ICCE2025 Subconference on

This sub-conference will be dedicated to exploring the frontiers of educational technology and its infrastructure. It aims to foster dialogue on the development of standards for system, resource, and data interoperability, and to inspire the creation of innovative learning technologies. The sub-conference will focus on advanced learning technologies that are reshaping the educational landscape through personalized learning experiences, adaptive content delivery, and Generative AIs. The role of Large Language Models (LLMs) in educational content generation, personalized tutoring, and AI-driven feedback mechanisms will be explored. Automated assessment will also be a key focus, along with Human-Computer Interaction and collaborative learning that enable more intuitive learning experiences.

It will also extend to Analytics in Teaching & Learning, examining how multimodal and AI-enhanced data-driven insights can optimize learning outcomes and enhance pedagogical strategies. Alongside these, it will delve into ethics and transparency in learning analytics, ensuring that these technologies are leveraged in a way that promotes fair, inclusive, and responsible educational practices. Discussions on privacy-preserving learning analytics, explainable AI in education, and regulatory frameworks for AI-driven decision-making will also be included.

The sub-conference will also highlight the pivotal role of Platforms & Infrastructure in supporting these technological advances. Central to this discussion will be the impact of learning platforms, which serve as intelligent, scalable, and adaptive learning processes that facilitate diverse types of interaction and feedback mechanisms to be more accessible, engaging, and tailored to individual learners. Examples of emerging platforms that will be discussed include cloud technology, ubiquitous learning, and virtual labs. We also encourage submissions related to metaverse-based education, AI-driven classroom orchestration, and real-time adaptive feedback systems. We welcome research that applies these technologies across diverse learning environments, including traditional classrooms, narrative-centered learning, embodied learning, game-based learning, online education, and adult learning contexts such as simulated training environments and healthcare education.

Scope of the Conference

Advanced Learning Technologies

• Adaptive learning systems

• Affective computing for learning

• Immersive learning environments

• Large Language Models (LLMs) and AI-driven educational tools

• Generative AIs in education

• Automated evaluation

• Collaborative learning

• Human-Computer Interaction

• Interactive multimedia

• Intelligent questioning systems

• Educational recommender systems

• AI-powered personalized learning frameworks

• Semantic Web in education

• Smart educational environments

• The Internet of Things in education
  

Analytics in Teaching & Learning Data 

• Data Literacy and Learning Analytics

• Game-based Learning Analytics

• Innovative learning analytics systems

• Analytics algorithm advancements

• Expansive data collection

• Pedagogical models and analytics

• Predictive models, analysis, and visualization

• Ethical frameworks in learning analytics

• Bias, Equity, Fairness, and Transparency in Learning Analytics

• Privacy-preserving learning analytics and data security

• Explainable AI and its role in education

• Multimodal learning analytics

• Social network analysis

• Sequential data mining
  

Platforms & Infrastructure

• Cloud-enhanced education

• Credentialing evolution

• Strategic implementation of advanced learning technologies

• Learning system architectural foundations

• Learning design interfaces

• Classroom orchestration tools

• Metaverse-based learning platforms and immersive VR/AR education

• Real-time adaptive feedback mechanisms

• Life cycle management of technical learning objects

• Ubiquitous learning technologies

• Intuitive Web interfaces

• Open educational ecosystems

• Virtual Laboratories

• Performance Support Tools (PSTs)

• Repository technologies

• Interoperability frameworks for multimodal educational data

• AI-driven simulation-based training for professional education

• Multimodal learning analytics in workforce development

• XR-based professional training (e.g., VR for medical simulations, AR for industrial training)

• Technology standards