Seminar: Dr Rebecca Eynon 'AI and Lifelong Learning: fragmentation and individualization'

AI and Lifelong Learning: fragmentation and individualization

Dr Rebecca Eynon, University of Oxford

12-1.30pm, Friday 8th February 2019, Outreach Building Room B1.11-1, Moray House School of Education, Holyrood Road, EH8 8FP

Access the Outreach building from Holyrood Road next to Levels cafe.  Room B1.11-1 is in the basement.

Link to sign up

Abstract

The role of artificial intelligence for learning is again attracting attention in academic, policy and commercial fields. This intensification of focus is particularly interesting in discussions around Lifelong Learning, where Lifelong Learning is not only seen as a way to prepare society for an ‘AI future’ but a context where AI could be ‘harnessed’ to facilitate learning opportunities, process and outcomes.  This talk will present findings from a mixed method study that explores the role of different actors in shaping the discourse and practice of the use of AI in Lifelong Learning; and highlights the social and educational implications of this fragmented landscape.

 

Biography

Rebecca Eynon is as Associate Professor and Senior Research Fellow at the University of Oxford. At the University she holds a joint academic post between the Oxford Internet Institute (OII) and the Department of Education. Her research explores the relationships between education, the Internet and inequalities, and she has carried out projects in a range of settings (higher education, schools and the home) and life stages (childhood, adolescence and late adulthood). Rebecca is co-editor of Learning, Media and Technology. She is co-author of Teenagers and Technology (Routledge, 2013) and Education and Technology: Major Themes (Routledge, 2016). Her work has been supported by a range of funders including the British Academy, the Economic and Social Research Council, the European Commission, Google and the NominetTrust.

 

Date of Event
Event Leader
Sian Bayne
Location
Outreach Building B1.11-1
Research Area
Data Society