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, and a practical lab where you practice these concepts with different data sets using R.

Five 2-hour teaching slots (once a week) - which consist of 1 hour lecture, 1 hour practical lab on-campus

Successful completion of level 3H psychology single honours

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Data visualisation report (written coursework, 100%, individual submission, max 1000 words)

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). In the brief, students will be given a dataset and information about what the respective organisations need in the report. The report will include a number of data visualisations to report the underlying data, as well as a brief verbal interpretation of each of the visualisations they are creating. Students will also be asked to provide a written reflection of their report, in which they are asked to explain why they have chosen these visualisation methods.

In comparison to the reports students produce on other psychology courses, this assessment relies more heavily on visual representation of data, which can be challenging to students with visual impairments. As a part of the course, students will be taught how to make their graphs accessible (e.g. colour blind friendly, how to produce alternative text in R). The instructions in the assessment brief given to the students will be fully written and not include any graphical displays of data to ensure accessibility of assessment.  

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

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

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

■ Critically evaluate and interpret data visualisations in different contexts

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

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.