ICET 2024 is the scientific
conference addressing the
real topics as seen by
teachers, students, parents
and school leaders. Both
scientists, professionals
and institutional leaders
are invited to be informed
by experts, sharpen the
understanding what education
needs and how to achieve it.
The topics include but not
limited to below:
Data-Informed Learning
Theories
Learning and Teaching
Processing Mining
Emotional Learning Analysis
Learner Engagement and
Involvement Quantification
and Analysis
Learning Early Warning and
Learning Intervention
Design and Adoption of
Learning Analytics Tools
Adaptive Learning Decision
Support and Feedback
Multivariate and Multimodal
Learning Assessment
Data-Driven Performance
Prediction
Discourse analysis in
Interactive Learning
Environments
Collaborative Learning
Analytics
Social and Epistemic Network
Analysis
Ethical Issues in Learning
Analytics
Chair: Assoc. Prof. Dr. Jianwei Li, Beijing University of Posts and Telecommunications, China
Modelling and Representation
of individual and group
learning
AI and the Future of
Learning
Wearable and Undisturbed
Learning Sensing
Technologies
Affective Computing in
Education
Generative AI in Education
AI-enabled Personalization
Learning
Learning Content
Recommendation
Intelligent Learning
Environments
Human-AI Hybrid Systems for
Learning
Intelligent Agent
(Assistants)
Intelligent Tutoring Systems
Educational Process
Visualization and Dashboard
AI-driven Transformation of
Learning/Curriculum
AI Ethical, Privacy and
Security Challenges in
Education
Chair: Senior Lecturer Dr. Qingqing Xing, The Hong Kong University of Science and Technology (Guangzhou), China
Designing Interactive
Virtual Reality (VR)
Simulations for Science
Education
Integrating Gamification
Elements into Online/Offline
Course Design
Utilizing Learning Analytics
to Inform Instructional
Design Decisions
Video Conferencing in
Learning
Social Media Integration in
Instruction
Digital Resources and Tools
for Instruction
Interactive Simulations for
Concept Teaching in STEM
Education
Automated Grading Systems:
Benefits, Challenges, and
Best Practices
Personalizing Feedback to
Support Student Learning
Technology-Enhanced
Classroom Management
Strategies
Digital Attendance Tracking
and Student Progress
Monitoring
Innovations in Technology
Integration for Instruction
Interactive Whiteboards and
Multimedia Presentations
Flipped Classroom Models
Integrating Robotics and
Coding in STEM Instruction
Identifying At-Risk Students
and Tailoring Support
Interventions
Evidence-Based Instructional
Decision Making
Chair: Prof. Hang Hu, Southwest University, China
Multisensing Devices Driven
Cognitive Neuroscience
Behavioral, Physiological
and Psychological Multilayer
Computation
Bahavioral, Cognitive,
Emotional Mechanisms in
Interactive Learning
Enviroments
Cognitive and Neuroscience
Inspired Artificial
Intelligence
Brain-Like Artificial
Intelligence
Brain-Computer Interfaces in
Education
Computational Educational
Neuroscience
Mind, Brain and Educational
Computing
Brain Cognitive Mechanisms
in Multimedia Learning
Cognitive Computing in Human
Languages
Neuroimaging for Leaner
Cognitive and Emotional
Modeling
Cognitive Psychology and
Learning Science in Big Data
Chair: Prof. Lau Bee Theng,
Swinburne University of
Technology Sarawak, Malaysia
Causal Inference Techniques
in Education
Empirical Research on
Artificial Intelligence
Methods and Education
Data Modeling and
Demonstration in Social and
Behavioral Sciences
Analysis and
Mediating/Moderating Effects
in Technology-enhanced
Education
Brain Scientific Methods and
Their Applications in
Educational Research
Methods and Techniques of
Educational Empirical Data
Collection
Application and Reflection
of Structural Equation Model
In Education
Application and Reflection
of Large Language Models In
Education
Data Mining and Learning
Analytics In Educational
Research
Application and Reflection
of Grounded Theory in
Educational Technology
Research
Trends and Prospects in The
Research of Educational
Quality
Application and Reflection
of Computationalism Research
Methodology in Education
Methodological Innovation of
Educational Empirical
Research in Big Data
Multimodal Learning
Analytics in Multi-Context
Learning Situations
Chair: Prof. Jingying Chen, Central China Normal University, China
AI-based Assistive
Technology for Special
Children
AI-Powered Intervention
Technology for Children with
ASD
Intelligent Behavior Sensing
for Special Children
AI-Assisted Assessment of
Children with ASD
Brain Source Reconstruction
for Mental Disorders
EEG Analysis for Special
Children
Intelligent Screening for
Children with ASD
Personalized Learning
Techniques for Special
Children
Human-Computer Interaction
Technology for Special
Education
Student Support Technology
for Special Children
Intelligent Tutoring Systems
for Special Education