Track Program Chairs

  • Nian-Shing CHEN
    National Taiwan Normal University, Taiwan
  • Patrica A. Jaques MAILLARD [Chair Coordinator]
    Universidade Federal do Paraná (UFPR) and Universidade Federal de
    Pelotas (UFPEL), Brazil
  • Sean Wolfgand Matsui SIQUEIRA
    Federal University of the State of Rio de Janeiro (UNIRIO), Brazil
  • Stephen J.H. YANG [Chair Coordinator]
    National Central University, Taiwan
  • Chengjiu YIN
    Kyushu University, Japan

Track description and topics of interest

Artificial Intelligence (AI) and Smart Learning Environments represent a new wave of educational systems, characterized by an effective and efficient blend of pedagogy, technology, and their synergistic fusion. These environments aim to enhance learning processes and improve educational outcomes. A ‘Smart Learning Environment’ refers to settings where learners are supported by adaptive and innovative technologies throughout their educational journey, from childhood to adulthood, encompassing both formal and lifelong learning.

AI in education serves to not only educate and train, but also to augment human productivity and improve the quality of work. This, in turn, elevates the standards of learning and teaching. By embracing AI, educators and learners can experience a transformation in traditional learning paradigms, making way for more efficient and effective educational practices.

Unlike traditional systems, Smart Learning Environments are not purely technology-driven or confined to specific pedagogical methods. They represent a diverse array of contexts and learning experiences, where learners and educators fluidly transition between different learning settings. This approach challenges the conventional institution-based instruction, paving the way for more personalized and lifelong learning opportunities.

At AISLE@ICALT, will explore various dimensions of applying artificial intelligence and the emerging smart learning environments, such as what makes a learning environment smart, challenges in the design and implementation of such environments in multiple and heterogeneous contexts, pedagogical and technological underpinnings, and the validation issues. Various components of this interplay include but are not limited to:

Key Topics of Interest:

  1. AI-Driven Pedagogical Strategies: Examining how AI influences pedagogical approaches, including adaptive learning models, AI in curriculum development, and the integration of AI tools for enhancing teaching and learning processes.
  2. Innovations in Smart Educational Technology: Highlighting the latest advancements in educational technology such as virtual and augmented reality, intelligent tutoring systems, and emotional intelligent learning environments.
  3. Ethics and Equity in AI Education: Addressing the ethical challenges and promoting equity in AI-driven education. This includes discussions on data privacy, algorithmic fairness, and ensuring inclusive learning opportunities for all.
  4. AI in Assessment and Evaluation: Exploring the use of AI in the assessment process, including automated grading systems, adaptive testing, and AI tools for feedback and evaluation.
  5. The Role of AI in Educational Administration: Investigating how AI can streamline administrative tasks, enhance decision-making processes, and support policy-making in educational contexts.
  6. Collaborative AI and Human-Centered Learning: Focusing on the collaboration between AI and human instructors, including co-teaching models, AI as a teaching assistant, and the development of empathetic and emotionally aware AI systems.
  7. Emerging Trends in AI and Education: Discussing the latest trends and future directions in AI and education, such as Large Language Models (LLMs), Metaverse in Education, Prompt Engineering for Education, Pedagogical AI Agent and Generative AI in Education.

AISLE@ICALT 2024 invites educators, researchers, and practitioners to contribute to this evolving field. By sharing insights, experiences, and innovations, we aim to shape the future of AI in education and foster environments that adapt, engage, and inspire learners at every stage of their educational journey.

Track Program Committee

  • Jorge Luis Bacca Acosta, Fundación Universitaria Konrad Lorenz, Colombia
  • Jorge Barbosa, Unisinos, Brazil
  • Irene Y.L. Chen, Department of Accounting, National Changhua University of Education, Taiwan
  • Tadeu Classe, Universidade Federal do Estado do Rio de Janeiro, Brazil
  • Laura de Oliveira F. Moraes, Universidade Federal do Estado do Rio de Janeiro, Brazil
  • Fabiano Dorça, Universidade Federal de Uberlandia, Brazil
  • Brendan Flanagan, Kyoto University, Japan
  • Gheorghita Ghinea, Brunel University, United Kingdom
  • Yen-Ting Lin, Department of Computer Science, National Pingtung University, Taiwan
  • Jia-Jiunn Lo, Professor, Department of Information Management, Chung-Hua University, Taiwan, Republic of China, Taiwan
  • Eleandro Maschio, Universidade Tecnológica Federal do Paraná, Brazil
  • Tatsunori Matsui, Waseda University, Japan
  • Riichiro Mizoguchi, Japan Advanced Institute of Science and Technology, Japan
  • Magalie Ochs, LSIS, France
  • Paulo Sérgio Santos, Federal Center for Technological Education of Minas Gerais, Brazil
  • Mônica Ferreira Da Silva, UFRJ, Brazil
  • Hsiao-Ting Tseng, National Central University, Taiwan
  • Cleon Xavier Pereira Júnior, Instituto Federal Goiano, Brazil
  • Tosh Yamamoto, Kansai University, Japan
  • Albert Yang, National Chung Hsing University, Taiwan
  • Christopher Yang, Kyoto University, Japan
  • Tzu-Chi Yang, National Yang Ming Chiao Tung University, Taiwan
  • Xiaokun Zhang, Athabasca University, Canada
  • Yungyu Zhuang, National Central University, Taiwan