Postgraduate Course: Dissertation (DSTI - SSPS) (PGSP11499)
|School||School of Social and Political Science
||College||College of Arts, Humanities and Social Sciences
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||This is a major piece of independent work which forms the final stage of the MSc programme. It is intended to allow students to demonstrate their ability to organise and carry out a substantial investigation into a problem in data science, according to sound scientific principles. The project involves both the application of skills learnt in the past and the acquisition of new skills. The final submission will be expected to be at a level appropriate for an independent researcher and be a good indication of a student's potential to go on to be a productive researcher in a relevant sub-discipline of Data Science (i.e. Social Data Science). This course is only available to students on the Data Science, technology and Innovation Online Learning MSc.
The project will be supervised by a member of academic staff from SSPS and possibly a co-supervisor appropriate to the context of the research (who may be within another part of the University or may be from an appropriate external organisation).
In this dissertation course you will be working independently on an extended piece of writing which is original and presents new research within it in the form of a sustained argument. The dissertation marks the final stage of your Masters degree and demonstrates that over the course of the programme you have gained the skills and knowledge required to engage in the formal and rigorous process of research. This process entails, but is not restricted to, identifying a suitable research topic, formulating research objectives, organising/analysing data, organising and reviewing relevant literature, devising an appropriate research methodology, reporting results, drawing conclusions and possibly even making relevant recommendations to the wider research community.
The design and conduct of the project will require a high level of commitment and application from the student. The dissertation demonstrates their ability to think scientifically and complete a research report that follows expected academic conventions of style, tone, structuring and referencing. Supervisory support will be supplemented by the detailed project handbook given to all students.
The types of activity involved in each project will vary but will include most of the following:
- a survey of the work that has previously been published in your subject, identifying gaps in the literature;
- describing the broad philosophical underpinning to your chosen research methods, including whether you are using qualitative or quantitative methods, or a mixture of both, and why;
- presenting your own original findings in relation to the phenomenon you have been gathering data about and the wider context in which it is located, in a form that is clear, relevant and simple;
- examining your results in relation to your research questions and in relation to existing research, enabling you to assess the contribution of your research.
Communication with supervisors, including discussion progress and review of draft materials, will be determined by the student and supervisor and is most likely to be carried out by a combination of email and telephone/skype.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| None
Course Delivery Information
|Academic year 2020/21, Not available to visiting students (SS1)
||Block 5 (Sem 2) and beyond
|Course Start Date
|Learning and Teaching activities (Further Info)
Dissertation/Project Supervision Hours 12,
Programme Level Learning and Teaching Hours 12,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework 100% (15.000 words dissertation)
|No Exam Information
On completion of this course, the student will be able to:
- Structure and summarise a body of knowledge relating to a substantial project topic in social data science.
- Critically evaluate previous work in the area.
- Conduct a programme of work in further investigation of issues related to the topic.
- Discuss and solve conceptual problems which arise during the investigation; justify research design decisions made during the investigation.
- Critically evaluate the investigation; present their work in compliance with academic standards.
|Graduate Attributes and Skills
||Apply critical analysis, evaluation and synthesis to issues that are informed by forefront developments in the subject/discipline;
Critically review, consolidate and extend knowledge, skills, practices and thinking in a subject/discipline.
|Course organiser||Dr Gian Campagnolo
Tel: (0131 6)51 4273
|Course secretary||Ms Maria Brichs
Tel: (0131 6)51 3205