Special Session 1


Human and AI Collaboration in Teaching and Learning: Mechanism, Challenges and Ethics


Although human-AI collaboration has drawn significant attention in recent years, its overall effectiveness remains inconclusive. At the individual level, AI supports self-regulated learning (Celik et al., 2025) by providing tailored feedback (Chen et al., 2025), fostering reflective practices (Yan et al., 2025), and facilitating adaptive assessment (Chen et al., 2025). It also enables immersive simulations that advance professional growth (Zheng et al., 2025; Wu et al., 2020; Koumpouros, 2024). At the group level, AI serves as a collaborative partner to co-create knowledge and hone professional judgment (Juan et al., 2026; Cai et al., 2025), driving a transition toward learner-centered, collaborative frameworks (Lin et al., 2024; Yan et al., 2023).
Conversely, integrating AI entails notable risks, including unethical practices, over-reliance (Darvishi et al., 2024), metacognitive passivity, diminished motivation (Lin et al., 2026), and superficial learning. Moreover, the impact of AI is moderated by human factors such as trust (Henderson et al., 2025), self-efficacy (Yang et al., 2024), and experience (Ghafouri et al., 2024), alongside institutional variables including financial support (Huang & Yu, 2025), organizational policy (Ng et al., 2025), and curricular alignment (Sumra et al., 2026).
For this special issue, we invite high-quality contributions centered on human-AI collaboration. We welcome original research, reviews, and conceptual papers exploring how AI can be integrated across curriculum design, material development, learning activities, and assessment to amplify - rather than replace - human expertise.

Call for Topics

  • Dynamics of Human-AI Interaction in Teaching and Learning
  • Ethics, Privacy, and Trust in Human-AI Collaborative Learning
  • Assessment and Feedback Systems via Human-AI Partnership
  • Human-AI Collaboration for Reflection and Self-Regulated Learning
  • Human-AI Interaction and Agency in Educational Environments

    • Session Chair

    Assoc. Prof. Wei Wei

    Macao Polytechnic University, Macao, China
     

    Dr Wei Wei is an Associate Professor in the Faculty of Applied Sciences at Macao Polytechnic University, where he serves as coordinator of PhD program in Educational Technology. He received his PhD from the School of Education, University of Leeds. He has published over 50 articles in peer-reviewed international journals. His recent research explores generative AI, social media analytics, online learning engagement, AI-generated feedback, classroom assessment, and technology-enhanced professional development.

    Co-chair

    Assit. Prof. Shuhan Zhang

    Macao Polytechnic University, Macao, China
     

    Dr. Zhang Shuhan is an Assistant Professor in the Faculty of Applied Sciences at Macao Polytechnic University, and she is a PhD supervisor in the program of Educational Technology and Innovation. She received her PhD from the Faculty of Education, The University of Hong Kong. Her research interests lie in STEAM education, AI education, educational assessment, and game-based learning.

     

    Submission Link: AETS 2026: Special Session 1 Submission