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Generative AI in Higher Education: Balancing Innovation and Integrity.

British journal of biomedical science
Generative Artificial Intelligence (GenAI) is rapidly transforming the landscape of higher education, offering novel opportunities for personalised learning and innovative assessment methods. This paper explores the dual-edged nature of GenAI's integ...

A systematic review of the impact of artificial intelligence on educational outcomes in health professions education.

BMC medical education
BACKGROUND: Artificial intelligence (AI) has a variety of potential applications in health professions education and assessment; however, measurable educational impacts of AI-based educational strategies on learning outcomes have not been systematica...

Exploring continual learning strategies in artificial neural networks through graph-based analysis of connectivity: Insights from a brain-inspired perspective.

Neural networks : the official journal of the International Neural Network Society
Artificial Neural Networks (ANNs) aim at mimicking information processing in biological networks. In cognitive neuroscience, graph modeling is a powerful framework widely used to study brain structural and functional connectivity. Yet, the extension ...

Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.

Nature communications
Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackl...

Development of compositionality through interactive learning of language and action of robots.

Science robotics
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental que...

Self-supervised learning of scale-invariant neural representations of space and time.

Journal of computational neuroscience
Hippocampal representations of space and time seem to share a common coding scheme characterized by neurons with bell-shaped tuning curves called place and time cells. The properties of the tuning curves are consistent with Weber's law, such that, in...

Dynamic planning in hierarchical active inference.

Neural networks : the official journal of the International Neural Network Society
By dynamic planning, we refer to the ability of the human brain to infer and impose motor trajectories related to cognitive decisions. A recent paradigm, active inference, brings fundamental insights into the adaptation of biological organisms, const...

Neural mechanisms of relational learning and fast knowledge reassembly in plastic neural networks.

Nature neuroscience
Humans and animals have a striking ability to learn relationships between items in experience (such as stimuli, objects and events), enabling structured generalization and rapid assimilation of new information. A fundamental type of such relational l...

Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton.

Science robotics
For trained individuals such as athletes and musicians, learning often plateaus after extensive training, known as the "ceiling effect." One bottleneck to overcome it is having no prior physical experience with the skill to be learned. Here, we chall...

Machine learning approach to student performance prediction of online learning.

PloS one
Student performance is crucial for addressing learning process problems and is also an important factor in measuring learning outcomes. The ability to improve educational systems using data knowledge has driven the development of the field of educati...