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IS40840

Academic Year 2024/2025

Data & Society (IS40840)

Subject:
Information Studies
College:
Social Sciences & Law
School:
Information & Comms Studies
Level:
4 (Masters)
Credits:
10
Module Coordinator:
Professor Kalpana Shankar
Trimester:
Autumn
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

We live in a data-saturated world. Data are collected about us from birth to death and produced by and about us in our daily lives. Data are a resource, a commodity, and sometimes a threat. It is impossible to live a life without being “datafied”; even attempting to do so can be considered suspicious. In this module, we examine some of the many ways in which the datafication of society is creating both opportunities and problems for citizens, policy-making, cultures, and societies. The module begins with exploring and defining relevant concepts such as algorithms, Big Data, and platforms, then delves deeply into a range of topics including data infrastructures, “smart cities”, open data, “data for good”, data and bodies, data justice, and biometrics. Readings will be drawn from science & technology studies, information studies, anthropology, and communication and media.

About this Module

Learning Outcomes:

• Define and analyse algorithmic processes, Big Data, and related terms with respect to their importance to contemporary societies
• Recognise the interconnections between data, infrastructures, collection and dissemination technologies, software, platforms and how data are produced and used
• Identify some ways in which groups and communities are using to make more informed choices and decisions for human well-being
• Identify specific concerns and harms related to datafication
• Demonstrate an informed and critical approach to understanding data power and politics

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

180
Lectures

24
Total

204

Approaches to Teaching and Learning:
Lecture; in-class discussion; hands-on classroom based activities

The module policy on the use of generative AI applications for assessments is that such applications are not permitted and evidence of the use of such applications for assessments constitutes academic misconduct.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (Open Book): Online timed exam Week 14 Graded No
50
 No
Exam (Open Book): Online exam that is open notes/open book Week 8 Graded No
50
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

feedback on each assessment will be given on Brightspace

Name Role
Lauren Teeling Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Fri 09:00 - 10:50
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