Skip to main content

Study information

Programme Specification for the 2023/4 academic year

MSc Social Data Science

1. Programme Details

Programme nameMSc Social Data Science Programme codePTS1HPSHPS08
Study mode(s)Part Time
Full Time
Academic year2023/4
Campus(es)Streatham (Exeter)
NQF Level of the Final Award7 (Masters)

2. Description of the Programme

Policy-making in all sectors has become more data driven and advanced training in issues of data use, data sharing, transparency, and accountability are important for both the public and private sectors. Unlocking the potential of collecting, sharing and analysing massive amounts of administrative and economic, social and political data to bring economic and social benefits requires individuals trained in both policy analysis and data analytics. 

 
The MSc in Social Data Science will offer rigorous data analytic training (e.g. data analysis, evaluation, decision-making) alongside a specialisation in a policy subfield (e.g. social and family policy, economic and public policy, environment, criminal justice, security). This MSc is an extension of the successful Q-Step programme training social scientist undergraduates in quantitative methods, and is one of three data science MSc delivered at Exeter. The MSc in Applied Social Data Science provides training for graduates who want to focus on the application of data analytics to the study of global uncertainties and societal/policy challenges. 
 
It is anticipated that the MSc would provide a clear pathway for recruiting excellent PhD students. Because of the need for excellent and confident data analysis skills in several sectors; Policy, business, criminal justice etc these may well be either partially or fully funded. Investment in quantitative social research methods is a priority area for the ESRC, so the MSc could provide a pathway for a CASE (ie, co-funded by a non-academic organisation) ESRC +3 studentship.

3. Educational Aims of the Programme

1. Strengthen the training in and understanding of data analysis and data-driven, evidence-based research methods and decision-making
2. Equip you with the numeracy, applied statistical and data handling skills sought by employers and/or as required as preparation for doctoral study.
3. Equip you with the technical understanding of a range of data analytic techniques (e.g. data visualisation) and the practical software/programming skills to implement these methods to address their own research questions
4. Develop your ability to apply data analysis techniques to a range of substantive and policy related questions.
5. Provide an opportunity for you to undertake project based research in the form of a dissertation.

The goal of the MSc is to equip you with the skills to apply evidence based practice in a range of subject areas using social and economic data. At the core of the programme is data analytics for the social sciences and policy analysis but it also offers training in substantive subject areas based on your interests. The programme is designed to provide high quality training, both to enable you to carry out your own research and to equip you to pursue other professional research activities subsequently

4. Programme Structure

5. Programme Modules

The following tables describe the programme and constituent modules. Constituent modules may be updated, deleted or replaced as a consequence of the annual programme review of this programme.

The MSc Applied Social Data Science programme is a 1-year programme of study at National Qualification Framework (NQF) level 7 (as confirmed against the FHEQ). This programme takes place across three academic terms. The programme is also divided into units of study called ‘modules’ which are assigned a number of ‘credits’. The credit rating of a module is proportional to the total workload, with 1 credit being nominally equivalent to 10 hours of work. Taught credits amount to 120 credits with an additional 60 credit project with partner or a research dissertation.

Stage 1


In addition to the 120 credits of compulsory modules, you must take 60 credits of optional modules from Sociology, Philosophy and Anthropology (SPA) and Politics. Suggested relevant modules are listed below, or you may take any postgraduate optional modules from the department of Social and Political Sciences, Philosophy, and Anthropology. View option modules for SPA and for Politics.

Compulsory Modules

CodeModule Credits Non-condonable?
SSIM915 Statistical Modelling 15Yes
SSIM916 Machine learning for social data science 15Yes
SSIM917 Programming for Social Data Science 15Yes
SSIM918 Data Visualisation 15No
SSIM907 Policy Analytics: Dissertation or Research Consultancy Project 60Yes

Optional Modules

CodeModule Credits Non-condonable?
MSc Applied Social Data Science 2023-24
SOCM033 Data Governance and Ethics 15 No
SSIM913 Longitudinal Data Analysis 15 No
SPAM001 Causal Inference and Evidence Based Policy Making 15 No
POLM897 Surveys and Experiments: Design, Implementation and Analysis 15 No

6. Programme Outcomes Linked to Teaching, Learning and Assessment Methods

Intended Learning Outcomes
A: Specialised Subject Skills and Knowledge

Intended Learning Outcomes (ILOs)
On successfully completing this programme you will be able to:
Intended Learning Outcomes (ILOs) will be...
...accommodated and facilitated by the following learning and teaching activities (in/out of class):...and evidenced by the following assessment methods:

1. Understand the relationships between, and the rationale for, particular data analysis methods and be able to select appropriate strategies for research and/or evaluation and analysis at relevant stages of the policy process;
2. Be competent at implementing a range of data analysis techniques using a variety of appropriate computer packages including e.g. R, and Python;
3. Be proficient in using data from large scale surveys, administrate data and open data sources;
4. Construct new data sets from a variety of open sources;
5. Be competent in descriptive and inferential statistics and use, model and interpret multivariate statistical data;
6. Critically evaluate and interpret your own research findings using advanced quantitative methods and refine research in light of findings
7. Understand the stages of the policy-making process.

All 10 ILOs are achieved through a variety of activities from traditional lectures and tutorials to group work, computer lab work, simulations and technical trainings in specialist software and techniques. 

 
1 and 7 are developed across the programme, in the core modules. 
 
