• 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.