The Digital Teacher: AI in Education

Duration: 2 hrs 2 mins
Publication date: 31 Oct 2025

Abstract

AI is revolutionising modern education. AI algorithms and educational robots are now integral to learning management and training systems, providing support for a wide array of teaching and learning activities. For example, chatbots that can provide personalised feedback, LLMs dedicated towards grading examinations, and even AI teachers. The applications of AI are rapidly evolving, reshaping the overall teaching and learning landscape. The advent of AI technologies has introduced further opportunities, attracting significant investment into the AI in education industry.

Despite the allure, several drawbacks exist, including academic misconduct from using chatbots to take examinations, reduced human interaction and creativity since information is directly summarised and collated, a bias towards users who are deemed normal by the algorithm, and privacy concerns, to name a few. This event aims to further investigate these topics by posing six thought-provoking questions to a four-person panel for discussion. It will be run semi-formally, encouraging an open conversation between panellists and the audience. You can find the most recent Hot Topics event on the IET YouTube channel to give you a better idea of how the event will be run.

Keywords:: AI in education

ChatGPT

IET

The Digital Teacher: AI in Education

academic misconduct

chatbots

digital technology

machine learning

thought provoking questions

Channels

Communications

Lectures

Speakers

Dr Eng Ofetotse

University of Greenwich, Senior Lecturer in Built Environment

Dr. Eng Ofetotse is a researcher and Senior Lecturer in the Built Environment at the University of Greenwich, where she teaches building physics, renewable energy, sustainability, and construction technology. She is passionate about mentoring young people aspiring to careers in STEM and actively supports initiatives that promote gender diversity in engineering and science. A published researcher, she also serves as a guest editor and reviewer for several leading academic journals. Eng holds a BSc in Quantity Surveying and a PhD in Energy and Environmental Engineering from the University of Reading. Alongside her academic career, she is an experienced consultant, advising organisations on energy management, sustainability, and ESG best practices.
Dr Farrah Arif

Queen Mary School of Business and Management, Senior Lecturer (Associate Professor)

Dr Farrah Arif is a Marketing academic passionate about bridging theory and practice. As a Commonwealth Scholar, she earned her PhD in Marketing from the University of Cambridge's Judge Business School. She is a Harvard Business School–trained academic. She is also a Fellow of the Higher Education Academy (FHEA), UK.With over 20 years of academic and professional experience across the UK, South Asia, and Central Asia, she has taught, led programmes, designed curricula, and collaborated with industry on research and consultancy projects. Her expertise spans digital marketing, influencer strategy, and marketing analytics, underpinned by a strong commitment to pedagogical innovation and learner impact.Currently, she is a Senior Lecturer (Associate Professor) in Marketing and Communications at Queen Mary School of Business and Management, where she serves as Co-Programme Director for the MSc Digital Marketing and Deputy Director Education - Teaching. Her mission is to inspire students and professionals alike to think critically, create strategically, and lead with integrity in a digitally evolving world.
Professor Richard Hill

The University of Huddersfield, Professor of Artificial Intelligence (Agentic AI)

Professor Richard Hill is a Fellow of the IET and a leading authority in Agentic AI and Applied Artificial Intelligence. A Chartered Engineer and National Teaching Fellow, he is known for translating academic research in Agentic AI into practical solutions that transform organisations and learning environments. As Professor of Intelligent Systems at the University of Huddersfield, he helps businesses and educators harness Agentic AI to build intelligent, autonomous systems that enhance productivity, innovation, and decision-making. His work integrates process engineering, generative AI, and enterprise systems to make Agentic AI adoption structured, ethical, and results-driven.
Dr Varuna De Silva

Loughborough University, Professor of AI and Digital Technologies

Varuna De Silva obtained his Ph.D. in Electronic Engineering from University of Surrey in 2011, after his first degree in Electronics and Telecommunication Engineering from University of Moratuwa in Sri Lanka. As a Post-doctoral Research Fellow, Varuna worked as a work package leader of a Large-Scale Integrated Projects "ROMEO", and “BATS” funded by the European Commission. In 2011 Varuna was awarded the “Chester Sall Award” from the IEEE consumer electronic society award, and Vice-chancellor's best Post-Graduate Research student at University of Surrey. Since 2013, he joined Apical Ltd, Now Part of ARM PLC, where he worked as a new algorithms developer for imaging and display systems to be run on efficient hardware platforms. The algorithms he developed were realized in nearly 500 million devices around the globe, and a patented technology for CMOS cameras, for which he is the lead inventor which appeared in nearly 90% of CCTV cameras in the world. In 2016, he assumed duties as a lecturer in digital engineering at Loughborough University, where he was promoted to a Senior Lecturer in Jan 2020 and to Reader in 2023. He is the programme director for MSc in AI and Data analytics. He is the recipient of three UKRI awards, including 2 as the Principal Investigator, in the area of next generation machine intelligence, and complementary industrial funding. His research has attracted £1Mn of funding from UKRI and with colleagues attached to a funding portfolio of in excess of £2Mn. He has actively collborated with industrial partners Chelsea Football Club, Dallas Mavericks (USA/NBA) and Toyota Manufacturing UK.He currently leads the Machine Intelligence Lab at Loughborough University and is the supervisor of 6 post-doctoral research fellow and students, and have graduated 8 PhD students as the supervisor. His team works on Engineering applications of Artificial Intelligence, specifically Multi-Agent learning, and multimodal machine learning, with a vision to scale state-of-the-art AI algorithms to real world Engineering systems. He currently holds a prestigious UKRI fellowship on which he acts as the inaugral Thematic Research Lead in AI and digital technologies for the UK Parliament. As part of this role he advises select committees, and supports research staff with specialist knowledge in AI and digital technologies across various policy issues. On a routine basis he provides expert deep technical advise to parliamentary select committees, which includes science innovation and technology committee, Digital communications and media committee and Joint Committee on Human Rights.

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