A machine learning enabled affective E-learning system model

Keyphrases

• Machine Learning 100%
• E-learning System 100%
• Learning System Model 100%
• K-nearest 50%
• Emotional State 50%
• Student Satisfaction 50%
• Ningbo China 25%
• University of Nottingham 25%
• Pollution 25%
• Computer Science 25%
• Convenience Sampling 25%
• Positive Emotions 25%
• Student Learning 25%
• Undergraduate Students 25%
• Learning English 25%
• Learning Results 25%
• System Performance 25%
• Electroencephalogram 25%
• Student Engagement 25%
• T-test 25%
• Supervised Machine Learning 25%
• Sampling Methods 25%
• Reinforcement Learning Approach 25%
• Learning Content 25%
• Brain Waves 25%
• Emotional Status 25%
• English Listening Skills 25%
• Content Personalization 25%
• English Reading Comprehension 25%
• Student Emotions 25%

Computer Science

• Machine Learning 100%
• e-learning 100%
• Learning Systems 100%
• e-learning Systems 100%
• Emotional State 66%
• Computer Science 33%
• Machine Learning Algorithm 33%
• Learning Approach 33%
• Learning Result 33%
• Systems Performance 33%
• Learning Resource 33%
• Student Engagement 33%
• Reinforcement Learning 33%
• Emotional Status 33%
• Convenience Sampling 33%
• Undergraduate Student 33%

Chemical Engineering

• Learning System 100%
• Reinforcement Learning 14%