دانلود کتاب A Step-by-Step Guide to Qualitative Data Coding

فهرست مطالب :

Cover
Half Title
Title Page
Copyright Page
Dedication
Brief contents
Detailed contents
Exhibits
List of Figures
List of Tables
List of Boxes
Acknowledgment
1 Introduction to qualitative data analysis
Emergence of qualitative research as an acceptable research inquiry
What is your paradigm?
Assumptions associated with the interpretative paradigms
Conclusion
References
2 Review of qualitative approaches and their data analysis methods
Qualitative approaches and their respective data analysis processes
Phenomenological approach
When to use the phenomenological approach
Giorgi’s (1975) approach towards analyzing phenomenological data
Hermeneutic phenomenological approach
When to use the hermeneutic phenomenological approach
Conducting hermeneutic phenomenological analysis
Interpretative phenomenological analysis
When to use interpretative phenomenological analysis
Conducting interpretative phenomenological analysis at the data analysis stage
Transcendental phenomenological approach
When to use the transcendental phenomenological approach
Conducting transcendental phenomenological analysis
Ethnography
When to use ethnography
Conducting analysis of ethnographic data
Narrative approach
When to use the narrative approach
Conducting narrative analysis
Case study approach
When to use the case study approach
Conducting case study analysis
Grounded theory approach
When to use the grounded theory approach
Conducting grounded theory analysis
Conclusion
References
3 Understanding the art of coding qualitative data
What is qualitative coding?
What comprises the art of coding?
Systematic process
Maintaining consistency
Promoting repeatability
Ensuring believability
Data reduction
Subjectivity
Transparency
Orientation to the art of qualitative coding
Qualitative coding strategies
Description-focused coding strategy
Characteristics of description-focused coding
When to use description-focused coding
Demonstration 3.1
Interpretation-focused coding strategy
Characteristics of interpretation-focused coding
When to use interpretation-focused coding
Demonstration 3.2
Presumption-focused coding strategy
Characteristics of presumption-focused coding
When to use presumption-focused coding
Demonstration 3.3
Qualitative data for practice:
Conclusion
Note
References
4 Preparing data to code
What kind of data can be qualitatively analyzed?
Transcribing audio files
Using existing data for qualitative analysis demonstrations
Using qualitative analysis tools
Using manual qualitative analysis tools
When to use manual qualitative analysis tools
Using qualitative data analysis software (QDAS)
When to use QDAS
Conclusion
References
5 Reflecting on, acknowledging and bracketing your perspectives and preconceptions
Knowing the ‘self’
Knowing your perspectives
Knowing your preconceptions
Knowing your lens
Bracketing your perspectives and preconceptions
Importance of bracketing at the data analysis stage
Steps in engaging in Epoché (bracketing) at the data analysis stage
Disclosing your perspectives, preconceptions, lens and expectations
Demonstration 5.1
Conclusion
References
6 Documenting personal reflections and the analytical process
Memo writing
Importance of memo writing
Types of memos
Conclusion
References
7 Manually assigning codes to data
Overview
Deciding on an appropriate coding strategy
Demonstration 7.1
Assigning labels to the research questions
Demonstration 7.2
Creating codes using the interpretation-focused coding strategy
Demonstration 7.3
Compiling codes and tallying code frequencies
Demonstration 7.4
Q&A about qualitative coding
Conclusion
References
8 Developing categories and themes
Transforming codes into categories and themes
Code transformation or categorization strategies
Presumption-focused coding strategy
Demonstration 8.1
Individual-based sorting strategy
Demonstration 8.2
Group-based sorting strategy
Demonstration 8.3
Conclusion
References
9 Connecting themes, and developing tables and diagrams
When to examine the relationships among categories/themes
How relationships among categories/themes are built
Demonstration 9.1
Using tables and diagrams
Tools for designing tables and diagrams
Demonstration 9.2
Demonstration 9.3
Demonstration 9.4
Conclusion
References
10 Using QDA Miner Lite to analyze qualitative data
QDA Miner Lite overview
Preparing qualitative data
Importing the interview transcripts
Demonstration 10.1
Overview of the QDA Miner lite software interface (see Exhibit 10.4)
Creating demographic variables and attributes
Demonstration 10.2
Demonstration 10.3
Exploring data
Coding empirical indicators
Demonstration 10.4
Developing categories/themes
Demonstration 10.5
List of themes and their respective codes for ‘GM concerns factors (RQ1)’
List of themes and their respective codes for ‘GM communication strategies (RQ3)’
Generating tables and diagrams
Demonstration 10.6
Conclusion
References
11 Using NVivo 12 to analyze qualitative data
NVivo 12 software overview
Preparing qualitative data
Demonstration 11.1
Exploring data
Demonstration 11.2
Coding empirical indicators
Demonstration 11.3
Developing categories/themes
Demonstration 11.4
Visualizing outcomes
Demonstration 11.5
Exporting outcomes
Demonstration 11.6
Conclusion
References
12 Using Dedoose to analyze qualitative data
Dedoose software overview
Functions of Dedoose across qualitative analysis stages
Demonstration 12.1
Preparing qualitative data
Coding excerpts (empirical indicators)
Demonstration 12.2
Rating excerpts (empirical indicators)
Developing categories/themes
List of themes and their respective codes for ‘GM concerns factors (RQ1)’
List of themes and their respective codes for ‘GM communication strategies (RQ3)’
Demonstration 12.3
Retrieving and exporting outcomes
Conclusion
References
13 Presenting qualitative findings
Introduction
Elements of a qualitative findings report
Overview
Example 13.1
Context of the data and findings
Example 13.2
Disclosure of preconceptions, perspectives, lens and expectations
Example 13.3
Data analysis process
Example 13.4
Coding data
Developing themes
Presenting the main findings
Findings presentation structures
Example 13.5a (Individualized theme-driven format)
Example 13.5b (Synthesized theme-driven format)
Summary
Example 13.6
Conclusion
References
14 Ensuring the credibility of the analysis process and findings
The concept of credibility
Ensuring consistency
Being systematic
Promoting transparency
Auxiliary credibility strategies
Implementing member checking
Utilizing theoretical sampling
Actively involving participants
Having a data analysis team
Conclusion
References
Appendix A
Appendix B
Index