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Effectiveness of AI-assisted game-based learning on science learning outcomes, intrinsic motivation, cognitive load, and learning behavior
This study aimed to investigate the effectiveness of using AI-assisted game-based learning on science learning outcomes, intrinsic motivation,...
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Comparative Analysis of Machine Learning, Ensemble Learning and Deep Learning Classifiers for Parkinson’s Disease Detection
A progressive neurodegenerative ailment called Parkinson's disease (PD) is marked by the death of dopamine-producing cells in the substantia nigra...
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The effects of self-efficacy, academic stress, and learning behaviors on self-regulated learning in blended learning among middle school students
Self-regulated learning ability is an important determinant of the effectiveness of blended learning. However, little research has been done on...
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The impacts of the comprehensive learning analytics approach on learning performance in online collaborative learning
Online collaborative learning has been an effective pedagogy in the field of education. However, productive collaborative learning cannot occur...
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Active Learning and Transfer Learning for Document Segmentation
AbstractIn this paper, we investigate the effectiveness of classical approaches to active learning in the problem of document segmentation with the...
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Optimizing learning return on investment: Identifying learning strategies based on user behavior characteristic in language learning applications
Began with Computer-Assisted Language Learning (CALL) in the 1960s and extended to the widespread use of various Mobile-Assisted Language Learning...
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The effects of students’ self-efficacy, self-regulated learning strategy, perceived and actual learning effectiveness: A digital game-based learning system
Self-regulated learning (SRL) strategies have been identified as a valuable component of digital game-based learning system (GBLS) activities....
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Towards Task Sampler Learning for Meta-Learning
Meta-learning aims to learn general knowledge with diverse training tasks conducted from limited data, and then transfer it to new tasks. It is...
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MAC: a meta-learning approach for feature learning and recombination
Optimization-based meta-learning aims to learn a meta-initialization that can adapt quickly a new unseen task within a few gradient updates. Model...
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Promoting math learning in educational games with virtual companions providing learning supports
To enhance the effectiveness of educational games, researchers have advocated adding learning supports in educational games, but this may come at the...
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Model gradient: unified model and policy learning in model-based reinforcement learning
Model-based reinforcement learning is a promising direction to improve the sample efficiency of reinforcement learning with learning a model of the...
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One improved learning analytics of interest transfer in interactive learning activities
Mining interactive learning activities and exploring learners' interest transfer are the key issues to realize education optimization and learning...
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Redirected transfer learning for robust multi-layer subspace learning
Unsupervised transfer learning methods usually exploit the labeled source data to learn a classifier for unlabeled target data with a different but...
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CNN-Transformer: A deep learning method for automatically identifying learning engagement
Learning engagement is an essential indication to define students' learning pacification in the class, and its automated identification technique is...
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Research trends in deep learning and machine learning for cloud computing security
Deep learning and machine learning show effectiveness in identifying and addressing cloud security threats. Despite the large number of articles...
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Identifying learning styles in MOOCs environment through machine learning predictive modeling
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid...
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Machine learning and human learning: a socio-cultural and -material perspective on their relationship and the implications for researching working and learning
The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new...
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Inferring source of learning by chimpanzees in cognitive tasks using reinforcement learning theory
Reinforcement learning is a mathematical framework for learning better choices through trial-and-error. Recent studies revealed that reinforcement...
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Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox
With the breakthrough of AlphaGo, deep reinforcement learning has become a recognized technique for solving sequential decision-making problems....
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Online teaching model in the context of blended learning environment: Experiential learning and TAM
Along with the development of the Internet and the new generation of ICT, blended learning (BL), online learning, and experiential learning (EL) are...
