PSDP Masterclass 1: Robot Overlords: Lessons learnt from co-designing a large collaborative course for interdisciplinary learners
| Dates: | 28 October 2020 |
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| Times: | 10:00 - 12:00 |
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| What is it: | Workshop |
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| Organiser: | Faculty of Biology, Medicine and Health |
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| Who is it for: | University staff, Adults |
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| Speaker: | Professor Andy Brass, Dr Caroline Jay, Dr Iliada Eleftheriou |
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Last year we developed a new UCIL course unit, designed to prepare any of our undergraduates for a world in which Artificial Intelligence and Machine Learning is becoming increasingly prevalent. Our students need to be prepared for the AI revolution – to understand the impact it will have on society, and to possess the knowledge that will allow them to be active participants in shaping the future of this important area.
We therefore worked with UCIL and student representatives to develop our course in this area – a first in the world. For the course to work there were requirements it needed to fulfil: it had to be interdisciplinary, introduce all students to some basic coding, responsive to a rapidly moving area, work with students as partners. All this needed to be developed for a surprisingly large initial cohort (over 100 students) and with no previous experience or template for developing this type of course.
In this masterclass we will be sharing the learning we developed as a part of this journey - the successes and failures - to help show how some new pedagogic strategies and improved teaching infrastructure can help us develop courses to prepare our students for the challenges of 21st century life.
To book a place, please go to the Training Catalogue at https://app.manchester.ac.uk/FBMHS5203
Speakers
Professor Andy Brass
Role: Professor of Bioinformatics
Dr Caroline Jay
Role: Lecturer in Empirically Sound Software Engineering
Dr Iliada Eleftheriou
Role: Lecturer in Healthcare Sciences
Travel and Contact Information
Find event
The event will take place online via Zoom and you will get the link once you have reserved your place at https://app.manchester.ac.uk/FBMHS5203
