8th International Conference on Education and Artificial Intelligence Technologies (EAIT 2027), 24-26 Sep 2027

The 8th International Conference on Education and Artificial Intelligence Technologies (EAIT 2027) explores applications of artificial intelligence and machine learning in education, intelligent tutoring systems, learning analytics, AI-enhanced teaching and assessment, emerging educational technologies, responsible AI, and personalized lifelong learning.

Key Topics

Artificial intelligence and machine learning in education
- AI applications in teaching and learning
- Machine learning and deep learning for educational applications
- Generative AI and large language models (LLMs) in education
- Foundation models and agentic AI in educational environments
- Natural language processing and computer vision
- Knowledge representation and educational knowledge graphs
- Intelligent decision support systems
- Explainable and trustworthy AI applications
Intelligent tutoring systems and personalized learning
- AI-powered personalized and adaptive learning systems
- Intelligent learning platforms and smart learning environments
- AI-based learning recommendations and path optimization
- Student modeling and knowledge tracing
- AI-assisted learning content generation
- Conversational AI, educational chatbots, and virtual teaching assistants
- Collaborative and social learning technologies
- Self-regulated and self-adaptive learning systems
Educational data mining and learning analytics
- Educational data mining and big data analytics
- AI-driven learning analytics and predictive modeling
- Student performance prediction and behavior analysis
- Multimodal learning analytics
- Student engagement and motivation analysis
- Educational data visualization and interpretation
- Learning process monitoring and evaluation
- Data-driven educational quality assessment
- Intelligent decision-making in educational management
AI-enhanced teaching, assessment, and educational innovation
- AI-assisted teaching and instructional design
- AI-enhanced curriculum development
- Automated assessment and intelligent grading
- AI-powered feedback and evaluation systems
- Generative AI for educational resource development
- Human-AI collaboration in teaching and learning
- AI applications in STEM and STEAM education
- AI-assisted programming and computing education
- Project-based and inquiry-based learning
- Educational management and innovative teaching models
Emerging technologies and intelligent educational environments
- Virtual reality (VR), augmented reality (AR), and extended reality (XR)
- Immersive learning environments and educational metaverse
- Digital twins and educational simulation
- Internet of Things (IoT) and smart classroom technologies
- Edge computing and cloud computing for education
- Robotics and intelligent robotic education
- Educational games and intelligent multimedia learning systems
- Mobile and ubiquitous learning technologies
- Blockchain and digital credentials
- Wearable technologies for smart learning
Responsible AI, educational ethics, and digital inclusion
- Responsible and ethical AI in education
- Privacy protection and data security
- AI fairness, transparency, and accountability
- Explainable AI and trustworthy educational technologies
- AI governance and educational policies
- Academic integrity and AI-generated content verification
- Bias detection and mitigation
- Digital accessibility and inclusive learning
- AI literacy and digital competency development
- Human-centered and sustainable AI in education
AI applications in professional education and lifelong learning
- AI in higher education and university teaching
- AI applications in K-12 education
- AI-enhanced vocational and technical education
- Intelligent corporate training and workplace learning
- AI for professional skills development
- Personalized lifelong learning systems
- AI-supported language learning and translation
- Intelligent assessment for professional certification
- AI in distance, online, and blended learning
- Digital transformation of educational institutions
- AI-driven career guidance and talent development
- AI technologies for interdisciplinary and cross-cultural education

Who should attend

Educators and teaching professionals
Academic researchers in artificial intelligence and education
Educational technology researchers and developers
Professionals involved in intelligent tutoring and personalized learning systems
Researchers in educational data mining and learning analytics
Specialists in AI-assisted teaching and assessment
Educational technology and platform developers
Professionals in vocational, technical, and higher education
Researchers in responsible AI and educational ethics
Experts in digital learning and educational innovation