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Unit information: Arts in the Age of Data in 2020/21

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. James Freeman
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Arts Faculty Office
Faculty Faculty of Arts

Description

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.

Students will primarily explore these issues by constructing their own data-based projects. 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.

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;
  • and to develop good practice in data mining, processing and analysis.

Intended learning outcomes

By the end of the unit students will be able to:

  1. demonstrate an understanding of when, how and why society and the Liberal Arts became increasingly quantitative;
  2. identify when is it appropriate to apply statistical measures and visualisations;
  3. demonstrate basic data science skills, through the appropriate and independent use of software such as Excel;
  4. design and develop a data-based project to answer group and individual research questions;
  5. critically evaluate the suitability, production and presentation of quantitative information.

Teaching details

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.

Assessment Details

Data challenges (Pass/Fail) [ILOs 2, 3 and 5]

Group Infographic (40%) [ILOs 2, 3, 4]

Individual 2,000-word Project Report (60%) [ILOs 1, 4, 5]

Reading and References

Brignell, J.E. (2000) Sorry, wrong number!: the abuse of numbers. Stockbridge: Brignell Associates

Crook, T. and O’Hara, G., (ed.) (2011) Statistics and the public sphere: numbers and the people in modern Britain, c.1800-2000. London: Routledge

Freeman, M. (2010) Quantitative skills for historians. Warwick: Higher Education Academy

Hudson, P. (2000) History by numbers: an introduction to quantitative approaches. London: Edward Arnold

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