7th International Conference on Artificial Intelligence in Education Technology (AIET 2026)

The 7th International Conference on Artificial Intelligence in Education Technology (AIET 2026) gathers experts, engineers, and researchers to explore and advance the integration of artificial intelligence in education technology.

Key Topics

• Inequity and inequality in education
  • S rights and responsibilities, data collection, management and dissemination
  • Socio-economic, gender, and racial issues. Intelligent techniques to support disadvantaged schools and students. Ethics in educational research: sponsorship, scientific validity, participant&rsquo
• Learning Contexts and Informal Learning
  • Collaborative and group learning
  • Educational games and gamification
  • Inquiry learning
  • Social networks
  • Communities of practice
  • Social dimensions of learning
  • Learning through construction and making
  • Ubiquitous learning environments
  • Lifelong, museum, out-of-school, and workplace learning
  • Learning grid
• Online and distance learning
  • Remote learning in k-12 schools
  • Massive open online courses
  • Mobile learning
  • Synchronous and asynchronous learning
  • Active learning in virtual settings
• Design, use, and evaluation of human-AI hybrid systems for learning
  • Systems and approaches in which educational stakeholders and AI tools build upon each other&rsquo
  • Research that explores the potential of human-AI interaction in educational contexts
  • S complementary strengths to achieve educational outcomes and/or improve mutually
• Innovative Applications
  • Scaling up and large-scale deployment of AI education systems
  • Domain-specific learning applications (e.g. language, science, engineering, mathematics, medicine, military, industry)
• Evaluation in the Context of Education Technologies
  • Design and formative studies of AI education systems
  • Studies on human learning, cognition, affect, motivation, and attitudes
  • Evaluation techniques relying on computational analyses
• Intelligent Techniques to Support Disadvantaged Schools and Students, Inequity and Inequality in Education
  • Socio-economic, gender, and racial issues. Ethics in educational research: sponsorship, scientific validity, participant`s rights and responsibilities, data collection, management and dissemination
• Intelligent and Interactive Technologies in an Educational Context
  • Data mining and machine learning
  • Natural language processing and speech technologies
  • Semantic web technologies
  • Knowledge representation and reasoning
  • Tangible interfaces, wearables and augmented reality
  • Multi-agent architectures
• Modelling and Representation
  • Facilitators, tasks and problem-solving processes
  • Models of learners, including open learner models
  • Modelling motivation, metacognition, and affective aspects of learning
  • Models of groups and communities for learning
  • Computational thinking and model-building
  • Ontological modelling
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  • Representing and analyzing activity flow and discourse during learning
• Learning Contexts and Informal Learning
  • Collaborative and group learning
  • Educational games and gamification
  • Inquiry learning
  • Social networks
  • Communities of practice
  • Social dimensions of learning
  • Learning through construction and making
  • Ubiquitous learning environments
  • Lifelong, museum, out-of-school, and workplace learning
  • Learning grid
• Models of Teaching and Learning
  • Motivational diagnosis and feedback
  • Intelligent tutoring and scaffolding
  • Agents that promote metacognition, motivation and affect
  • Interactive pedagogical agents and learning companions
  • Adaptive question-answering and dialogue, Educational data mining, Learning analytics and teaching support, Learning with simulations