2-6 are further developed and ensured through the dissertation or project. 
 
2 is ensured and developed further through the Mathematics and Programming module. 
 
Learning outcomes are also ensured through assignments in the term-two required module, dissertation skills and the dissertation 

These skills are summatively assessed through a combination of term-time essays, lab assignments, presentations, examinations and dissertation work. The combination of and length of essays, lab assignments, presentations and exams will vary from one module to the next according to credit value in conformity with College Assessment Norms.

Intended Learning Outcomes
B: Academic Discipline Core Skills and Knowledge

Intended Learning Outcomes (ILOs)
On successfully completing this programme you will be able to:
Intended Learning Outcomes (ILOs) will be...
...accommodated and facilitated by the following learning and teaching activities (in/out of class):...and evidenced by the following assessment methods:

1. Gather, organise and deploy evidence and information from a variety of primary and secondary sources.
2. Define researchable problems and formulate questions and hypotheses;
3. Construct reasoned argument, synthesize relevant information, and critically analyse subject material.
4. Manage your own learning self-critically.
5. Carry out high quality and informed research independently;
6. Be competent in critically evaluating the collection, analysis and interpretation of structured and unstructured data using a variety of techniques;

These skills are developed throughout the degree programme, with progression to independent control of the process by the dissertation phase (term 3). 

 
1 thru 3 are developed through self assessment of assignments, staff feedback on formative assignments, and student self-appraisal in core modules. 
 
5 is developed from in-class training and lectures (qualitative research module)
 
1, 2, 3, 4 and 5 are developed through independent research (the dissertation) 
 
6 is developed through assignments, the dissertation and independent reading.

1 and 2 are assessed through term-time essays, oral presentations, and examinations. 3 is assessed through essays 

 
4 is assessed through assignments (dissertation skills), project report (second-term required module) and the dissertation 
 
5 and 6 are assessed through the dissertation

Intended Learning Outcomes
C: Personal/Transferable/Employment Skills and Knowledge

Intended Learning Outcomes (ILOs)
On successfully completing this programme you will be able to:
Intended Learning Outcomes (ILOs) will be...
...accommodated and facilitated by the following learning and teaching activities (in/out of class):...and evidenced by the following assessment methods:

1. Communicate effectively and fluently in speech and writing;
2. Use information and communication technology (ICT) for the retrieval and presentation of information;
3. Work independently, demonstrating initiative, self-organization and time-management;
4. Collaborate with others to achieve common goals
5. Perform effectively – under the supervision of a mentor – in a demanding and international work environment
6. Understand the role of data and evidence based decision making in public and commercial life;
7. Understand the principles of policy-relevant research – including the development of evidence-based policy;
8. Develop good communication skills when delivering material to inter-disciplinary audiences.
9. Communicate complex quantitative methods to a lay audience with policy or societal focus;

1, 8, 9 are developed in presentations, class discussion and written assignments.

 
2 and 3 are developed through presentations, written assignments and the work placement 
 
4 is developed through group work in module seminars 
 
5 developed through supervision sessions 
 
6 and 7 are developed through module readings, class discussion and written assignments

1, 3 and 9 are assessed through presentations, written assignments, and examinations. 

 
2 and 6 are assessed through written assignments that require computer software packages for the retrieval and presentation of information. 
 
7 is assessed through written work for modules 
 
4 is assessed through group discussion and presentations in seminars 
 
5 and 6 are assessed through the assignments 
 
8 is assessed through presentations 

7. Programme Regulations

Classification

Full details of assessment regulations for all taught programmes can be found in the TQA Manual, specifically in the Credit and Qualifications Framework, and the Assessment, Progression and Awarding: Taught Programmes Handbook. Additional information, including Generic Marking Criteria, can be found in the Learning and Teaching Support Handbook.

8. College Support for Students and Students' Learning

9. University Support for Students and Students' Learning

Please refer to the University Academic Policy and Standards guidelines regarding support for students and students' learning.

10. Admissions Criteria

Undergraduate applicants must satisfy the Undergraduate Admissions Policy of the University of Exeter.

Postgraduate applicants must satisfy the Postgraduate Admissions Policy of the University of Exeter.

Specific requirements required to enrol on this programme are available at the respective Undergraduate or Postgraduate Study Site webpages.

11. Regulation of Assessment and Academic Standards

Each academic programme in the University is subject to an agreed College assessment and marking strategy, underpinned by institution-wide assessment procedures.

The security of assessment and academic standards is further supported through the appointment of External Examiners for each programme. External Examiners have access to draft papers, course work and examination scripts. They are required to attend the Board of Examiners and to provide an annual report. Annual External Examiner reports are monitored at both College and University level. Their responsibilities are described in the University's code of practice. See the University's TQA Manual for details.

(Quality Review Framework.

14. Awarding Institution

University of Exeter

15. Lead College / Teaching Institution

Faculty of Humanities, Arts and Social Sciences (HASS)

16. Partner College / Institution

Partner College(s)

Not applicable to this programme

Partner Institution

Not applicable to this programme.

17. Programme Accredited / Validated by

0

18. Final Award

MSc Social Data Science

19. UCAS Code

Not applicable to this programme.

20. NQF Level of Final Award

7 (Masters)

21. Credit

CATS credits

180

ECTS credits

90

22. QAA Subject Benchmarking Group

23. Dates

Origin Date Date of last revision