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Artificial Intelligence, Work and Learning (EDPS0225)

Key information

Faculty
IOE
Teaching department
Education, Practice and Society
Credit value
30
Restrictions
N/A
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module addresses one of the most challenging issues facing all societies - the 4th Industrial Revolution (4IR) and the increasing deployment of Artificial Intelligence (AI) in all sectors of economic, political and social life: issues that are, at present, not addressed in any other module offered within the Institute. The overarching aims of this module are to:

  • explore the Work-AI-Learning nexus at a conceptual level;
  • address the changing relationship between work, technology and skill as a result of the increasing deployment of AI in workplaces and societies at a practical level;
  • consider the implications of the above changes for learning in different contexts.

The module has been designed to be taken by anyone, irrespective of the MA on which they are enrolled

Participants will be able to:

  • understand key terminology in discussions about work and technology, such as Fordism, Post Fordism, and technological determinism and shaping.
  • understand the importance of developing a historical perspective on the technological change and its implications for work.
  • appraise critically the relationship between technological change and its implications for skill and learning in the contexts of education and work.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 3 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
100% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
0
Module leader
Professor David Guile
Who to contact for more information
crystal.pereira@ucl.ac.uk

Intended teaching term: Term 3 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
100% Coursework
Mark scheme
Letter Grade

Other information

Number of students on module in previous year
31
Module leader
Professor David Guile
Who to contact for more information
crystal.pereira@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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