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Generative AI-TE 2026 : 1st (Generative) AI in Technology-Enhanced Learning

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Link: https://iv.csites.fct.unl.pt/uk/symposia/iv/gai-tel/
 
When Jul 28, 2026 - Jul 31, 2026
Where London-UK
Submission Deadline Apr 20, 2026
Notification Due May 15, 2026
Final Version Due Jun 1, 2026
Categories    generative ai in education   technology-enhanced learning   learning analytics & adaptive   intelligent tutoring systems,
 

Call For Papers

1st International Symposium on (Generative ) Artificial Intelligence in Technology-Enhanced Learning

This symposium examines how Artificial Intelligence in general, and Generative AI in particular, is transforming The research and application area of Technology Enhanced Learning (TEL).
Focus is on the use of Language Models, and Large Language Models are used in TEL, to promote learning, in fields such as Intelligent Tutoring Systems, computation and use of Learning Analytics, Adaptive Systems, and data-informed educational practice.
It brings together research addressing design, evaluation, ethics, and governance of (Gen)AI-mediated learning environments, bridging technical innovation with pedagogical and societal considerations.
Topics of interest are as follow:

Design & Learning Experience
Generative AI for learning design, content creation, and curriculum support
Adaptive and personalised learning systems powered by generative models
Human–AI collaboration in teaching, learning, and assessment
Intelligent tutoring systems and AI-supported feedback mechanisms
AI-supported assessment design and formative feedback
Learning design for AI-mediated and hybrid learning environments
Analytics & Methods
AI-driven learner modelling, profiling, and prediction
Learning analytics for evaluating AI-mediated learning experiences
Integration of generative AI with learning analytics pipelines
Multimodal learning analytics (text, audio, video, interaction data)
Analytics-informed prompt engineering and adaptive content generation
AI-assisted learning interventions and impact evaluation
Methodological challenges in studying AI-mediated learning
Ethics, Governance & Trust
Responsible, ethical, and trustworthy AI in learning environments
Explainable and interpretable AI for educational decision-making
Bias, fairness, transparency, and accountability in generative AI systems
Data governance, privacy, and regulatory challenges in AI-driven learning
Learner agency, consent, and control in AI-mediated education
Academic integrity and the ethical use of generative AI
Practice, Policy & Deployment
Learning dashboards and visual analytics for AI-enhanced education
Institutional adoption and pedagogical transformation
Policy implications of generative AI in education
Case studies and real-world deployments of AI in learning contexts
Professional development for educators using generative AI
Futures of learning analytics in the age of generative AI

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