Teaching & Learning

Dr. Dimple R. Thadani (PhD, SFHEA, PGCHE) is a Senior Lecturer at Hong Kong Baptist University, specialising in AI-related business subjects, including AI for Business and Business Intelligence. She holds a PhD in Information Systems, an Advance HE Senior Fellowship (SFHEA), and a Postgraduate Certificate in Higher Education (PGCHE). Dedicated to integrating technology, education, and business to prepare students for the digital era, she received the Higher Education Outstanding Teaching Achievement Award from the Ningbo Education Bureau (Municipal Level) in April 2025. Her research interests include AI tools and pedagogy, agentic AI for education, AI in business education, digital transformation, platform strategies, and the development of smart cities.

This team is recognised for their collaborative work on the GE course, “GTCU/GTSU/GTSC2805 Critical AI Literacies: Embracing AI for Social Good”.

The Panel is impressed by the alignment between the course’s pedagogies and assessments. The course is guided by a clear pedagogical framework—understand, apply, and create—which provides a robust structure to equip students with the integrated literacies essential to the AI era and drives them toward an ethical use of AI. This thoughtful design ensures that every teaching and learning activity and assessment directly supports the core goal: fostering not just technical skills, but critical judgement and social responsibility.

A key factor in this recommendation is the team’s innovative, transdisciplinary course structure. The members’ distinct areas of expertise in computer science, visual arts, communication, and business provide a comprehensive and synergistic foundation for the course. This blend of perspectives prepares students for real-world problem-solving by challenging them to analyse AI from multiple critical angles. Demonstrating remarkable foresight, the team has also developed a manual to ensure the course’s quality and to facilitate its expansion with new teaching members in the future.

The Panel also notes the team’s deep commitment to active learning, particularly their “create → critique → refine” methodology. This methodology is brought to life through a hands-on format centered on discussion and critique, made possible by a flipped classroom model. Furthermore, to address the challenge of AI-generated assignments, the team has incorporated live debates that require students to think on their feet, ensuring genuine understanding and engagement.

In recognition of their exceptional course design, innovative pedagogy, and impactful transdisciplinary collaboration, the Panel recommends the team for the GE Teaching Award (Team Teaching) to honour their excellent performance.