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Artificial Intelligence and Data Analytics in Education (CCME0123)

Key information

Faculty
IOE
Teaching department
Culture, Communication and Media
Credit value
30
Restrictions
Any student wishing to take this module from outside of the programme (MA Education and Technology) must apply to do so by submitting a short statement about why they want to join and how their background relates to the subject. The statement should be sent to ioe.ma.edtech@ucl.ac.uk
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

The application of Artificial Intelligence (AI) in Education is of critical importance to the way that both fields of Education and AI evolve in the future as well as to influencing the direction the present debates in an informed way. This module will provide a wide range of students, including teachers, educators and current or potential start-up employees or aspiring entrepreneurs with an opportunity to reflect on their position to key debated topics related to Artificial Intelligence in Education and Data Analytics, and an introduction to fundamental concepts therein, along with an opportunity for practical application of those concepts to specific educational problems.

This module may be of interest also to students studying topics in media and education as it will tackle myths, ethical questions and future perspectives related to Artificial Intelligence in general and in Education in particular.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 2 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

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

Other information

Number of students on module in previous year
0
Module leader
Professor Kaska Porayska-pomsta
Who to contact for more information
ioe.ma.edtech@ucl.ac.uk

Intended teaching term: Term 2 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

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

Other information

Number of students on module in previous year
7
Module leader
Professor Kaska Porayska-pomsta
Who to contact for more information
ioe.ma.edtech@ucl.ac.uk

Intended teaching term: Term 2 听听听 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
1
Module leader
Professor Kaska Porayska-pomsta
Who to contact for more information
ioe.ma.edtech@ucl.ac.uk

Intended teaching term: Term 2 听听听 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
28
Module leader
Professor Kaska Porayska-pomsta
Who to contact for more information
ioe.ma.edtech@ucl.ac.uk

Last updated

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

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Sustainability

For a list of modules related to climate change as well as social and environmental sustainability at 果冻影院, type 'climate' or 'sustainability' into the search. Visit Sustainable 果冻影院 for information on extra-curricular activity on sustainability.

Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed exams and in-class activity will be confirmed by the teaching department for the module.

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