Special Session 4: Artificial Intelligence and Educational Data Analytics: Technologies, Applications, and Trustworthy Governance

 Description 

Artificial intelligence (AI) and educational data analytics are reshaping teaching, learning, assessment, and educational management by enabling intelligent, personalized, and data-driven educational services. Recent advances in large language models, multimodal AI, intelligent tutoring systems, learning analytics, and educational data mining have significantly improved learning experiences and instructional effectiveness. At the same time, these technologies introduce new challenges concerning data privacy, algorithmic fairness, transparency, cybersecurity, ethical AI, and trustworthy governance.
This special session aims to provide an interdisciplinary forum for researchers, practitioners, and educators to present recent advances in AI-enabled educational technologies, educational data analytics, intelligent learning systems, and responsible AI governance. The session welcomes theoretical research, innovative methodologies, intelligent systems, practical applications, and empirical studies that contribute to trustworthy and sustainable digital education.
Particular attention will be given to AI-powered learning environments, multimodal educational intelligence, adaptive learning systems, educational data governance, learning analytics, intelligent assessment, privacy-preserving technologies, and responsible AI deployment. By bringing together researchers from computer science, educational technology, artificial intelligence, data science, and digital governance, this session seeks to foster interdisciplinary collaboration and promote innovative educational technologies that are intelligent, secure, trustworthy, and learner-centered.

 Session Topics 

The topics of interest include, but are not limited to:
- Artificial Intelligence for Education
- Large Language Models and Generative AI in Education
- Intelligent Tutoring Systems and Adaptive Learning
- Learning Analytics and Educational Data Mining
- Educational Data Analytics and Predictive Learning
- Multimodal AI and Intelligent Human–Computer Interaction
- AI-based Assessment and Intelligent Feedback
- Educational Data Governance, Privacy, Security, and Trustworthy AI

 Submission Method 

Submit your Full Paper or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 4 (Artificial Intelligence and Educational Data Analytics: Technologies, Applications, and Trustworthy Governance)

 Session Organizers 

Lecture Jianxun Guo,
Nanjing University of Finance and Economics, China
 
Jianxun Guo is a Lecturer at the School of Law, Nanjing University of Finance and Economics, China. He received his Ph.D. in Law from the University of Exeter, UK. His research focuses on AI governance, educational data governance, digital governance, insurance law, and the regulation of emerging technologies. He has published extensively on AI-enabled educational systems, privacy impact assessment (DPIA), blockchain-based educational governance, trustworthy learning analytics, and digital transformation in higher education. His recent work promotes interdisciplinary collaboration between law, artificial intelligence, and educational technology.

 

Lecturer Meng Xu,
Nanjing University of Finance and Economics, China
 
Meng Xu is a Lecturer and Master's Supervisor at the School of Law, Nanjing University of Finance and Economics, China. She received her Ph.D. in Law from the University of Exeter, UK. Her research interests include technology law, data governance, smart ports, cross-border data flows, and AI governance. She has published research on data governance, blockchain-enabled educational systems, generative AI governance, and digital transformation in higher education. Her work emphasizes responsible innovation, legal governance, and trustworthy digital ecosystems.

 

Assoc. Prof. Fan Yang,
Nanjing University of Finance and Economics, China
 
Fan Yang is an Associate Professor and Master's Supervisor at the School of Information Engineering, Nanjing University of Finance and Economics, China. He is a recipient of the Young Scholars Support Program and Young Outstanding Talent Program of the university. His research interests include artificial intelligence, multimodal learning, computer vision, data mining, intelligent human-computer interaction, and AI for medical research. He has led projects funded by the National Natural Science Foundation of China and has published extensively in leading AI and computer science venues, including AAAI, Pattern Recognition, IEEE Transactions on Circuits and Systems for Video Technology, Information Sciences, and Knowledge-Based Systems. His research bridges advanced AI technologies with real-world intelligent applications.