- Innovative uses of GenAI to enhance instructional design, adaptive learning, content creation, and discipline-specific pedagogy.
- AI applications in formative and summative assessment, feedback automation, and addressing challenges related to plagiarism, authorship, and originality.
- Leveraging AI to improve student participation, personalise learning pathways, and support data-informed decision-making in education.
- Ethical frameworks, governance, data protection, algorithmic bias, transparency, and equitable access in AI-driven educational systems.
- Embedding sustainability principles, social responsibility, and human values into AI-enhanced engineering and higher education curricula.
- AI-supported approaches to academic advising, career planning, counselling, cross-cultural communication, leadership development, and lifelong learning.
- Faculty development, changing teaching roles, professional identity, and leadership in AI-enabled and digitally transformed learning environments.
- Preparing students for human-centric, AI-integrated workplaces through entrepreneurship, innovation, and future-ready skill development.
- Design and evaluation of flexible, immersive, and technology-enhanced learning environments, including virtual labs, simulations, and extended reality.
Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore's scope and quality requirements and can be retrieved by EI Compendex and Scopus.
Accepted papers that do not meet IEEE Xplore's requirements will be scheduled exclusively for oral or poster presentation.
University of Electronic Science and Technology of China
University of Glasgow