Academic leadership at NTU Singapore
Technology, Education & Partnerships
How should universities teach, assess, and build knowledge when AI systems are becoming part of everyday intellectual work?
I serve as Assistant Dean for Technology and Education in the College of Humanities, Arts, and Social Sciences at Nanyang Technological University.
My work in this role concerns how the College approaches technology and AI in curriculum, teaching, and external collaboration. The goal is to make better judgments about where these systems help learning, where they weaken it, and what students need to understand about AI beyond how to use a particular tool.
AI, Curriculum & Teaching
Generative and agentic AI raise practical questions for every field in the humanities, arts, and social sciences. They also raise questions about knowledge, authorship, judgment, evidence, and responsibility. Those questions belong throughout the curriculum.
Where does AI improve learning?
Some uses can make comparison, iteration, feedback, or exploration more productive. Others replace the difficult work through which learning happens. The distinction depends on the learning objective, not on the novelty of the tool.
What should students understand?
Competence with AI should include more than prompting. Students need ways to assess evidence, recognize limitations, understand how systems shape communication, and decide when their use is appropriate.
How should teaching and assessment change?
Faculty need room to experiment responsibly while preserving clear academic standards. Assessment should make reasoning, process, and disciplinary judgment visible, even when AI is part of the work.
Why the Humanities, Arts & Social Sciences Matter
Humanities, arts, and social-science expertise belongs at the center of AI education. Questions about language, culture, persuasion, creativity, identity, institutions, and social consequences shape how these systems are designed and used.
My own research in Human–AI Communication and embodied interaction informs this work. It keeps the focus on how people actually understand and respond to intelligent systems, rather than treating adoption as a purely technical matter.
External Collaboration
I welcome conversations with researchers and practitioners working on AI education, human–AI interaction, responsible deployment, robotics, immersive technology, and AI product design.
Useful conversations may involve:
- Research and teaching collaborations
- Curriculum and knowledge exchange
- Student learning and professional opportunities
- Responsible experimentation with emerging systems
- Human-centered technology development
This page is an invitation to discuss shared questions, not a commitment on behalf of NTU. Any institutional initiative would involve the appropriate College and university processes.
Before joining NTU, I worked in the Bay Area and became familiar with the questions that technology organizations bring to research and education. My current work in Singapore gives those conversations a different institutional and regional context.
Start a Conversation
Relevant conversations include AI literacy, curriculum and assessment, responsible AI use, university–industry research and teaching models, immersive technology, robotics, and the changing relationship between people, knowledge, and intelligent systems.
Email: david.jeongcg [at] ntu.edu.sg
For research questions and doctoral study, visit the Embodied Dynamics Lab. For publications and current work, return to the research overview.