AI in Education special: Episode 1 - Strategic integration of GenAI across educational programmes...
LivUni - The Academy
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AI in Education special: Episode 1 - Strategic integration of GenAI across educational programmes...
32 просмотра · 5 дней назад
LivUni - The Academy
23 подписчика
32 просмотра · 5 дней назад
In this first episode, I chat with Paul Craig who is the AssociateDean for Learning and Teaching within the Department of Computing at Xi’an Jiaotong-Liverpool University. Paul has recently published work on strategic integration of Generative AI across whole programmes and I was interested in both his experience of this approach and the wider conversations that may have led to within the department and beyond.Paul Craig has been a researcher working in the area of Information Visualization for around 15 years. His PhD studied the use of Animated Information Visualization for the Exploratory analysis of microarray time-course data, with Professor Jessie Kennedy at Edinburgh Napier University in 2006, and has since worked as a research fellow on projects for the National Science Foundation, Scottish enterprise, and the European Community in the areas of taxonomy, bioinformatics and intelligent interfaces. He is currently working on multi-device interfaces and explainable information visualization for antibiotic residue monitoring.The Academy’s Developing Practice Podcast is produced by The Academy, University of Liverpool. The role of the Academy is to promote and enable organisational excellence through the strategic development of the University’s people and practices. To find out more about the work of The Academy check out: https://www.liverpool.ac.uk/the-acade...
Music & FX: This podcast uses sounds from https://freesound.org/s/417560/... music from https://www.purple-planet.com (https://www.purple-planet.com/)
Reading list: Paul Craig, Thomas Selic, and Ling Wang (2026) alayered strategy for integrating generative AI into practice-led computer programming education. Developing Academic Practice, https://doi.org/10.3828/dap.2026.5