2025 Gibbons Lecture Series: “How artificial intelligence is reshaping education”
Do not miss the annual thought-provoking public lectures organised by The School of Computer Science.
Artificial Intelligence offers new opportunities to enhance teaching, personalise learning and improve student outcomes. The 2025 Gibbons Lecture Series explores the role of AI in modern education, examining real-world applications, discussing the impact on teachers and students, and addressing the challenges of interacting with AI. Whether you are an educator, student or policymaker, this series will provide valuable insights into how AI is revolutionising education and what the future holds.
Tuesdays, 13 May – 3 June, 6 PM
6 – 6.30 PM – refreshments (General Library Basement Foyer)
6.30 – 7.30 PM – lecture (LiBB15/109-B15)
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How might AI contribute to solving our educational challenges?
Speaker: Prof Stuart McNaughton, Curriculum and Pedagogy, University of Auckland
Date: Tuesday 13 May 2025
Abstract
Rather than start with the promise of AI, I first introduce the big challenges we face in education in Aotearoa New Zealand. Then ask the question how AI might contribute to solving these. Two overarching concerns are posed as equity and excellence. Contributing to solving these requires solving four system problems: variability in performance, scalability of what works, capability to implement what works and sustainability of what works. AI can contribute assessments for complex cognitive and social emotional skills, and instruction that goes beyond simple tutorial functions. Prototypes of both standalone assessments and games illustrate that promise. These could have direct and indirect effects on each of the four challenges. However, educational change always carries risks. A notable risk with AI is exacerbating the overarching concerns.
Livestream: TBC
Beyond the Computer Lab: Why AI Literacy Matters for Everyone
Speaker: Dr Kathryn MacCallum, Associate Professor in Digital Education and Educational Technologies, University of Canterbury (UC)
Date: Tuesday 20 May 2025
Abstract
Artificial Intelligence (AI) is no longer confined to tech giants and research labs; it underpins everyday experiences from online recommendations to self-driving cars. As AI technologies become increasingly omnipresent, understanding how they work and how they shape our world is essential for every individual—no matter their age or background. This lecture highlights why AI literacy must move beyond the domain of computer science into our classrooms, our homes, and our wider communities. We will explore the foundational principles of AI, dispel common myths, and discuss the implications that AI has on the wider educational sector. Drawing on practical examples and educational initiatives, we will examine how even young learners can develop meaningful AI skills and critical thinking capacities. By cultivating a generation equipped to scrutinise, use, and co-create AI responsibly, we can ensure that all share the benefits of these intelligent technologies.
Livestream: TBC
Exploring the application of AI in Education, in this panel session academics from the Department of Electrical, Computer, and Software Engineering and Te Puna Wānanga School of Māori and Indigenous Education
Speakers: Dr Piata Allen, Te Puna Wananga; Dr Nasser Giacaman, Prof Catherine Watson, and Dr Jesin James, Dept of Electrical, Computer and Software Engineering, University of Auckland.
Date: Tuesday 27 May 2025
Abstract
Exploring the application of AI in Education, in this panel session academics from the Department of Electrical, Computer, and Software Engineering and Te Puna Wānanga School of Māori and Indigenous Education outline their joint projects which include:
Matapaki Atamai Hangahanga, Reflective and Interactive Learning with AI: Written assessments often fail to engage students or provide meaningful, personalised feedback on learning. By integrating verbal conversational AI, we aim to create more engaging assessment activities that encourage deeper reflection and sustain deeper student interest. Offering a reo Māori version of the AI Co-Thinker platform will also support students, who submit coursework and examinations in te reo Māori, to increase their language proficiency.
AI pronunciation coach: This project will develop the first-ever AI-based pronunciation coach for te reo Māori, addressing critical gaps in knowledge about pronunciation feedback in language learning technologies. Mastering pronunciation requires accurate articulation or correct positioning of the mouth and tongue. Currently, AI-based te reo Māori language learning tools fail to provide guidance on articulation.This study aims to establish and define the accepted pronunciation range for te reo Māori in collaboration with Te Hiku Media, leaders in Indigenous language revitalisation through speech technology, and te reo Māori experts. The findings of this research will enable the development of an AI-based te reo Māori pronunciation coach that provides detailed, real-time, culturally aligned feedback to help learners improve their pronunciation and their confidence in interacting with te reo Māori speakers.
Following a brief overview of each project, the panel will engage in a Q&A session around challenges and opportunities for utilising AI in Education in Aotearoa.
Livestream: TBC
I Prompt, Therefore I Code: Adapting Computing Education in the Age of AI
Speaker: Prof Paul Denny, School of Computer Science, University of Auckland
Date: Tuesday 03 June 2025
Abstract
Sure, I’ll write an abstract for your talk! Generative AI is rapidly transforming the landscape of computing, presenting both complex challenges and exciting opportunities. At the professional level, debate continues about the future of software development: will AI largely replace human developers, or will it enhance efficiency and drive an even greater demand for skilled professionals? Similarly, in computing classrooms, where programming has traditionally been the foundation, the ease with which AI models can generate code has prompted an urgent need to re-think teaching, learning, and assessment strategies. In this talk, I will share some attempts to adapt to this evolving challenge, a topic that has become increasingly central to computing education research. I will also take a moment to express my gratitude to those who have supported my academic journey, which began with a Master’s thesis under the supervision of Associate Professor Peter Gibbons; it is an honour to deliver this inaugural lecture as part of the Gibbons Memorial Lecture Series.
Livestream: TBC