On 28 January, CTLE held a dynamic half-day professional development event, focusing on fundamentals of education in AI era. Nearly 80 UM academic colleagues joined the event.

Prof. Michael Hui (Vice Rector for Academic Affairs) led the kick-off of the event. In his opening remarks, quoting the slogan of UM’s 45^th anniversary, he posed a few questions about the future of teaching and learning in university education in the age of AI.

GenAI can generate answers in seconds but cannot replace learning with our own minds.

The future of education still lies in human skills.

During her plenary session entitled ‘The sprint and the marathon: Learning and teaching transformations in the age of AI’, Dr. Juila Chen (The Hong Kong Polytechnic University) emphasised that educators must respond swiftly while teaching in order to support long-term transformation in higher education. She highlighted several emerging concerns, including learners’ reliance on AI, diminishing creativity, the rise of deepfakes, emotional dependency on AI tools and growing questions about the value of degrees and the purpose of attending university.

She also shared PolyU’s strategies, including AI policies and guidelines, literacy courses and assessment redesign, prioritising multiple stages and authentic tasks to ensure students demonstrate genuine understanding and application.

Dr. Chen further reminded the audience that universities must clarify what learning truly means, reaffirm the value of human‑centred education and prepare students for an increasingly complex and uncertain future, framed through VUCA/TUNA/BANI perspectives.

She proposed four key components of future-ready education: techno‑competency, disciplinary training, soft skills, and the capacity to engage with the ‘unknown unknowns’. She also stressed that both teaching and learning processes need to spotlight cognitive onloading.

AI is not the future of learning: it is the present.

 Students stand out not by how fast they use AI, but by how deeply they think, question and grow beyond it.

The event also invited three UM students to share their perspectives on the purpose of learning and personal growth thriving in the age of AI. The panel was moderated by Prof. Katrine WONG (DCTLE) and Dr. Julia CHEN.

• Hongye TAN (FST) described AI as an efficient search engine that helps students overcome the challenge of identifying where to begin when learning new things. Without AI, he said, learning could be overwhelming. He believed that a year‑long GE course for first‑year students, with a focus on life goals, would be helpful. He also suggested the development of a university-wide platform for information exchange.
• Xinzhu LIU (FSS) shared that she uses AI to organise learning materials, strengthen critical thinking and brainstorm research ideas. She mentioned her experience with AI’s creative capabilities and suggested the creation of a GE course dedicated to AI literacy and ethics. She expressed a desire to remain engaged with UM after graduation.
• Haoruyi JI (FAH) said that AI helps her in focusing on meaning rather than language and supports her academic writing. However, she also expressed concerns about students becoming overly reliant on AI. She hoped that alumni could continue to access AI tools and academic databases supported by UM after graduation.

In their closing remarks, the moderators highlighted a central challenge: if everyone uses AI in similar ways, the differentiating qualities of individuals may increasingly be found in uniquely human capacities. While AI enhances efficiency, the panel reiterated that genuine learning, motivation and authentic effort remain irreplaceable.

Dr. Chris Fulton (CTLE) facilitated an interactive session on ‘Re-Blending Learning’. In this session, participants explored practical strategies and tools for maintaining student focus amid growing digital distraction.

The session introduced two tried and tested human-first approaches, including starting class with a quick question, poll or pair-work activity, or with a brief writing activity. Participants shared focus activities that involved small group work.

Three tools were highlighted for re-blended learning: YuJa in-video quizzes (with scores sent to Moodle), YuJa in-video comments for social annotation, and Copilot for designing active learning activities. A Think-Pair-Share template demonstrated how to integrate AI guidelines at different phases: prohibited during individual thinking, permitted with caution during pair work, and encouraged during class discussion.

To watch playback of all sessions, please go here.

The presentation slides are available to colleagues here.