Lixiang Yan, Tsinghua University

Yizhou Fan, Peking University

Yueqiao Jin, Monash University

Nancy Law, University of Hong Kong

Yu Zhang, Tsinghua University

Xibin Han, Tsinghua University

This special section examines agentic AI in education, defined as computational systems exhibiting interactivity, bounded autonomy, and adaptability within human-defined objectives. Unlike reactive AI tutoring systems or prompt-based generative AI tools, agentic AI initiates action, sustains participation, and maintains functional roles through persistent memory and task decomposition. The shift toward such systems reconfigures how epistemic labour and coordination are distributed within learning communities, affecting learners' perceptions of agency, shared regulation, and collaborative reasoning.

The section welcomes empirical and conceptually grounded studies exploring how agentic AI reshapes learner perceptions, teacher roles, epistemic labour, and social-cognitive dynamics. Particular emphasis is placed on understanding when artificial agency supports productive learning versus constraining learner autonomy, examining this across diverse educational contexts, learner populations, and cultural settings. Contributions addressing governance, responsibility, equity, and methodological innovation are encouraged.

Appel publié par British Journal of Educational Technology. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Conceptualising Agentic AI as Artificial Agency in Education: Frameworks and models that define agentic AI explicitly in terms of interactivity, bounded autonomy, and adaptability, and that clarify boundaries between agentic AI, generative AI assistants, and reactive AIED systems.
• Learner and Teacher Perceptions of Artificial Agency: Empirical investigations of how learners and educators interpret AI initiative, persistence, and role adoption, and how these perceptions shape trust, attribution of intent, responsibility, and participation in learning activities.
• Epistemic Labour and Initiative Redistribution: Studies examining how agentic AI redistributes epistemic labour within individual or collaborative learning, including effects on problem framing, task coordination, evaluation, and decision-making when AI initiates actions rather than responding to prompts.
• Regulation, Coordination, and Social-Cognitive Dynamics: Analyses of how agentic AI influences self-regulation, co-regulation, and shared regulation, particularly in group settings where AI adopts persistent roles that shape interactional norms, turn-taking, and closure of inquiry.
• Temporal Persistence and Path Dependence in Learning Processes: Research that captures how agentic AI's sustained participation and memory create path-dependent learning trajectories, including benefits for coherence and risks of early framing effects or cascading errors.
• Identity Inference, Social Presence, and Responsibility: Empirical work on how proactive AI behaviour affects identity inference and social presence in cue-lean environments, and how responsibility and accountability are negotiated when learning actions originate from artificial agents.
• Methodological Approaches for Studying Artificial Agency: Methodological contributions that advance the measurement of artificial agency and its effects, including multimodal analyses, process-level modelling, and designs that distinguish agentic participation from tool-based assistance.
• Governance and Educational Implications of Agentic AI: Analyses addressing accountability, transparency, and institutional responsibility when agentic AI functions as a collaborator, coordinator, or evaluator in educational settings.

Timeline

• August 1, 2026: Abstract submission deadline
• October 28, 2026: Full manuscript submission deadline
• March 15, 2027: Final manuscript acceptances
• May 1, 2027: Issue publication online

Andrea Antonio Cantone, University of Salerno

Dragan Ahmetovic, University of Milano

Paloma Diaz, Universidad Carlos III de Madrid

Giuliana Vitiello, University of Salerno

This special issue explores how immersive technologies such as Virtual Reality, Augmented Reality, and Mixed Reality can be designed and implemented to create equitable educational experiences that serve all learners. While immersive technologies offer significant potential for engaging students through interactive, embodied learning, many current applications lack adequate accessibility and inclusive design considerations, potentially creating new digital divides.

The special issue welcomes interdisciplinary research integrating perspectives from human-computer interaction, educational technology, accessibility research, and learning sciences. It seeks contributions investigating how immersive technologies can support diverse learners, including students with disabilities, neurodivergent learners, and individuals from varied cultural and socio-economic backgrounds.

Original research articles, empirical studies, case studies, and evidence-based methodological analyses addressing accessibility challenges, design frameworks, adaptive systems, evaluation methods, and inclusive practices in XR educational environments are invited for submission.

Appel publié par Behaviour & Information Technology. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Design and development of accessible and inclusive immersive learning and training environments
• Inclusive design frameworks and guidelines for immersive educational technologies
• Immersive technologies supporting students with disabilities (e.g., cognitive, sensory, motor, neurodevelopmental conditions)
• Adaptive and personalized immersive learning and training experiences
• Accessibility challenges and solutions in XR educational interfaces
• Use of immersive technologies to support neurodivergent learners
• Evaluation methods for accessibility, usability, and user experience in immersive educational systems
• Immersive technologies for social skills training and behavioral learning
• AI-driven adaptive systems in immersive learning environments
• Multimodal and embodied interaction techniques for accessible XR learning
• Immersive simulations for inclusive education and special education
• XR technologies for experiential and collaborative learning in inclusive classrooms
• Ethical, social, and accessibility implications of immersive technologies in education

Timeline

• November 30, 2026: Manuscript deadline