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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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Multi-behavior-based graph contrastive learning recommendation
Graph-based collaborative filtering recommendations can more effectively explore the interaction information between users and items. However, its...
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Using multimodal learning analytics to model students’ learning behavior in animated programming classroom
Studies examining students’ learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge...
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Learning behavior feature fused deep learning network model for MOOC dropout prediction
Massive open online courses (MOOCs) have become one of the most popular ways of learning in recent years due to their flexibility and convenience....
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Dual-view co-contrastive learning for multi-behavior recommendation
Multi-behavior recommender systems (MBR) typically utilize multi-typed user interactive behaviors (e.g., purchase, click, view and add-to-cart) in...
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Dual-branch deep learning architecture enabling miner behavior recognition
Nonstandard miner behavior can have adverse effects on coal mine safety production. Therefore, accurately capturing miner behavior in complex...
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Hybrid analysis of the learner’s online behavior based on learning style
Since the covid pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major...
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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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Student behavior recognition based on multitask learning
The assessment of students’ classroom behavior is an important part of classroom teaching evaluation. However, teachers cannot timely, objectively...
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Click is not equal to purchase: multi-task reinforcement learning for multi-behavior recommendation
Reinforcement learning (RL) has achieved ideal performance in recommendation systems (RSs) by taking care of both immediate and future rewards from...
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Intra- and Inter-behavior Contrastive Learning for Multi-behavior Recommendation
Multi-behavior recommendation (MBR) aims to improve the prediction of target behavior by exploiting multi-typed auxiliary behaviors. However, most...
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Investigating behavior patterns of students during online self-directed learning through process mining
One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior...
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Exploring Opportunities to Identify Abnormal Behavior of Data Center Users Based on Machine Learning Models
AbstractThe article describes the main provisions of the proposed method of identifying abnormal behavior of data center users, which uses machine...
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A study of falling behavior recognition of the elderly based on deep learning
The current computer vision-based elderly falling behavior recognition algorithm mainly uses target detection followed by behavior recognition for a...
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Unraveling human social behavior motivations via inverse reinforcement learning-based link prediction
Link prediction aims to capture the evolution of network structure, especially in real social networks, which is conducive to friend recommendations,...
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Dropout prediction and decision feedback supported by multi temporal sequences of learning behavior in MOOCs
The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods,...
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A 4D strong spatio-temporal feature learning network for behavior recognition of point cloud sequences
Although the depth map sequence widely used in behavior recognition can provide depth information. However, depth pixels are not strongly correlated...
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Multi-behavior recommendation based on intent learning
Users often exhibit different intents when interacting with recommender systems, guiding their engagement across various behavior categories like...
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Driving behavior analysis and classification by vehicle OBD data using machine learning
The transportation industry’s focus on improving performance and reducing costs has driven the integration of IoT and machine learning technologies....
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From unsuccessful to successful learning: profiling behavior patterns and student clusters in Massive Open Online Courses
The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An...
