2nd Asia-Pacific Intelligent Educational Technologies Conference (APIET 2027)

The 2nd Asia-Pacific Intelligent Educational Technologies Conference (APIET 2027) is a conference that explores artificial intelligence in education, learning analytics, collaborative learning, and adaptive learning systems.

Key topics

• Artificial intelligence in education
  • Intelligent tutoring systems
  • Natural Language Processing (NLP) in education
  • Educational data mining and learning analytics
  • Machine learning in education
  • Intelligent agents and virtual assistants
  • Affective computing and emotion analysis
  • Automated assessment and feedback
  • Computer vision in education
  • AI for special education
  • AI in curriculum design and content generation
  • AI for teacher support
• Adaptive learning systems
  • Intelligent tutoring systems (ITS)
  • Learner modeling and profiling
  • Adaptive content delivery
  • Learning analytics in adaptive systems
  • Gamification and adaptive learning
  • Adaptive assessment and feedback
  • Adaptive learning and artificial intelligence
  • Emotion-aware adaptive systems
  • Evaluation and effectiveness of adaptive learning systems
  • Cross-domain adaptive learning
  • Adaptive learning in STEM education
• Collaborative learning and social networks
  • Collaborative learning environments
  • Social Network Analysis (SNA) in education
  • Computer-Supported Collaborative Learning (CSCL)
  • Peer learning and peer assessment
  • Community of practice and learning communities
  • Collaborative knowledge construction
  • Social media in education
  • Group dynamics and teamwork in learning
  • Collaborative learning analytics
  • Gamification and collaborative learning
  • Collaborative learning in MOOCs and online education
  • Collaborative learning in STEM and beyond
• Learning analytics and educational data mining
  • Predictive analytics in education
  • Personalized learning and recommendations
  • Temporal analysis of learning data
  • Assessment and feedback analytics
  • Data-driven curriculum design
  • Learning process mining
  • Multimodal learning analytics
  • Learning analytics for teachers and instructors
  • Gamification and learning analytics
  • Learning analytics in MOOCs and online education
  • Visualization of learning data
  • AI-driven educational data mining
  • Learning analytics for equity and inclusion

Who should attend