Aspects of intelligent learning systems

Aim and Topics

In addition to e-learning using Learning Management System (LMS), intelligent and adaptive learning systems including next-generation digital learning environments have been applied to a variety of educational fields. Furthermore, artificial intelligence (AI) is considered to be the key technology for solving educational problems and smoothen teaching and learning. Online learning using such systems has the potential to realize optimized learning for learners regardless of time and distance.

This invited session focuses on various aspects of the intelligent and adaptive learning systems, including how various learning systems interact with learners/educators in capturing rich interaction data, pre-process and analyzing them using cutting-edge analytical methods such as knowledge discovery, natural language processing (NLP), data mining, deep learning, AI, etc. for changing the dynamics of physical and social environments. This invited session explores intelligent and affective aspects such as knowledge representation, automatic feedback generation, AI bias in learning systems, multimedia annotation, innovativeness in e-learning, etc. to design new tools that could solve complex social and educational problems.

Specific topics of interest include but not limited to:

• Intelligent and adaptive learning systems
• Technology enhanced learning and its theoretical foundation
• Course management in online and virtual learning
• Usage of Learning Management System (LMS) for teaching and learning practices
• AI in education
• Applications of Generative AI (such as ChatGPT, Midjourney) in Education
• Practice in specific educational contexts (such as language learning, STEAM, and disaster prevention) using ICT
• Learning analytics and evidence-based education
• Usage, security, ethics, and privacy policy of educational data
• Development of educational tools
• Curriculum and instructional design
• Gamification and gamified learning environments
• Adaptive support for learning, models of learners, diagnosis, and feedback
• Modeling of motivation, metacognition, and affective aspects of learning
• Recommendation systems
• Complex system architecture
• Adaptation of AR/VR/XR in reshaping education
• Intelligent interfaces
• Models and techniques for educational data mining
• Embodied learning for wellbeing in education

Submission

KES2025 Invited Sessions Submission