Course Catalogue

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You will get an overview of the principles of good data visualisation and working knowledge on how to critically interpret graphs, as well as hands-on practice on creating data visualisations in different contexts. This course will also look into the psychology behind how we interpret graphical illustrations of data, why data visualisations are often misleading, and how to present your data ethically and transparently. Each week will be split into a lecture going over theoretical and empirical aspects of the psychology of data visualisation or an interpretation seminar, and a practical lab where you practice these concepts with different data sets using R.

Weekly two-hour lectures consisting of teaching and practical

Successful completion of level 3H psychology single honours

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Practical skills assessment (10%, individual submission)
Students are given a number of practical skills homeworks to complete. These are marked as a participation grade and the code itself is not assessed - if a student submits all practical skills homeworks and demonstrates reasonable engagement with the tasks, they will get full marks for this component.

Interpretation exercise (15%, individual submission)
Students are provided a number of graphs and they will be asked to interpret, evaluate and suggest improvements based on the theory of data visualisation covered in lectures.

Data visualisation report (written coursework, 75%, individual submission)

Students will be asked to produce a report to address a brief from a hypothetical organisation (students select one from a number of different briefs). The report will include a number of data visualisations to report the underlying data, a brief verbal interpretation and a written reflection.

The assessments on this course rely heavily on visual representation of data, which can be challenging to students with visual impairments. The interpretation exercise requires visually inspecting a number of graphs; alternative assessment will be provided when required. For the data visualisation report, the assessment brief will be fully written with no visual representations of data.

The aim of the course is to enhance students' understanding of the psychology behind how we interpret data visualisations, good data visualisation principles, and the responsibility associated with creating representative and transparent data visualisations. The course will also allow students to develop their ability to produce and interpret complex data visualisations as critical consumers of data via skills-based learning.

By the end of this course students will be able to:

■ Critically appraise the role of perceptual and cognitive mechanisms underpinning the interpretation of data visualisations

■ Critically evaluate and interpret data visualisations in different contexts

■ Critically appraise the role of data visualisation in communicating your data

■ Produce appropriate visualisations considering inclusivity and presentation context

■ Produce advanced data visualisations that effectively and transparently communicate complex data.