Behavioral Dynamics Analysis in Language Education: Generative State Transitions and Attention Mechanisms by Qi Zhang, Yiming Qian, Shumiao Gao, Yufei Liu, Xinyu Shen, Qing Jiang

“…This study proposes a novel approach for analyzing learning behaviors in Chinese language education by integrating generative attention mechanisms and generative state transition equations. …”
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Implementation strategies: lessons learned during an e-learning intervention to improve dietary behaviors and feeding practices in early childhood education and care by Henrik Lian, Nina Cecilie Øverby, Frøydis Nordgård Vik, Anine Christine Medin, Natalie Garzon Osorio, Christine Helle, Tormod Bjørkkjær, Penelope Love, Harry Rutter, Mary Elizabeth Barker, Elisabet Rudjord Hillesund, Sissel Heidi Helland

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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

“…By synthesizing findings from 32 studies, this review elucidates the available AI-based techniques to analyze tactical behavior and identify the collective dynamic based on artificial neural networks, deep learning, machine learning, and time-series techniques. …”
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CLASSIFYING ANDROID MALWARE CATEGORIES BASED ON DYNAMIC FEATURES: AN INTEGRATION OF FEATURE REDUCTION AND SELECTION TECHNIQUES by abdullah alsraratee, Ahmed Al-Azawei

“…This study utilizes machine learning techniques namely, K-Nearest Neighbor, Random Forest and Decision Tree to classify Android malware based on dynamic analysis. …”
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Molecular dynamics and machine learning study of tensile behavior in single-crystal tungsten containing He bubbles by Pan-dong Lin, Yan Lin, Hong-guang Li, Shu-gang Cui, Jun-feng Nie, Bai-wen Zhong, Yu-peng Lu

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Artificial Intelligence (AI) in Education: A Case Study on ChatGPT’s Influence on Student Learning Behaviors by Thuy Nhu Thi Nguyen , Nam Van Lai , Quyet Thi Nguyen

“…The integration of ChatGPT at Ho Chi Minh City University of Technology and Education (HCMUTE) aims to transform teaching and learning dynamics. …”
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University Students’ Autonomous Learning Behaviors in Three Different Modes of ICT-Based Instruction in the COVID-19 Era: A Case Study of Lockdown Learning by Mátyás Bánhegyi, Balázs Fajt

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Coordinate Representations for Interference Reduction in Motor Learning. by Sang-Hoon Yeo, Daniel M Wolpert, David W Franklin

“…However, any difference in the limb's endpoint location typically changes the hand position, joint angles and the hand orientation making it ambiguous as to which of these changes underlies the ability to learn dynamics that normally interfere. Here we examine the extent to which each of these three possible coordinate systems--Cartesian hand position, shoulder and elbow joint angles, or hand orientation--underlies the reduction in interference. …”
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Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks by Zhe Bai, Xishuo Wei, William Tang, Leonid Oliker, Zhihong Lin, Samuel Williams

“…Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. …”
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Modeling eating behaviors: The role of environment and positive food association learning via a Ratatouille effect by Anarina L. Murillo, Muntaser Safan, Carlos Castillo-Chavez, Elizabeth D. Capaldi Phillips, Devina Wadhera

“…Eating behaviors among a large population of children are studied as a dynamic process driven by nonlinear interactions in the sociocultural school environment. …”
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APPLICATION OF MACHINE LEARNING IN BEHAVIORAL MODIFICATION by Sudeep Varshney, Aditi Chandra, Pushpendra Kumar Rajput, Sunil Kumar, Gunjan Varshney

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Analyzing the practice of medical humanistic care based on a social learning model: mapping the trajectory of the learning dynamic process from the learner’s perspective by Bilu Gu, Yiming Lv, Jiyu Zhu, Xiaoling Sun, Xiaoling Sun, Kun Li

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Concurrent Contribution of Co-Contraction to Error Reduction During Dynamic Adaptation of the Wrist by Andria J Farrens, Kristin Schmidt, Hannah Cohen, Fabrizio Sergi

“…MRI-compatible robots provide a means of studying brain function involved in complex sensorimotor learning processes, such as adaptation. To properly interpret the neural correlates of behavior measured using MRI-compatible robots, it is critical to validate the measurements of motor performance obtained via such devices. …”
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Personalized learning path optimization based on enhanced deep neural network: higher education teaching model integrating learner behavior and cognitive style by Xiaomei Ding, Huaibao Ding, Fei Zhou, Lihong Zhao

“…The model adopts the Actor-Critic framework to introduce a multilayer perceptron (MLP) in the Actor part to fuse behavioral data and cognitive style, and a long short-term memory (LSTM) neural network in the Critic part to process time series data, thereby realizing the selection and dynamic adjustment of personalized learning paths. …”
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Enhancing action recognition in educational settings through exercise-induced neuroplasticity by Xu Yuan, Han Li, ShuangYi Feng, MingYang Sun

“…To bridge this gap, we propose a novel approach that integrates neuroplastic principles into action recognition for educational applications. Existing models primarily rely on behavioral metrics, neglecting the underlying neural mechanisms that drive skill acquisition.MethodsOur method introduces a Neuroplastic Learning Dynamics Model (NLDM), a computational framework designed to simulate the synaptic modifications, cortical reorganization, and learning-induced connectivity changes that occur during educational engagement. …”
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Analyzing the learning behavior patterns of business english learners using deep learning technology by Xiaohui Zeng

“…This study employs deep learning technology to conduct a comprehensive analysis and prediction of learning behavior patterns among business English learners, making several innovative contributions. …”
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Randomized controlled trial protocol on enhancing students’ togetherness, relatedness, and interactions for learning in physical education: the TRI-PE project by Rubén Llanos-Muñoz, Javier Sevil-Serrano, David Lobo-Triviño, Miguel A. López-Gajardo, Francisco M. Leo

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Impact of Learner Behavior on Academic Performance by Rudzani Israel LUMADI

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Enhancing Mobile App Recommendations With Crowdsourced Educational Data Using Machine Learning and Deep Learning by Naadiya Mirbahar, Kamlesh Kumar, Asif Ali Laghari

“…In the rapidly evolving digital landscape, personalized recommendations have become essential for enhancing user experience. Machine learning models analyze user behavior patterns to suggest relevant entertainment, education, or e-commerce content. …”
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Multimodal deep learning for art behavior analysis and personalized teaching path generation by Yikun Li, Jie Shi

“…Personalized teaching paths generated based on EPG can dynamically adjust according to learners’ real-time capability profiles and learning progress, improving learning efficiency by 42.6%. …”
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