Social Research MA

Autumn term Philosophy of Social Science Research (20 credits)

The module considers fundamental philosophical debates about what counts as ‘knowledge’ across the social sciences. Teaching addresses (natural) science as a method of obtaining knowledge and the interpretative tradition in the social sciences. Students explore fundamental philosophical debates about what counts as ‘knowledge’ across the social sciences and apply these discussions to their own disciplines and field of study.

The module introduces students to social science research designs and ethical issues in research practice. Learning supports students to be able to make strategic choices when developing their own projects, and to assess the design and research ethics decision making in others’ published research work.

• Thesis-related preparation
• Information Skills for Social Sciences
• University Programme of Skills Training (as necessary)
• Dissertation-related preparation

Concepts, methods and skills central to quantitative research, including data collection approaches and concept operationalization, are core throughout this module. Building on a grounding in ideas relating to probability sampling, sampling error and statistical inference, coverage of techniques extends from comparisons of means and simple cross-tabular analyses to a discussion of multivariate analysis approaches, focusing on linear and logistic regression

Qualitative research is examined across a range of topics, from different approaches and methods including ethnographic and observational research, discourse and conversation analysis, documentary and archival analysis, participatory research and the use of interviews. Ethics in qualitative research is specifically considered, as is the evaluation of qualitative research.

• Thesis-related preparation

• Four advanced training modules (10)
• Dissertation (60)

Unless stated, all advanced training courses run as 2-day intensive workshops from 10–4pm with breaks. This list is updated regularly as new courses are approved so do check this website from time to time to see what is on offer.

These advanced training courses are open to all research students in the College (and some departments in other Colleges, such as Geography, subject to the discretion of the Programme Team). However, places on each course are limited and priority will be given to MA Social Research students.

These advanced training courses are also open to all staff in the University who may wish to attend without completing the assessments. However, all doctoral researchers and staff who wish to do so will be placed on a waiting list. Confirmation will be sent a week before the course dates.

• Social Research Advanced Training Modules Timetable 2018-19 (PDF - 648KB)

• Introduction to Econometric Software
  12 October, 2, 16, 30 November 2018
• Narrative Research
  25 and 27 March 2019
• Questionnaire Design
  30 April and 7 May
• Factor Analysis
  1 May and 15 May 2019
• Introduction to Causal Inference
  2 and 3 May 2019
• Case Study Research Design
  8 and 22 May 2019
• Multivariate Linear to Logistic Regression
  9 May and 10 May 2019
• Approach to Research on Discourse
  13 May and 14 May 2019
• Regression with Categorical Dependent Variables
  16 May and 17 May 2019
• Documentary Research in Education, History and the Social Sciences
  20 and 21 May 2019
• Policy Evaluation
  23 and 24 May 2019
• Visual Research Methods
  28 and 29 May 2019
• Q Methodology - A Systematic Approach for Interpretive Research Design
  30 May and 31 May 2019
• Introduction to Time Series Regression
  3,4,5,6 June 2019
• Researching Disability
  7 and 14 June 2019
• Mixed Methods Research Design
  10 and 11 June 2019
• Advanced Qualitative Data Analysis (NVivo)
  12 and 13 June 2019
• Researching Young People
  17 and 18 June 2019

NB: some courses have pre-requisites, e.g. to register on Multiple Linear and Logistic Regression, Factor Analysis, or Narrative Research, you will need to have passed Social Research Methods II (20 credits module), or equivalent. You will need to provide evidence that you have passed a similar course on quantitative/qualitative data analysis where appropriate.

To register for the above advanced training courses, please e-mail: specifying which courses you are interested in. When registering for courses, please provide your name, student ID, department/programme you are affiliated to, and your e-mail address.

You will receive a confirmation e-mail, acknowledging your request, and advising you of availability.