The rapid advancement of Artificial Intelligence (AI) technologies—ranging from rule-based systems and machine learning to large language models (LLMs) and multimodal AI—has revolutionized how human-computer interaction is conceived and implemented in educational settings. However, current research often lacks a nuanced understanding of how AI can be meaningfully embedded into domain-specific learning processes. Rather than adopting a one-size-fits-all approach, this special session emphasizes the need to align AI functionalities with the unique epistemic and pedagogical characteristics of individual disciplines.

This session aims to explore the disciplinary affordances of AI-integrated educational environments, analyze the nature and quality of interaction processes between learners and AI, and examine how these processes influence their cognitive, affective, and behavioral learning outcomes. Of particular interest is how the synergy between specific types of AI technologies (e.g., conversational AI, intelligent tutoring systems) and subject-matter features (e.g., inquiry in science, argumentation in language, modeling in mathematics) can lead to more meaningful and effective learning experiences.

The primary objectives of this special session are:

  • To investigate how different AI technologies can be optimally matched with the epistemic and instructional features of various academic disciplines.
  • To examine the interactive mechanisms that emerge in AI-supported learning scenarios, including feedback loops, dialogue moves, co-construction patterns, and learner agency.
  • To assess how the nature and quality of human-AI interaction impacts learning performance across cognitive, affective, and behavioral dimensions.

We encourage submissions on a range of topics, including but not limited to

  • Disciplinary Affordances and AI Integration
    • Aligning AI capabilities with disciplinary inquiry models (e.g., problem solving, experimentation, modeling)
    • Designing AI-empowered systems through learner-centered perspective
    • Design principles for discipline-specific AI learning companions or tutors
    • Epistemological considerations in human-AI co-learning
  • Interaction Processes and Learning Analytics
    • Fine-grained analysis of human-AI dialogues and multimodal interactions
    • Sequence modeling and discourse analysis to detect learning-relevant interaction patterns
    • Dynamic scaffolding and adaptive feedback mechanisms across subject areas
  • Impact of AI Tools/Platforms/Apps on Learning Outcomes
    • Comparative studies on AI-enhanced vs. traditional instructional methods
    • Quantitative and qualitative evaluation of student performance, engagement, and self-regulation
    • Longitudinal tracking of learning trajectories in AI-mediated environments
  • Cross-Disciplinary and Multimodal Perspectives
    • Case studies across STEM, humanities education
    • Integration of LLMs and multimodal AI into interdisciplinary learning environments
    • Culturally responsive AI design for diverse learner populations
  • Ethical and Pedagogical Considerations
    • Human agency and teacher roles in AI-supported instruction
    • Data privacy, fairness, and bias in adaptive AI systems
    • Transparent and explainable AI for educational trustworthiness

This special session invites empirical, theoretical, design-based, and methodological contributions from researchers in AI in education, learning sciences, HCI, educational psychology, and subject-specific pedagogy. Case studies and cross-disciplinary collaborations are particularly encouraged.

Important Dates

  • Special Session Papers Submission: 15 July 2025
  • Acceptance Notification: 15 August 2025
  • Camera-Ready Submission: 08 September 2025
  • Conference Date: 16-18 Oct 2025

Paper submission instruction

Paper submission system is available at: https://cmt3.research.microsoft.com/BESC2025.

All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to BESC 2025, originality, significance and clarity.

Please note:

  • Paper review will be double-blind, and submissions not properly anonymized will be desk-rejected without review.
  • Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings.
  • Papers must be clearly submitted in English and will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation.
  • Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work.
  • Top quality papers after presented in the conference will be selected for extension and publication in several special issues of international journals, e.g., IEEE Transactions on Computational Social Systems (IEEE), IEEE Transactions on Learning Technologies (IEEE), CCF Transactions on Pervasive Computing and Interaction (Springer), EURASIP Journal on Image and Video Processing (Springer), World Wide Web Journal (Springer), Social Network Analysis and Mining (Springer), Human-Centric Intelligent Systems (Springer), Natural Language Processing (Elsevier), Health Information Science and Systems (Springer), Web Intelligence (IOS Press), etc.
  • The use of artificial intelligence (AI)–generated text in an article shall be disclosed in the acknowledgements section. The sections of the paper that use AI-generated text shall have a citation to the AI system used to generate the text.

Organizing Committee

Special Session Chairs
Dr. Daner Sun, The Education University of Hong Kong, Hong Kong SAR
Dr. Jingyun Wang, Durham University, UK
Dr. Wangda Zhu, The Hong Kong Polytechnic University, Hong Kong SAR
Dr. Yin Yang Nicole, The Education University of Hong Kong, Hong Kong SAR

Program Committee Members
Dr. Weng Xiaojing, The Education University of Hong Kong, Hong Kong SAR
Dr. Liu, Lukas Z., The University of Hong Kong, Hong Kong SAR
Dr. Koon Chun Alex, The Chinese University of Hong Kong, Hong Kong SAR
Dr. Yang Jian, The University of Hong Kong, Hong Kong SAR
Dr. Zhang Lexuan, The Education University of Hong Kong, Hong Kong SAR
Dr. Junjie Gavin, Wu, The Education University of Hong Kong, Hong Kong SAR
Dr. Xiaoyi Tian, North Carolina State University, USA
Dr. Yu Hao, Icahn School of Medicine at Mount Sinai, USA
Mr. Yuanzhi Wang, Cornell University, USA
Dr. Mengni Zhang, UW Madison, USA
Dr. Yuanqing (Ching) Tian, NC State University, USA

All inquiries about the special session proposal can be directed to the Special Session Chairs:
Daner Sun, The Education University of Hong Kong, China ([email protected])