This is a hybrid event; attendees can either join in person or on Zoom. If the latter, please click on the 'Register for this event' button in the top right corner of this webpage, and fill in the form.
If you would prefer to attend in person, the seminar will take place in Room G/8, in the Waterloo Bridge Wing of Franklin Wilkins Building, King's College London, Stamford Street, SE1 9NH. If you are not a member of CRESTEM, please email firstname.lastname@example.org to RSVP.
Recent developments in artificial intelligence (AI) powered by innovations in machine learning based on artificial neural networks are infiltrating all aspects of our lives. These developments can enhance or transform learning. These possibilities to dramatically change education as well as the wider application of AI have implications for what learners and teachers need to understand about AI in education and beyond.
In this seminar Mary Webb will draw on her research work with international groups: EDUsummIT, the International Federation of Information Processing (IFIP) and Informatics for All (I4ALL), to examine these new developments, opportunities and challenges. In EDUsummIT, Mary led a group of researchers, policymakers and practitioners to examine the implications of developments in machine learning for the use of AI for learning. They focused particularly on issues of explainability and accountability as well as the need for literacies that are required for understanding AI and its implications (Webb et al., 2021). Mary has also been working with the two other groups focusing specifically on computing curricula but incorporating AI as an important aspect. First their task force of the education committee of IFIP has, for some years, been researching changes to computing curricula worldwide and I4ALL have developed a framework incorporating AI for Informatics curricula across Europe.
In this talk, Mary will focus on the following questions: How should we incorporate new opportunities associated with rapid developments in artificial intelligence and machine learning into school curricula and learning and how can we deal with the accompanying challenges? What are the implications for educational research?
Reference: Webb, M. E., A. Fluck, J. Magenheim, J. Malyn-Smith, J. Waters, M. Deschênes and J. Zagami (2021). "Machine learning for human learners: opportunities, issues, tensions and threats." Educational Technology Research and Development 69(4): 2109-2130.
Speaker: Dr Mary Webb
Mary Webb is Reader in IT and Education at King’s College London. Mary is internationally recognised for her research on pedagogy across both Computer Science as a subject and the uses of new technologies for learning.
Mary's research has resulted in over 150 publications. Recent research has focused on analysing computing curricula, pedagogy for learning computing and for using digital technologies for learning especially in science education but also in other curriculum subjects. Mary's international collaborations have focused particularly on her work on the IFIP education committee executive and as a member of the Steering Committee of Informatics For All (I4ALL) Coalition For Europe.
Mary also runs a module on recent developments in digital technologies in education on the MA Education, teaches on the PGCE computing and supervises PhD students on AI in education and aspects of learning computing. Previously, Mary taught science and computing in both primary and secondary schools.