AIMC Topic: Learning
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Gated recurrent deep learning approaches to revolutionizing English language learning for personalized instruction and effective instruction.
Scientific reports
Apr 15, 2025
Communication is essential for success in today's world, making English language learning (ELL) a crucial skill. Innovative solutions are required to tackle complex language learning issues and meet the various demands of learners. Personalized learn...
A knowledge tracing approach with dual graph convolutional networks and positive/negative feature enhancement network.
PloS one
Apr 9, 2025
Knowledge tracing models predict students' mastery of specific knowledge points by analyzing their historical learning performance. However, existing methods struggle with handling a large number of skills, data sparsity, learning differences, and co...
Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing.
PloS one
Apr 7, 2025
In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing model (CL-PTKT...
A personalized recommendation algorithm for English exercises incorporating fuzzy cognitive models and multiple attention mechanisms.
Scientific reports
Apr 4, 2025
In the era of digital education, the rapid growth and disordered distribution of learning resources present new challenges for online learning. However, most of the exercise recommendation systems lack targeted guidance and personalization. In respon...
Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectiv...
Curriculum is more influential than haptic feedback when learning object manipulation.
Science advances
Apr 2, 2025
Dexterous manipulation remains an aspirational goal for autonomous robotic systems, particularly when learning to lift and rotate objects against gravity with intermittent finger contacts. We use model-free reinforcement learning to compare the effec...
Mastering diverse control tasks through world models.
Nature
Apr 2, 2025
Developing a general algorithm that learns to solve tasks across a wide range of applications has been a fundamental challenge in artificial intelligence. Although current reinforcement-learning algorithms can be readily applied to tasks similar to w...
[How older people are learning through artificial intelligence-assisted health technologies : Cute seals and nervous fall sensors].
Zeitschrift fur Gerontologie und Geriatrie
Mar 27, 2025
BACKGROUND: With the growing use of artificial intelligence (AI) in various areas of life, AI technologies are increasingly being developed for the nursing and care of older people and are intended to contribute to greater safety for older people in ...
Exploring the categories of students' interest and their relationships with deep learning in technology supported environments.
Scientific reports
Mar 26, 2025
Interest is not only the starting point to begin a wonderful learning journey for students, but also an important driver for deep learning and continuous progress. This study used latent profile analysis (LPA), multiple logistic regression analysis, ...
Select for better learning: identifying high-quality training data for a multimodal cyclic transformer.
Journal of neural engineering
Mar 25, 2025
. Tonic-clonic seizures (TCSs), which present a significant risk for sudden unexpected death in epilepsy, require accurate detection to enable effective long-term monitoring. Previous studies have demonstrated the advantages of multimodal seizure det...
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