University of St Andrews - Online
MSc / PGDip / PGCert in Data Literacy for Justice - OnlineOnline United Kingdom
DURATION
1 up to 3 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
31 Aug 2025
EARLIEST START DATE
Aug 2025
TUITION FEES
GBP 18,000 *
STUDY FORMAT
Distance Learning
* for MSc part-time | GBP 12,000 - for PGDip part-time | GBP 6,000 - for PGCert part-time
Introduction
Tackle the world's most pressing social, environmental, and sustainability challenges by using data-driven approaches to drive positive, justice-led change.
Why study this course?
This fully online programme will provide you with skills in critical thinking, statistical modelling, spatial data, data visualisation and science communication to allow you to tackle some of society’s biggest challenges. We’ll teach you how to effectively interpret and use data to drive meaningful change, which we relate to the three pillars set out below:
- Social justice: to create a fair and just society where all individuals have equal access to opportunities, resources, and rights.
- Environmental justice: where no group of people should bear an unfair share of negative environmental impacts.
- Sustainability: meeting the needs of the present without compromising the ability of future generations to meet their own needs.
First, our experts introduce the conceptual foundations of sustainability and the theories underpinning social and environmental justice, which serve as the basis for our practical case studies.
Second, you will develop statistical and spatial data science capacities, with an emphasis on generating compelling evidence from data. This includes critical engagement with the use and misuse of data, the inherent biases in big data, and data ethics, alongside training in a range of statistical approaches, from foundational to advanced, for analysing diverse datasets.
Finally, the programme draws on science communication and data visualisation techniques, enabling you to present data clearly and effectively for different audiences, including policymakers and the general public.
This MSc is designed for students from diverse educational backgrounds, with varying skill levels and interests. It's built-in flexibility allows you to select the pathway that best suits your needs, letting you work with the types of data most relevant to your current or future field of practice.
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Admissions
Scholarships and Funding
We are committed to supporting you through your studies, regardless of your financial circumstances.
Successful entrants starting online studies at Master's level can apply for scholarships of up to £6000 towards the course fees.
- Commonwealth Distance Learning Scholarships Data For Justice (deadline Tuesday, 20 May 2025)
- St Leonard's funding opportunities
- Graduate discount (15% off tuition fees)
Curriculum
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 the 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.
Program Outcome
- Develop your understanding of key issues in social and environmental justice and their sociopolitical contexts, and theories of social change.
- Build your confidence in responsibly collecting quality data, including key concepts for data analysis, spatial data science, data modelling using real datasets, and using open-source platforms.
- Construct engaging and accessible narratives with data, including data visualisation for lay and expert audiences.
- Practice effective public engagement strategies, including using journalism outlets and social media for impactful communication.
- Enjoy the flexibility to start at the beginning if you don't have a background in statistics, or take a more advanced class to enhance your existing skills.
- Boost your impact potential by diversifying your science communications and data visualisation toolboxes.
Program Tuition Fee
Career Opportunities
Our graduates work in a variety of organisations in the public and private sectors, in roles including data analyst or scientist, research officer, investment or development manager, consultant, policy advisor, environmental economics, fundraising and communications, higher education, consultancy, and research.
Student Testimonials
Why study at University of St Andrews - Online
Wherever you are, you can take St Andrews with you. Online Master's at the University of St Andrews combine all the benefits of studying at one of the world's oldest and best universities, with all the advantages of flexible, personalised learning.
Program delivery
Teaching
A mix of recorded lectures, live question and answer sessions, peer-to-peer learning, digital resources such as podcasts, and online forums.
Flexible schedule
You will access modules and components at a pace and on a timetable that suits your work and study environment.