Research training

Induction programme

A Graduate School induction programme is held at the start of each term, with a week-long event in September. This programme aims to introduce a range of key matters, including policies, training and the nature of the doctoral student experience. It also integrates with Departmental induction events, which give information specific to their discipline. 

Graduate School Seminar Series

The Graduate School Seminar Series, which is open to all doctoral students, covers a wide range of key topics pertinent to different stages of the doctoral journey, from presentation skills to preparing for upgrade. Seminars are usually held from 3 - 4 pm, on Mondays, during term time.

Core Qualitative Methods

This module provides an interdisciplinary introduction to qualitative traditions of social research. It aims to give you an understanding of some of the main forms of qualitative research, offer opportunities to develop the skills for conducting qualitative research, and help you in reading and assessing research publications.

The course is also designed to offer you opportunities to discuss your research and exchange ideas with students from a range of disciplines.

The course is designed as an introduction for those with little or no previous experience of this methodology. Core Qualitative Research Methods is open to all MRes and MPhil/PhD students at Goldsmiths.

Modelling Social Data I&II

These modules are designed to help researchers to understand and gain skills in quantitative research. Researchers may choose complete one or both modules, depending on their training needs. However, entry to Modelling Social Data II requires successful completion of Modelling Social Data I or demonstration of prior learning and sufficient background in quantitative methods to ensure you will be able to engage successfully in Modelling Social Data II.

Modelling Social Data I will give you advanced training in the application of quantitative methods in social research. You'll have the opportunity to carry out exploratory secondary analysis of official and other data sets, using SPSS (Statistical Package for the Social Sciences).

You'll learn the importance of quantitative data analysis to any understanding of the social. The emphasis is the conceptual appreciation of the statistical techniques and the ability to select and use different social statistical methods depending on their appropriateness for the research problem and the data collected.

Rather than requiring students to reproduce the mathematical underpinnings of statistical techniques, this module develops an intuitive conceptual understanding of how statistical and quantitative methods structure datasets and how we can perform analyses to better understand that structure and test hypotheses.

Modelling Social Data II will introduce you to extensions to multivariate techniques covered in Modelling Social Data I. Specifically, you'll explore issues of time, space, and latency through the modelling process. While linear regression techniques remain the ‘go to’ approach for analysing survey data, there are numerous ways in which models can be derived that better ‘fit’ the data. This module is all about making such advancements in a way that gradually builds on prior knowledge.

Learning and Teaching in Higher Education (LTHE) pathway

The LTHE pathway (consisting of two 15-credit modules) comprises Stage 1 of the wider Postgraduate Certificate in Higher Education (PGCHE) Programme (itself 4x15 credit modules overall).

The LTHE pathway is aimed both at registered MPhil/PhD students and at postdoctoral researchers who are either new to university teaching or otherwise have limited learning and teaching experience in higher education.

Participants will have opportunities to critically explore and discuss educational theories and the practice of learning and teaching in higher education and reflect on scholarly and practitioner activities, including professional development, both individually and collectively, with academic and professional peers.