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Curricular information is subject to change
Students who successfully complete this module should be able to:
• Define and recognise Big Data and their differences with the data generated in more traditional approaches such as surveys and interviews
• Understand the relevance of social theory to data-driven research
• Discuss the affordances and challenges in relation to materialising concepts central to social theory in the framework of data-driven research
• Outline the main modifications needed for a new framework of social theory that responds to a more solution oriented sociology
Student Effort Type | Hours |
---|---|
Lectures | 24 |
Autonomous Student Learning | 180 |
Total | 204 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Essay: 3000 words essay on a set of pre-defined topics | Coursework (End of Trimester) | n/a | Graded | Yes | 70 |
Presentation: Students will need to present short introductions to different concepts in each lecture | Varies over the Trimester | n/a | Graded | No | 30 |
Resit In | Terminal Exam |
---|---|
Autumn | No |
• Feedback individually to students, post-assessment
Not yet recorded.
Name | Role |
---|---|
Lucia Suchorova | Tutor |