills. Therefore, e-learnin...

Transformer-based deep learning for adaptive pedagogy under uncertain student preferences.

Scientific reports
As educational environments become increasingly heterogeneous, conventional teaching strategies often fall short in accommodating the diverse and evolving learning behaviors of students, particularly when individual learning preferences are ambiguous...

Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatial.

Proceedings of the National Academy of Sciences of the United States of America
Information processing in the brain relies on the transmission of spikes through chemical synapses whose efficacies often depend on their recent firing history. While effects of such short-term plasticity on neural information processing have long be...

Engagement patterns of middle school students with AI teachable agents in mathematics learning.

Scientific reports
 This study investigates how secondary students engage with an AI teachable agent (TA) during mathematics learning, with particular focus on learners whose performance declined after interacting with the TA system. Using a mixed-methods design, we an...

The MIND model a microlearning AI-integrated instructional design for enhanced learning outcomes.

Scientific reports
In recent years, microlearning has gained significant attention due to technological advancements such as generative AI (GenAI), diverse learner needs, and a growing emphasis on improving learning outcomes. However, designing effective microlearning ...