Creative data analysis
Date:
08/10/2024 - 09/10/2024
Organised by:
Social Research Association
Presenter:
Dr Nicole Brown
Level:
Entry (no or almost no prior knowledge)
Contact:
Patricia Cornell
training@the-sra.org.uk
![video conference logo](/site-resources/brand/images/videoconference-transparent-200px.png)
Venue: Online
Description:
Introduction/Overview
The aim of this interactive workshop is to consider data analysis in qualitative research with a specific focus on how to treat and deal with data that is not textual, but comes out of the use of creative methods (drawings, paintings, pick-a-card, LEGO models, etc.). Using real data from research using creative methods for data collection we explore how analysis of "messy data" can be approached.
We consider the principles and process of analysis within qualitative research in general when we discuss if analysis is ever an objective process and if there is a difference between analysing data from linear texts or visual/sensory data, such as that from building LEGO models, song lists, photographs, videos and the like. Delegates have opportunities to practise analysing visual data on its own, in connection with textual data employing the "Systematic Visuo-Textual Analysis" or by employing creative forms of expression.
In line with the pedagogical principles of social constructivism the course is delivered as a mixture of interactive group tasks, discussions and lectures to enable active and experiential learning. This workshop can be taken on its own or following on from the workshop "Creative methods to collect and generate data in qualitative research".
Learning outcomes
By the end of the workshop, participants will:
- Have critical awareness of advantages and risks when using creative methods in qualitative research
- Be equipped to use creative methods for data analysis
- Have a critical appreciation of existing approaches to and paradigms of data analysis, particularly linked to non-textual data
- Feel permitted to "experiment" and "try" in qualitative research
Topics
The course will cover:
- Theoretical underpinning to data analysis
- Practical ideas for data analysis
- Ethical issues and quality considerations to be accounted for when using creative methods
- The role of the researcher in analysis
Who will benefit?
This course is suitable for anyone who would like to experience and learn more about alternative and/or complementary methods to existing qualitative approaches (i.e. focus groups, interviews). It is expected that participants will have prior experience of and with qualitative research. Participants at the early, middle and final stages of a qualitative research project will benefit, but if possible, it is best to consider analysis at the proposal stage.
Course tutor
Dr Nicole Brown is Associate Professor at IOE, UCL's Faculty of Education and Society, and Director of Social Research & Practice and Education Ltd. Underpinned by her interpretation of human communication relying on the embodied, metaphorical understanding of the world, she regularly uses participatory and creative approaches to data collection and analysis. Nicole has taught research methods for over ten years, including at the American Association for Public Opinion Research (AAPOR), the Society for Research into Higher Education (SRHE), the National Centre for Research Methods (NCRM), Photovoice Worldwide and the British Medical Association (BMA). Nicole has authored Making the Most of Your Research Journal and co-authored Embodied Inquiry: Research Methods. For Nicole's publications check https://iris.ucl.ac.uk/iris/browse/profile?upi=NBROW65
Cost:
£165 for SRA members, £220 for non-members
Website and registration:
Region:
International
Keywords:
Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Qualitative Data Handling and Data Analysis, Research Management and Impact, Research Skills, Communication and Dissemination
Related publications and presentations:
Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Qualitative Data Handling and Data Analysis
Research Management and Impact
Research Skills, Communication and Dissemination