AIMC Topic: Learning

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Dental Students' Learning Experience: Artificial Intelligence vs Human Feedback on Assignments.

International dental journal Jan 10, 2025
OBJECTIVE: This study evaluated the effectiveness of an AI-based tool (ChatGPT-4) (AIT) vs a human tutor (HT) in providing feedback on dental students' assignments.
Formative Feedback Students, Dental Educational Measurement Education, Dental Artificial Intelligence Learning Feedback Male Female Humans
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Generative AI in Higher Education: Balancing Innovation and Integrity.

British journal of biomedical science Jan 9, 2025
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...
Learning Humans Students Universities Artificial Intelligence
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Dynamic planning in hierarchical active inference.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2025
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...
Reinforcement, Psychology Decision Making Robotics Neural Networks, Computer Humans Brain Learning Artificial Intelligence Animals
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Synergistic learning with multi-task DeepONet for efficient PDE problem solving.

Neural networks : the official journal of the International Neural Network Society Jan 3, 2025
Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine l...
Machine Learning Learning Problem Solving Humans Neural Networks, Computer
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AI and Uncertain Motivation: Hidden allies that impact EFL argumentative essays using the Toulmin Model.

Acta psychologica Jan 3, 2025
This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated ...
Uncertainty Female Saudi Arabia Young Adult Writing Motivation Male Learning Humans Adult Students Artificial Intelligence
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Predicting learning achievement using ensemble learning with result explanation.

PloS one Jan 2, 2025
Predicting learning achievement is a crucial strategy to address high dropout rates. However, existing prediction models often exhibit biases, limiting their accuracy. Moreover, the lack of interpretability in current machine learning methods restric...
Humans Learning Students Machine Learning Logistic Models Algorithms
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Biologically plausible gated recurrent neural networks for working memory and learning-to-learn.

PloS one Dec 31, 2024
The acquisition of knowledge and skills does not occur in isolation but learning experiences amalgamate within and across domains. The process through which learning can accelerate over time is referred to as learning-to-learn or meta-learning. While...
Memory, Short-Term Nerve Net Animals Models, Neurological Humans Brain Neural Networks, Computer Learning
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Deep neural networks and humans both benefit from compositional language structure.

Nature communications Dec 30, 2024
Deep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce forms for new meanings. For humans, languages with more compositional ...
Natural Language Processing Linguistics Humans Learning Language Neural Networks, Computer Deep Learning
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Unified Knowledge-Guided Molecular Graph Encoder with multimodal fusion and multi-task learning.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
The remarkable success of Graph Neural Networks underscores their formidable capacity to assimilate multimodal inputs, markedly enhancing performance across a broad spectrum of domains. In the context of molecular modeling, considerable efforts have ...
Humans Neural Networks, Computer Models, Molecular Machine Learning Learning
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Enhancing consistency and mitigating bias: A data replay approach for incremental learning.

Neural networks : the official journal of the International Neural Network Society Dec 20, 2024
Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, as old data from previous tasks is unavailable when learning a new task. To address this, some methods propose replaying data from previous tasks durin...
Learning Deep Learning Humans Neural Networks, Computer Bias
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