The workshop brings together researchers and practitioners from computer science, education, cognitive science,
psychology, ethics, economics, human-computer interaction, and social sciences.
Topics of Interest
We welcome contributions on (but not limited to) the following topics. Submissions may address
questions such as: What does it mean to learn in the age of AI? When does AI augment learning, and when does
it replace it? What skills remain distinctly human in an AI-augmented world? How do we define learning
success when AI completes tasks for students? How do we evaluate the long-term impact of AI on learning
outcomes? How does AI change the nature of creativity, problem-solving, and critical thinking? How do we
ensure AI tools do not reinforce existing inequalities?
Responsible AI in Education
- Transparency, explainability, and accountability in AI-powered learning systems
- Communicating AI limitations (e.g., hallucinations, uncertainty) to users
- Large language models in educational contexts
- Privacy, data protection, and governance of student data
- Learning analytics and educational data mining
- Ethical frameworks and governance for AI in education
- AI policy and regulation in educational institutions
- Designing systems that make risks visible, interpretable, and actionable
Equity, Fairness & Inclusion
- Bias detection, measurement, and mitigation in educational AI
- Inclusive and accessible AI-supported learning environments
- Addressing inequalities in access, representation, and AI literacy
- AI for supporting diverse and underserved learners
- Sociological and cultural factors in AI adoption across educational contexts
- Digital divide and unequal access to AI-powered tools
- Gender, race, and disability bias in AI-powered learning systems
- Community-based and participatory approaches to equitable AI design
Human-Centered AI
- Learner agency vs. over-reliance and automation bias
- Cognitive impacts of AI use (e.g., shallow learning, reduced effort, illusion of understanding)
- Intelligent tutoring systems and conversational agents
- Evolving teacher roles: augmentation, adaptation, or deskilling
- Designing for reflection, reasoning, and metacognition
- Cognitive science and psychological dimensions of AI-supported learning
- Student wellbeing and mental health in AI-mediated learning
- Adaptive and personalized learning environments
Serious Games & Inclusive Learning
- AI-enhanced serious games for education and training
- Game-based approaches for AI literacy and critical thinking
- Serious games for social-emotional learning and inclusion
- Participatory design of serious games with marginalized communities
- Narrative and storytelling in AI-driven educational games
- Emotional and motivational dimensions of game-based learning
- AI-generated content in serious games: opportunities and risks
- Accessibility and universal design in serious games
- Transfer of learning from game-based to real-world contexts
Interdisciplinary & Social Perspectives
- Sociological and psychological dimensions of AI in education
- Cognitive science approaches to AI-supported learning
- Economic and policy implications of AI adoption in education
- Cultural and contextual factors in AI-enhanced learning environments
- AI and the future of educational institutions
- Philosophical and ethical dimensions of AI in education
- Cross-cultural perspectives on AI-supported learning
- AI and educational equity from a policy perspective
Teaching AI
- Teaching AI literacy across formal and informal learning contexts
- Curriculum design for responsible AI education
- Teaching AI concepts across disciplines and age groups
- Pedagogical approaches to explaining AI limitations and risks
- Teacher training and professional development for AI-integrated classrooms
- Assessing student understanding of AI systems and their societal impact
- Evaluating the effectiveness of AI education programs and interventions
- Student and teacher perceptions of AI: trust, fear, and agency
01
Full Papers
Novel findings, methods, or theoretical frameworks. Up to 12 pages (excluding references).
Deadline: 03 July 2026Read
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02
Short Papers
Work-in-progress, position papers, and preliminary results. Up to 6 pages (excluding references).
Deadline: 03 July 2026Read
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03
Doctoral Consortium
PhD students present ongoing research and receive feedback from senior researchers and peers.
Deadline: 03 July 2026Read
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