Approaches to Analysing Qualitative Data: Archaeology as a Metaphor for Method (few places remaining)
Date:
18/10/2016
Organised by:
NCRM, University of Southampton
Presenter:
Professor Emeritus Clive Seale (Brunel University) and Professor Maria Tamboukou (University of East London)
Level:
Intermediate (some prior knowledge)
Contact:
Penny White
Research Coordinator
National Centre for Research Methods
Email: p.c.white@southampton.ac.uk
Tel: 02380584539
Description:
How can we ‘dig down’, and where do we dig, to get an analytic grip when working with large and complex bodies of qualitative data? The metaphor of archaeology enables qualitative analysts to think about what lies ‘underneath’ the corpus of material being analysed, working extensively and intensively to identify and excavate meaning.
In this seminar, researchers working with different bodies of qualitative materials will discuss how they approached their analysis, from a range of methodological perspectives. The seminar is likely to be of interest and use to researchers with a range of qualitative analytic skills and experience, from postgraduate to senior.
14.00 Welcome and introduction: Lynn Jamieson and Rosalind Edwards
14.15 Professor Emeritus Clive Seale (Brunel University) : An archaeological approach working with keyword analysis of a large corpus of qualitative data
15.00 Dr. Susie Weller (University of Southampton) and Dr. Emma Davidson (University of Edinburgh) : A layered archaeological approach to analysis across multiple sets of qualitative longitudinal data
15.45 Tea
16.15 Professor Maria Tamboukou (University of East London) : Archaeology of knowledge and working in the archives
17.00 Round up and Finish
* You may like to arrive a few hours early so that you can visit the fascinating collection in The Foundling Museum before the seminar starts.
Cost:
Free of charge
Website and registration:
Region:
Greater London
Keywords:
Qualitative Data Handling and Data Analysis
Related publications and presentations:
Qualitative Data Handling and Data Analysis