| Unit name | Arts in the Age of Data |
|---|---|
| Unit code | AFAC20007 |
| Credit points | 20 |
| Level of study | I/5 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Dr. Perry |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | Arts Faculty Office |
| Faculty | Faculty of Arts |
Why this unit is important?
Twenty-first century society is awash with data. Whether collected by governments, technology companies, or individuals, we produce and interact with vast quantities of numerical information about almost every aspect of our lives. Indeed, the vastness of the data collected and our increasing reliance on it to make decisions has led some to claim that we are living through ‘the age of data’. Yet this turn towards data has a much longer history, and the disciplines that make up the Liberal Arts have been just as affected by it as the social and physical sciences. This unit therefore encourages students to understand and contextualise recent developments as part of a longer story in which societies and Liberal Arts subjects both turned to quantification and revealed the limits of what we can know through data alone.
How this unit fits into your programme of study?
As part of the Liberal Arts programme, this unit aims to empower you to become a critical citizen in the digital era. That sounds a bit grandiose, but the truth is that most of the forces remaking our political, social, cultural, and economic worlds are invisible unless you can download, manipulate, and visualise data. Likewise, if we want to challenge and disrupt long-held assumptions (one of the defining aims of the Liberal Arts), we increasingly need to tell our stories through data and reveal the limits of other people's data.
The unit aims:
• to develop understanding of how and why society and the Liberal Arts became increasingly quantitative;
• to enhance students’ abilities to comprehend and evaluate data sources, analyses, and visualisations;
• to develop good practice in data mining, processing and analysis.
An overview of content
Students will primarily explore the above issues by constructing their own data-based projects supported by workshops and a lecture series. They will have the opportunity to work in small groups with a tutor on projects which assemble a dataset and then use basic data science skills to answer research questions and visualise their findings. They will then either extend these findings further through a personal data project report or further engage with the key conceptual ideas, histories and contemporary issues through an essay project.
This is not a maths unit. It's about making things with data, data which could range from the number of crimes committed in 19th Century London to the gender pay gap in 21st Century Britain. In particular, we will help you ask interesting questions, go out and get or recover data, bring datasets together to make a powerful argument, and set this in the context of a bigger picture: the story of how our data society emerged, the Liberal Arts role in that story, the reasons why we have the data we have, and the power relations and inventions that link together a world of AI, Netflix, facial recognition, and climate change models.
How will students, personally, be different as a result of the unit?
Our aim is for you to become a particular kind of data scientist - a "data humanist" is probably the best term. Whereas others focus on collecting raw data from surveys and experiments or inventing new techniques to detect patterns, your unique skillset will combine powerful digital capabilities with the historical and cultural knowledge needed to make a case for change, shift our view of past societies, and raise a sceptical eyebrow about a stat in the news, a data vis on Twitter, or a promise on a bus.
On successful completion of the unit, students will be able to:
Teaching will be delivered through a combination of synchronous and asynchronous activities, including lecture content, interactive sessions, data challenges, and supporting activities for project work. Students will be expected to participate on a weekly basis. There will be opportunities for tutor and peer feedback.
Tasks which help you learn and prepare you for summative tasks (formative):
Practice data challenge (0%, Not Required for Credit)
Peer-review of infographic (0%, Not Required for Credit)
Tasks which do not count towards your unit mark but are required for credit (zero-weighted):
Data challenges (0%, Pass/Fail Required for Credit) [ILOs 2, 3, 5]
Tasks which count towards your unit mark (summative):
Group infographic (40%) [ILOs 2, 3, 4]
Individual project, 2000 words (60%) [ILOs 1, 4, 5]
For the individual project, students will choose between either a data-driven report that extends their group project independently and contextualises this in the ‘age of data’ or an individual essay that further engages with key ideas and issues raised in the lecture series.
When assessment does not go to plan
When required by the Board of Examiners, you will normally complete reassessments in the same formats as those outlined above. However, the Board reserves the right to modify the form or number of reassessments required. Details of reassessments are normally confirmed by the School shortly after the notification of your results at the end of the academic year.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. AFAC20007).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
