Module SSI2004 for 2021/2
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Undergraduate Module Descriptor
SSI2004: Research Design in the Social Sciences
This module descriptor refers to the 2021/2 academic year.
Module Aims
The aim of this module is to introduce you to the principles of research design in the social sciences so that you are able to assess the research of others (e.g. in the media, in research articles) and use quantitative skills in your own research projects. This module covers the basics of research design and the scientific method, explaining how measuring variables allows us to test theories and hypotheses. It guides you in how to collect and manage social data, using surveys and experiments. It also discusses the concept of causality and introduces various research designs that can be used for causal inference with social data.
On successfully completing the programme you will be able to: | |
---|---|
Module-Specific Skills | 1. Demonstrate an understanding of the principles of research design in the social sciences. 2. Demonstrate knowledge of different types of empirical research and data collection techniques. |
Discipline-Specific Skills | 3. Apply knowledge of the principles of research design to social science problems. 4. Critically evaluate empirical research in the social sciences. |
Personal and Key Skills | 5. Write reports to a deadline. 6. Evaluate the quality of empirical evidence in the public debate on social and political matters. |
Module Content
Syllabus Plan
Whilst the module’s precise content will vary from year to year, it is envisaged that the syllabus will cover the following themes:
- Descriptive and causal logic in social science research.
- The problem of causal inference.
- Experiments: field, laboratory, and survey.
- Survey research.
- Natural experiments and instrumental variables.
- Longitudinal research and difference-in-differences estimation.
- Computational social science.
- Mixed methods for social science research.
Learning and Teaching
This table provides an overview of how your hours of study for this module are allocated:
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
---|---|---|
22 | 128 | 0 |
...and this table provides a more detailed breakdown of the hours allocated to various study activities:
Category | Hours of study time | Description |
---|---|---|
Scheduled learning and teaching activity | 22 | 11 x 2 hour lectures/workshops |
Guided independent study | 78 | Reading and preparation for classes |
Guided independent study | 50 | Reading, preparation and writing of the assignments |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
How this Module is Assessed
In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.
Formative Assessment
A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
---|---|---|---|
Plan for research design assessment | 500 words | 1-4, 6 | Written and oral feedback |
Summative Assessment
A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.
Coursework | Written exams | Practical exams |
---|---|---|
100 | 0 | 0 |
...and this table provides further details on the summative assessments for this module.
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
---|---|---|---|---|
Critical review of a research paper | 50 | 1,500 words | 1-6 | Written feedback |
Research design | 50 | 1,750 words | 1-6 | Written feedback |
Re-assessment
Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
---|---|---|---|
Critical review of a research paper | Critical review of a research paper (1,500 words) | 1-6 | August/September reassessment period |
Research design | Research design (1,750 words) | 1-6 | August/September reassessment period |
Indicative Reading List
This reading list is indicative - i.e. it provides an idea of texts that may be useful to you on this module, but it is not considered to be a confirmed or compulsory reading list for this module.
R.A.Singleton & B.C.Straits. Approaches to Social Research. Oxford University Press (2017).
M.Salganik, Bit by Bit: Social Research in the Digital Age. Princeton University Press (2017).
F.J.Fowler, Survey Research Methods, 5th ed., Sage (2013).
J.D.Angrist and J.-S.Pischke, Mastering ‘Metrics: The Path from Cause to Effect. Princeton University Press (2014).
K.Imai, Quantitative Social Science: An Introduction. Princeton University Press (2017).
T.Dunning, Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press (2012).
A.S.Gerber and D.P.Green, Field Experiments: Design, Analysis, and Interpretation. W.W.Norton (2012).
R.Glennerster and K.Takavarasha, Running Randomized Evaluations: A Practical Guide. Princeton University Press (2013).
G.King, R.O.Keohane & S.Verba. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton University Press (1994).
R.B.Morton & K.C.Williams, Experimental Political Science and the Study of Causality: From Nature to the Lab. Cambridge University Press (2010).
D.C.Mutz, Population-Based Survey Experiments, Princeton University Press (2011).