تحلیل دادههای کیفی(به زبان انگلیسی)
Qualitative Methods Workshops, ATU, Teheran, 2019
Analysing Qualitative Data
Dr Lea Sgier
University of Geneva, Switzerland
26-27 January 2019
Content and aims
Qualitative data are notoriously difficult to analyse: invariably described as "voluminous, unstructured and unwieldy" (Bryman and Burgess 1994:216) and, more generally "bulky". They are often hard to "reduce" and make sense of beyond simple description. Also, they are typically highly context-specific and therefore impossible to submit to standardised analytical procedures. Finally, qualitative data are inherently multi-layered, hence open to multiple interpretations, which complicates data analysis and makes it vulnerable to various analytical shortcomings (over-interpretation, one-sidedness in the analysis etc., cf. Antaki et al. 2003).
This workshop provides a first introduction to qualitative data analysis for the social and human sciences (and related disciplines). It focuses on the general principles and steps of qualitative data analysis that underpin a variety of approaches roughly known as involving some form of “coding”, and applicable to a variety of types of data (textual, visual, audio-visual) (cf. for instance Miles, Huberman and Saldaña 2014; Maxwell and Chmiel 2014). We will go through the various steps that compose the coding process (from pre-analysis to the elaboration of a coding scheme to the actual coding, inventorising, mapping and analysis/interpretatin of data), both in practice and in theory. We will also discuss varieties in which this process unravels in practice, depending on the research aims, for example in terms of inductive vs deductive analysis, or exploratory and descriptive vs explanatory research, as well as the specific complexities that incur when we use this approach for comparative analysis. By the end of the workshop, the participants should have a good grasp of this method and have an idea how it would apply to their own data (if applicable). They should also have understood how the process of data analysis as such links to what comes before (research design and data collection in particular).
Understanding the general principles of qualitative data analysis is useful in itself: it gives researchers a handy and easily applicable tool that will help them organise, reduce and make sense of their qualitative data efficiently (whether for manual or for soft-ware assisted analysis). It also serves a second purpose though: a good understanding of the logic of coding is also very useful as a basis for types of qualitative analysis that are more interpretive in nature (discourse analysis, narrative analysis, some types of frame analysis etc.) that are typically less formalised and harder to explain in terms of how they “work”. A good understanding of the logic of coding will help to see that these approaches, although different in spirit and aim, follow similar methodological steps.
Format
The workshop will include various types of activities: lectures by the instructor, group exercises, discussions of participants’ questions and plans.
Participants are expected to be willing to engage in active data analysis exercises. A large portion of the workshop will consist in us going together through the key steps of a data analysis exercise and discussing issues as they arise (and how they could transpose to the participants’ real-life concerns).
Participants
This workshop is mainly meant for participants with little or no knowledge of qualitative data analysis who wish to get a first grip of the basics, either as a method in itself that could be useful to them, or as a preparation for learning other types of data analysis (such as discourse analysis) that work somewhat differently (and more interpretively), but that become easier to grasp and use if the basics of coding are understood. The workshop is also suitable for people with some understanding of qualitative data analysis who would like to reflect on their own ways of going about analysis.
The workshop is designed mainly for participants from the social and human sciences, but it is open to participants from other fields and disciplines as well, including participants from interdisciplinary fields.
Preparation
The participants will be provided with a few of texts in support of the workshop. The ones markes with an * are advised to be read ahead of the workshop. The others serve as reference material for before or after the workshop for participants who want to engage more deeply with this method. All readings will be provided in electronic format ahead of the workshop.
The participants will also receive some data extracts about ten days ahead of the workshop that they will be asked to simply read through before the beginning of the workshop.
Day-to-day outline (tentative)
Day 1:
8:00-10:00
Introduction to the workshop; overview of the field of qualitative data analysis; first exercise in qualitative data analysis
10:00-12:00
Introduction to the logic of coding (steps, processes); the role of theory in coding
13:00-15:00
Coding exercise (1): inductive and deductive coding scheme development; what is a “good” coding scheme?
15.00-17:00:
Coding exercise (2): coding (inductive/deductive; in vivo/analytic etc.)
Day 2:
8:00-10:00
Coding exercise (3): validity checks on the coding; inventorising and mapping; searching for paterns.
10:00-12:00
Coding exercise (4): searching for patterns (continued) beyond description; data analysis and interpretation.
13:00-15:00
Extensions of the basic process: types of analysis (descriptive, explanatory), comparative analysis, process tracing analysis, etc.; software-assisted analyis (with a brief demonstration of MaxQDA if desired).
15:00-17:00
Implications of data analysis on data collection (and management); participants’ further questions.
Readings:
Bazeley, Patricia (2009). "Analysing Qualitative Data: More Than Identifying Themes". Malaysian Journal of Qualitative Research 2(2): 6-22. (http://www.researchsupport.com.au/Bazeley_MJQR_2009.pdf)
*Butcher, Howard Karl et al. (2001). "Thematic Analysis in the Experience of Making a Decision to Place a Family Member With Alzheimer's Disease in a Special Care Unit". Research in Nursing&Health 24: 470-80.
Fereday, Jennifer and Muir-Cochrane, Eimear (2006). "Demonstrating Rigor Using Thematic Analysis: A Hybrid Approach of Inductive and Deductive Coding and Theme Development". International Journal of Qualitative Methods. 5(1). 80-92.
Maxwell, Joseph A. and Chmiel, Margaret (2014). "Notes Toward a Theory of Qualitative Data Analysis", in Flick, Uwe (ed.), The Sage Handbook of Qualitative Data Analysis, London: Sage, pp. 21-34.
(*)Miles, Matthew B., Huberman, A. Michael and Saldaña, Johnny (2014). Qualitative Data Analysis: A Methods Sourcebook. Thousand Oaks: Sage, ch. 1, *2, 4, 6-9.
Palmberger, Monika and Gingrich, Andre (2014). "Qualitative Comparative Practices: Dimensions, Cases and Strategies", in in Flick, Uwe (ed.), The Sage Handbook of Qualitative Data Analysis, London: Sage, pp. 94-108.
*Ritchie, Jane and Spencer, Liz (2002). "Qualitative Data Analysis for Applied Policy Research", in Huberman, A. Michael and Miles, Matthew B. (eds), The Qualitative Research Companion. Thousand Oaks: Sage, pp. 305-329.
The instructor
Lea Sgier is a political scientist by training. She is a senior lecturer in qualitative methodology at the University of Geneva (Switzerland) and a senior researcher at the Professional University of Social Work in Geneva. She is also an instructor at various international methodology summer and winter schools (Essex Summer School UK, ECPR Winter School, WSSR Concordia, Montreal, SSRM University of Hong Kong, CUSO doctoral programmes of the French speaking Swiss universities), where she teaches qualitative methodology and academic writing (in English and French). From 2010-17 she was a professor of qualitative methodology at Central European University (CEU) in Budapest, Hungary. Since 2013, she is a member of the Steering Committee of the ECPR Standing Group on Political Methodology (Europe’s main professional organisation of political scientists), and from 2009-16 she acted as an instructor and methodological advisor for two large scientific cooperation projects with the Western Balkans (RRPP) and with the South Caucasus (ASCN).
Her research interests are in gender and politics; dementiaand old age policy, and qualitative-interpretive methods. She is co-investigator of a project on older people’s political citizenship in Switzerland (2017-19); is about to complete a project on health and care professionals’ training needs in the field of dementia, for the Canton of Geneva (2018-19), and currently works for a project on cantonal dementia policies in Switzerland.
Lea.Sgier@unige.ch, +41 22 379 89 51