Artificial Intelligence in Education
Exploring how AI transforms personalized learning, intelligent feedback, adaptive assessment, and data-driven decision-making in education
Track Introduction
Artificial Intelligence (AI) is rapidly transforming the landscape of education by enabling personalized learning experiences, intelligent feedback, adaptive assessment, and data-driven decision-making. This track provides a platform for researchers, educators, and practitioners to discuss the latest advances in AI-powered educational technologies and their impact on teaching and learning.
Topics of interest include, but are not limited to, adaptive educational systems, intelligent tutoring systems, pedagogical agents, machine learning applications in education, learning analytics and educational data mining, natural language processing for learning support, AI-enhanced assessment, agent-based learning environments, and emerging architectures for AI-enabled educational ecosystems.
We welcome theoretical, empirical, and practical contributions that explore how AI can improve learning effectiveness, accessibility, engagement, and educational innovation across diverse contexts.
THE TOPICS INCLUDED BUT NOT LIMITED TO THE FOLLOWING
Generative AI & LLMs in Education
AI-Powered Adaptive Learning
Intelligent Tutoring Systems
AI Agents in Learning Environments
Machine Learning for Education
Learning Analytics & Data Mining
NLP for Education
Intelligent Educational Systems
AI-Driven Assessment & Feedback
AI-Enhanced Pedagogy
Track Chairs
Dr. Dongkun Han
The Chinese University of Hong Kong, Hong Kong, China
Dr. Dongkun Han is a Senior Lecturer in the Department of Mechanical and Automation Engineering at The Chinese University of Hong Kong. He earned his Ph.D. from The University of Hong Kong and held research and visiting appointments at the Technical University of Munich, the University of Michigan, Stanford University, and the German Institute of Science and Technology in Singapore.
His interdisciplinary scholarship advances AI-enhanced mathematics and general education, e-learning, experiential robotics education, and professional development for engineering educators. He co-founded the CUHK Smart Garden and has earned CUHK's University Education Award, the Vice-Chancellor's Exemplary Teaching Award, and multiple Faculty and General Education teaching awards.
Assoc. Prof. John Paul P. Miranda
Pampanga State University, Philippines
Dr. John Paul P. Miranda is an Associate Professor V at Pampanga State University, Philippines, where he also serves as Center Manager for Global Reputation and Sustainability. At the university's Mexico Campus, he concurrently serves as Program Head of the Bachelor of Science in Information Technology and Coordinator for Accreditation and Institutional Assessment.
His research focuses on AI in education, educational data mining, data analytics, machine learning, technology adoption, and human–computer interaction. He has authored over 100 Scopus-indexed publications and holds editorial and peer-review roles for international academic journals. His university recognized him as Most Outstanding Researcher in 2020, 2023, and 2024.
Submit Your Paper to Track 5
The manuscript should be submitted via the Electronic Submission System or by email to eset.conference@outlook.com
no later than the submission deadline of Oct. 25, 2026. When submitting, please select Track 5 as the designated track.