Call for Papers


Topics are interested but not limited to:

  • Generative AI and Large Language Models (LLMs)
  • Lightweight and Domain-Specific AI Models
  • Retrieval-Augmented Generation (RAG) and Knowledge-Enhanced AI
  • Explainable, Trustworthy, and Responsible AI
  • AI Hallucination Detection and Content Verification
  • Federated Learning and Privacy-Preserving AI
  • AI-Generated Content for Education and Research
  • AI-Assisted Programming and Intelligent Software Development
  • Neuromorphic Computing and Emerging Computing Architectures
  • AI-Driven Optimization and Intelligent Computing Systems

  • Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) for
  • Education
  • Immersive and Multisensory Learning Environments
  • Human-AI Interaction and Collaborative Intelligence
  • Brain-Computer Interfaces and Neuroadaptive Learning
  • Digital Twins and Virtual Laboratories
  • 3D Reconstruction and Interactive Visualization
  • Intelligent Robotics and Educational Robotics
  • Internet of Things (IoT) and Smart Learning Environments
  • Generative AI for Interactive and Immersive Experiences

  • AI-Enabled Information Systems and Digital Platforms
  • Edge-Cloud Computing and Intelligent Service Architectures
  • Next-Generation Networks for Digital Learning
  • Semantic Communication and Intelligent Networking
  • Cloud Computing for Education and Research
  • Microservices and Distributed Computing Systems
  • Open-Source Technologies and Digital Ecosystems
  • Intelligent Automation and Robotics-as-a-Service
  • Digital Transformation of Information and Education Systems
  • AI-Powered Teaching and Learning Systems
  • Intelligent Tutoring Systems and AI Learning Assistants
  • Personalized and Adaptive Learning Technologies
  • Automated Assessment and Intelligent Feedback
  • Generative AI in Teaching, Learning, and Curriculum Design
  • AI Literacy and Digital Competency Development
  • Online, Blended, and Hybrid Learning
  • Virtual Laboratories and Remote Experiments
  • Learning Design and Technology-Enhanced Pedagogy
  • AI-Enhanced STEM and Engineering Education
  • Digital Transformation in Higher Education
  • Educational Innovation, Accessibility, and Inclusive Learning
  • Human-AI Collaboration and the Future of Education
  • Academic Integrity, AI Ethics, and Responsible AI in Education



  • Learning Analytics and Educational Data Mining
  • Multimodal Learning Analytics and Behavioral Analysis
  • AI-Driven Learning Assessment and Performance Prediction
  • Early Identification of Learning Difficulties and Personalized Intervention
  • Knowledge Graphs and Intelligent Knowledge Management
  • Multimodal Information Retrieval and Semantic Search
  • Big Data Analytics for Education and Research
  • Data-Driven Decision-Making in Education
  • Privacy-Preserving Data Analytics
  • Blockchain and Digital Credentials for Academic Integrity
  • Synthetic Data Generation and Data Quality Assessment
  • Information Credibility, Misinformation Detection, and Digital Trust