Data Literacy for Justice - online 2025 and 2026 entry

For more details, including weekly contact hours, teaching methods and assessment, please see the module catalogue. The modules are examples from previous academic years and may be subject to change before you start your course.

• MSc

  Students studying towards an MSc must take two compulsory modules and at least six optional modules.

  Compulsory modules

  • Theoretical Foundations of Social and Environmental Justice: introduces theories and contemporary debates in the areas of social and environmental justice – from climate and ecological to health and reproductive justice - allowing students to develop an understanding of how to frame a justice-led campaign of interest to them.
  • Science Communication and Public Engagement: builds a range of skills for translating science into action, ranging from finding and evaluating sources of information to using social media to communicate the science and engage different audiences.

  Optional modules

  Two to five modules must be taken from the following options:

  • Welcome to Data: Rubbish in; Rubbish out: encourages critical reflection on data including sources, types of data, sampling design, as well as how data can be used and abused. It also introduces open-source statistical software, such as R, as well as principles of reproducible data analysis.
  • Statistical Foundations: introduces basic statistical concepts, methods to explore patterns in data, and skills in interpreting statistical results. The module is structured around the use of statistics to understand social or environmental processes, using real datasets and surveys. Students are supported through a self-guided practical exercise.
  • Quantitative Methods: focuses on analytical techniques and approaches, the rationale behind data models, and the underlying assumptions of those models, as well as the pros and cons of their use. The lectures cover quantitative models such as regression models, event history models, time series models, and causal inferences.
  • Advanced Data Visualisation: introduces theoretical foundations behind data visualisation and elaborates on principles of communicating large and complex data. Through interactive practicals, this module provides the skills and tools to produce publication-quality scientific figures and maps.
  • Introduction to Spatial Data Science: introduces Spatial Data Science (SDS), including why we need SDS for everyday life activities. Spatial point pattern analysis tools and methods for decision support in space are part of this module.
  • Advanced Spatial Data Science: builds on knowledge and skills covered in Introduction to SDS, and extends to topics such as spatial autocorrelation, interpolation and Geographically Weighted Regression (GWR), to understand how relationships vary through space.

  And at least one module must be taken from the following options:

  • Advanced Science Communication and Public Engagement: the module will look at how to consider and incorporate issues of justice, equity, diversity, and inclusion, including accessibility, into science communication for public engagement endeavours. Covering topics from stop-motion animation to planning a successful social media campaign, and organising more traditional community outreach and engagement.
  • Tools for Evaluating Impact: The module will provide familiarity with the basics of: theories of social change; understanding impact research design; engaging stakeholders; participatory approaches; and critically reading Impact Assessment Reports.
  • Visuals for Policies and Publics: this module covers the core principles of creating and evaluating visual content, understanding copyright law, and designing informative and engaging data visualisations and infographics.

  Finally, MSc students must submit a three-part individual research project (worth 60 credits) developed in dialogue with their supervisor and the module convener, consisting of:

  • a literature review (5,000 word limit) (40%)
  • an appropriate applied piece, such as a policy brief, in which case 3000 words maximum (40%)
  • a 1000-word reflection on their experience of translating academic research into practice (20%).

  At MSc level you may need to take certain optional modules in combination with each other.

• PGCert or PGDip

  Students studying towards a PGCert and a PGDip take the following compulsory modules:

  • Theoretical Foundations of Social and Environmental Justice: introduces theories and contemporary debates in the areas of social and environmental justice.
  • Science Communication and Public Engagement: builds a range of skills for translating science into action, ranging from finding and evaluating sources of information to using social media to communicate the science and engage different audiences.

  And two to four optional modules from the following.

  • Welcome to Data: Rubbish in; Rubbish out: this module encourages reflection on the use of statistics in society and social/environmental debate, as well as introducing exploratory quantitative data analysis via an open-source platform (for example, R).
  • Statistical Foundations: introduces basic statistical concepts, methods to explore patterns in data, and skills in interpreting statistical results. The module is structured around the use of statistics to understand social or physical and environmental processes, using real datasets and surveys.
  • Quantitative Methods: focuses on analytical techniques and approaches, the rationale behind data models, and the underlying assumptions of those models, as well as the pros and cons of their use.
  • Advanced Data Visualisation: elaborates on principles of producing publication-quality scientific figures, enhancing graphs and charts, and generating maps in R.
  • Introduction to Spatial Data Science: introduces Spatial Data Science (SDS), including why we need SDS.
  • Advanced Spatial Data Science: builds on knowledge and skills covered in Introduction to SDS, which could include, for example, Geographically Weighted Regression (GWR).

  In addition to the above, students studying towards a PGDip will take at least one module from the following:

  • Advanced Science Communication and Public Engagement: explores the incorporation of issues of justice, equity, diversity, and inclusion (JEDI), including accessibility, into science communication for public engagement endeavours. We may cover topics from stop-motion animation to organising more traditional community outreach and engagement.
  • Tools for Evaluating Impact: The module will provide familiarity with the basics of: theories of social change; understanding impact research design; engaging stakeholders; participatory approaches; and critically reading Impact Assessment Reports.
  • Visuals for Policies and Publics: Creative Visual Arts for Sciences: covers the core principles of evaluating and creating content, understanding copyright law, and designing data visualisations and infographics.

  At both PGCert and PGDip levels, you may need to take certain optional modules in combination with each other.