In this episode, Dr Zhongtian Sun shares insights from both sides of the AI education landscape—as a researcher developing behaviour-aware personalised learning systems, and as a lecturer witnessing first hand how generative AI is reshaping how students learn.
We dive into the development of SPAR-GNN, a hybrid framework that uses graph neural networks and large language models to deliver selective feedback only when students show signs of struggle—like frustration or hint-dependence. We unpack how “at-risk” learners are identified, the ethical dimensions of selective AI support, and what it means to teach in an age where tools like GPT and Co-pilot are becoming second nature to students.
We also explore the shifting dynamics of deep learning and software development education—where project-based, independent learning collides with the realities of AI-assisted shortcuts. What new pedagogies are emerging to ensure genuine understanding, not just efficiency? And how do we assess learning when generating an answer is no longer proof of knowledge?
Dr Zhongtian Sun is a Lecturer in Artificial Intelligence at the University of Kent, with a research focus in graph representation learning, explainable AI and large language models (LLMs). His research aims to enhance the reasoning capabilities of deep learning models, with applications in healthcare, finance, education and recommendation.
He holds a PhD in Computer Science from Durham University and has held research roles at the Universities of Cambridge and Oxford, contributing to projects in clinical AI, knowledge graph reasoning and LLM-based decision support. He also worked on a funded research project with the UK Department for Transport through the Turing Internship Network.
Dr Sun is Co-founder and CTO of an AI for Finance startup, developing a knowledge graph powered platform for market analysis and multi-agent portfolio reasoning.
His academic collaborations span Oxford, Cambridge, Glasgow, Durham and the Alan Turing Institute. He serves as Area Chair and Senior Programme Committee Member for leading conferences including ECAI, AIED, ICLR and is Visiting Faculty at the University of Cambridge.