1. QUALITATIVE DATA ANALYSIS
Week 11

2. Lesson objectives Review qualitative research
Managing qualitative data
Analysing qualitative data

3. What is Qualitative Research
“….research that describes phenomena in words instead of numbers or measures….Quantitative research: research that describes phenomena in numbers and measures instead of words.” (Krathol: 1993)

4. Why qualitative approach?
Not everything that counts can be counted, and not everything that can be counted counts
-Albert Einstein

5. Common features of Qualitative Research
In-depth and interpreted understanding of the social world of research subjects- how they make meanings of social circumstances, experiences and interactions in the ‘fields’ or life situations.
Describing social phenomena as they occur
Using data collection methods suitable to the social context (interactive, flexible and sensitive)
Maintaining close contacts between researcher and research subjects for emergent issues to be explored jointly.
Rich data- as perceived from ‘inside’- empathetic understanding without bias or preconceived ideas.
Producing detailed data, extensive, rich and inductively extracted (Holmes, et.al. pg99)

6. Types of Qualitative Research
Phenomenology
Grounded Theory
Ethnography
Case Study

7. CASE STUDY/IES
A case study is an exploration of a “bounded system” or a case (multiple cases) over time through detailed, in-depth data collection involving multiple sources of information rich in context (Cresswell, 1998).
A case study design is employed to gain an in-depth understanding of the situation and meaning for those involved (Merriam, 2001)

8. CASE STUDY/IES
The process of conducting a case study begins with the selection of the ‘case’.
The selection is done purposefully, not randomly; selection of a particular person, site, program, process, community or other bounded system because it exhibits characteristics of interest to the researcher. (Merriam, 2002)

9. Analyzing and Interpreting Data
Quantitative
Data analysis consist of statistical analysis
Data analysis involves describing trends, comparing group differences or relating variables
Interpretation compares results with prior predictions and past research
Qualitative
Data analysis consist of text analysis
Data analysis involve describing the information and developing themes
Interpretation situates the findings within the larger, more abstract meanings

10. Data Analysis: Qualitative Data
Definition:
An inductive process of organizing the data into categories and identifying patterns among themes and categories.
Data collected from interviews, observation and documents – in overwhelming volume

11. Steps in Data Analysis
Generally these are the common steps in data analysis
Organizing data
Need to organize because of the volume and large amount of information
Organizing materials by type: all interviews, all observations, all documents, all photographs and visual materials
Organizing by participants, site, location etc.
Keeping duplicate copies of all forms of data

12. Steps in Data Analysis Transcribing Data
Process of converting audiotape recordings or fieldnotes into text data (written data)
Highlighting pauses, questions, clarification, intonation and voice modulation (lengthy break, silence, laugh, inaudible etc.)

13. Steps in Data Analysis Exploring Data Preliminary exploring the data
Read several times- write memos/notes in the margin or hunches, ideas, concepts
Helps forms an initial analysis
Basis for general understanding

14. Steps in Data Analysis Describing and developing themes
Forming an in-depth understanding of the phenomenon under study
The processes from data to generating a description and themes are
Indexing /Coding data
Using code to develop themes
Connecting and interrelating themes

15. (i) Coding Data
The process of segmenting and labeling text to form descriptions and broad themes in the data
The process of dividing data into parts by some classification system
Make sense of the data
The research questions and research concerns becomes the basis for generating themes/categories

16. Steps in coding data Identifying text segments:
Tags/labels for assigning units of meanings
Codes are labels used to describe a segment of text
Assigning a code word or phrase that accurately describes the meaning of the text statement

17. Steps in coding data Identifying text segments:
Codes can address many different topics:
Setting/ context code
Description of a school
Processes code – what happens
Sequence of events e.g disruptions
Periods, stages, phases

18. Steps in coding data Activities code Relationship code
Regularly occurring e.g attendance, lunch breaks, working session/ classroom session starts and ends.
Relationship code
Friendships, enemies, relatives, superiors and subordinates

19. Steps in coding data Feelings code Event code
Angry, happy, enthusiastic
Event code
Specific events
Unexpected/ significant
Riot, commotion, strike, disagreements

20. (ii) Developing themes
After coding the entire text, make a list of all code words.
Cluster together similar codes
Look for redundant codes
Reduce codes to a more manageable number e.g 25-30
Go back to data, look for new codes

21. (ii) Developing themes
Identify themes from codes
Themes – similar codes put together to form a major idea/ perspective
Support with evidence/ specific quotes

22. (iii) Connecting and interrelating themes
Minor themes are subsumed within major themes
Major themes lead to broader themes
Towards more abstraction
Display a chronology, sequence or patterns showing interconnection of themes
A pattern that explains the research questions
Linking the themes together in some meaningful way- to show interaction and interrelatedness of the findings
(may use diagrams or model)

23. Pattern of Themes: Learning Beliefs among Muslim adult learners in non-formal learning environment
Memorising
Memorising for better understanding
Gain knowledge
Seek new knowledge
Performing ritual
Practical application
Moral duty
Muslims’ duty
Good Muslim
Obligatory learning
God’s guidance
To seek heaven/paradise
Cleanse heart and soul
To seek God’s pleasure
Acquiring knowledge
(ii) Practical knowledge
(iv) Religious duty
(v) Spiritual pleasure
Temporal reasons/ belief
B. Temporal and Hereafter reasons/ belief
C. Godly and Hereafter reasons/ belief

24. Pattern of Themes: Learning Beliefs among Muslim adult learners in non-formal learning environment
Temporal and Hereafter reasons/ beliefs
Temporal reasons/ beliefs
Hereafter reasons/ beliefs
LEARNING BELIEFS

25. Let’s analyse some qualitative data