With the rapid advancement of artificial intelligence, particularly Generative AI, Large Language Models (LLMs), intelligent agents, and multimodal learning technologies, education is undergoing significant transformation. EAIAT focuses on the development, application, and evaluation of intelligent technologies in education, covering both fundamental AI techniques and their innovative applications in teaching, learning, assessment, and educational management.
The conference welcomes original research contributions, practical applications, experimental studies, and technological innovations in, but not limited to, the following topics:
Topics of interest for submission include, but are not limited to:
Track 1: Artificial Intelligence and Machine Learning in Education
Artificial Intelligence Applications in Education
Machine Learning and Deep Learning for Educational Applications
Generative Artificial Intelligence in Teaching and Learning
Large Language Models (LLMs) and Foundation Models in Education
Agentic AI and Multi-Agent Systems for Education
Natural Language Processing for Educational Applications
Computer Vision and Pattern Recognition in Education
Knowledge Representation and Knowledge Graphs for Education
Intelligent Decision Support Systems for Education
Explainable and Trustworthy AI in Educational Applications
Track 2: Intelligent Tutoring Systems (ITS)
AI-Powered Personalized Learning Systems
Adaptive and Intelligent Learning Systems and Adaptive Education
Smart Learning Environments
Intelligent Learning Platforms and Applications
AI-Based Learning Recommendation Systems
Student Modeling and Knowledge Tracing
AI-Assisted Learning Content Generation
Conversational AI and Educational Chatbots
Virtual Teaching Assistants and Intelligent Learning Agents
Collaborative and Social Learning Technologies
Self-Regulated and Self-Adaptive Learning Systems
AI-Driven Learning Path Optimization
Track 3: Educational Data Mining and Learning Analytics
Educational Data Mining and Big Data Analytics
AI-Driven Learning Analytics
Predictive Analytics for Student Performance
Student Behavior Modeling and Analysis
Multimodal Learning Analytics
Educational Data Visualization and Interpretation
Academic Performance Prediction
AI-Based Student Engagement and Motivation Analysis
Learning Process Monitoring and Evaluation
Educational Data Management and Processing
Intelligent Decision-Making in Educational Management
Data-Driven Educational Quality Assessment
Track 4: 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
AI-Supported Examination and Assessment Systems
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 with AI
AI-Enhanced Educational Management and Administration
Innovative Teaching Models and
Pedagogical Technologies
Track 5: Emerging Technologies and Intelligent Educational Environments
Virtual Reality (VR) and Augmented Reality (AR) in Education
Extended Reality (XR) and Immersive Learning Environments
Metaverse and Digital Twin Technologies for Education
Multimodal Human-Computer Interaction in Learning
Internet of Things (IoT) and Smart Classroom Technologies
Edge Computing and Cloud Computing for Education
Robotics and Intelligent Robotic Education
Educational Simulation and Serious Games
Intelligent Multimedia Learning Systems
Mobile and Ubiquitous Learning Technologies
Blockchain and Digital Credentials in Education
Wearable Technologies for Smart
Learning
Track 6: Responsible AI, Educational Ethics, and Digital Inclusion
Responsible and Ethical AI in Education
Privacy Protection and Data Security in Educational AI
Fairness, Transparency, and Accountability of AI Systems
Explainable AI and Trustworthy Educational Technologies
AI Governance and Policy for Education
Academic Integrity in the Age of Generative AI
AI-Generated Content Detection and Verification
Bias Detection and Mitigation in Educational AI
Digital Accessibility and Inclusive Learning Technologies
AI Literacy and Digital Competency Development
Educational Technology for Diverse and Underserved Learners
Sustainable and Human-Centered AI in
Education
Track 7: 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