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AIED 2026: International Conference on AI in Education

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AIED
Día de Entrega:
2026-01-26
Fecha de Notificación:
2026-03-23
Fecha de conferencia:
2026-06-27
Ubicación:
Seoul, South Korea
Ediciones:
ICORE: A   QUALIS: B1   Vistas: 39375   Seguidores: 16   Asistentes: 8

Solicitud de Artículos

AIED 2026 (International Conference on AI in Education) is a ICORE A / QUALIS B1 conference held in Seoul, South Korea on 2026-06-27. The paper submission deadline is 2026-01-26. Acceptance notifications are sent on 2026-03-23.

Discover the AIED 2026 tracks This year's conference invites both empirical and theoretical contributions to the core AIED research within the following three tracks. Domain-specific submission can be submitted to different tracks depending on their focus. Track 1 — Technical aspects of AIED Focus The computer science and engineering dimension of AIED. The primary contribution must be technical. Representative topics Novel AIED architectures and system engineering Novel cognitive systems and computational reasoning Knowledge representation and domain modeling Agentic AI and (multi) agent systems Machine learning, deep learning, generative models, NLP, and video modeling Data mining, feature engineering, predictive modeling Multimodal systems AIED systems for special education Frugal systems in AIED Intelligent tutoring system implementation Evaluation through computational metrics (accuracy, validity, reliability) Keywords Intelligent tutoring systems, Pedagogical agents, LLMs, Classifiers, Predictive models, Clustering, Data mining, Multi-agent architectures, Proof-of-concept, Knowledge representation Track 2 — Human aspects of AIED Focus Human learning, pedagogy, and theoretical foundations. The primary contribution must come from learning science and humanities. Representative topics Studies on agency, co-regulation, and human-AI collaboration Empirical evaluation of AIED systems (quantitative, qualitative, or mixed methods) Learning sciences perspectives on AIED Pedagogical theories and instructional design Human cognitive, motivational, metacognitive, or affective processes Collaborative, informal, or game-based learning studies Analyses focused on understanding learners, teachers, or educational phenomena Keywords Pedagogy, Cognitive states, Affective states, Learning theory, Learner engagement, Self-regulation, Learning processes, Motivation, Metacognition, Social learning, Lifelong learning, Collaborative learning Track 3 — Societal aspects of AIED Focus Ethics, equity, policy, and societal dimensions of AIED. The primary contribution must address ethics, equity, policy, or societal dimensions of AIED. Representative topics Algorithmic fairness, bias, transparency, accountability Privacy, surveillance, data governance Cultural awareness in AIED Low-resource and development contexts; addressing the AIED divide Socio-economic, gender, and racial equity in AIED Ethical frameworks for AIED deployment Policy implications for AI in education AI literacy and critical AI education when focusing on societal implications Keywords Bias, Fairness, Transparency, Inclusion, Privacy, Governance, Responsible AI, Under-resourced contexts, Societal impact
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