Track Program Chairs

• Patrícia A. JAQUES, Universidade Federal do Paraná (UFPR) and Universidade Federal de Pelotas (UFPEL), Brazil [coordinator]
• Laura DE OLIVEIRA F. MORAES, Universidade Federal do Estado do Rio de Janeiro, Brazil
• Sean Wolfgand Matsui SIQUEIRA, Federal University of the State of Rio de Janeiro (UNIRIO), Brazil [coordinator]

Track description and topics of interest

Artificial Intelligence (AI) and Smart Learning Environments (SLEs) represent a transformative wave in educational systems. While SLEs provide the architectural framework for context-aware and ubiquitous learning, the recent surge in Generative AI offers new capabilities to make these environments truly adaptive.

This track explores the synergistic fusion of pedagogy, environmental context, and advanced AI agents. We aim to discuss how AI can not only diagnose learner needs but also dynamically generate personalized content, feedback, and scaffolding in real-time, creating responsive environments that support learners across formal and lifelong learning contexts.

Topics of Interest

We invite submissions that address the intersection of AI and learning environments, including
but not limited to:

• Generative AI & LLMs in Education: Utilizing Large Language Models to generate dynamic educational content, automated feedback, and tutoring within learning environments.
• Intelligent Agents & Chatbots: The role of AI agents as ubiquitous tutors that bridge the physical and digital worlds.
• AI-Driven Pedagogical Strategies: Examining how AI influences pedagogical approaches, including adaptive learning models, AI in curriculum development, and personalized learning paths.
• Context-Aware Adaptation: Systems that use AI to adapt to the learner’s real-world context, emotional state, and learning location.
• Innovations in Smart Educational Technology: Highlighting advancements such as virtual/augmented reality (VR/AR), IoT (Internet of Things), and wearable sensors integrated with intelligent processing.
• Collaborative AI and Human-Centered Learning: Focusing on the collaboration between AI and human instructors (e.g., co-teaching models, AI as a teaching assistant).
• Ethics and Equity in AI-Enhanced Environments: Addressing ethical challenges, data privacy, algorithmic fairness, and the impact of Generative AI on academic integrity.

Track Program Committee