This document discusses various approaches to organizing and presenting qualitative data analysis. It outlines seven ways to organize data including by groups, individuals, themes, research questions, instruments, case studies, and narratives. Narrative and biographical approaches are described as a way to add context and perspective. Systematic approaches like comparing groups and analyzing deviant cases are also presented. The document provides examples of tactics and tools that can be used in qualitative data analysis such as counting frequencies, noting patterns, clustering, and content analysis techniques.

1. ORGANIZING AND PRESENTING
QUALITATIVE DATA
© LOUIS COHEN, LAWRENCE
MANION & KEITH MORRISON

2. STRUCTURE OF THE CHAPTER
• Tabulating data
• Seven ways of organizing and presenting
data analysis
• Narrative and biographical approaches to
data analysis
• Systematic approaches to data analysis
• Methodological tools for analyzing qualitative
data

3. TABULATING DATA
(Accompanying table)
• Key: P1 = Primary 1, P 6 = Primary 6, F3 = Secondary
Form 3, F5 = Secondary Form 5.
• The left hand column indicates the number of the
respondent (1-12) and the level which the respondent
taught (e.g. P1, F3 etc.).
• Where data for respondents in each age phase are
similar they are grouped into a single set of responses
by row; where there are dissimilar responses they are
kept separate.
• The right hand column indicates the responses. In
many cases respondents all gave similar responses in
terms to the topic (strengths and weaknesses of English
language teaching); these are grouped together.

4. Q7: Strengths and weaknesses of English language teaching
1. P1 Students started learning English at a very young age
and they should be good at it. However, this could
also be a disadvantage as students were too young to
learn English and to understand what they were taught
2-6: P6 These respondents all commented that individual
schools had great autonomy over syllabus design.
Consequently, some syllabus contents were too rich to
be covered within the limited time span. Therefore, it
was hard to make adjustments, though students could
not cope with the learning requirements. This put
pressure on both teachers and students. Worse still,
some schools made students learn other foreign
languages apart from English, and that made the
learning of English more difficult.
7-9: F3
10-12:
F5

5. SEVEN WAYS OF ORGANIZING AND
PRESENTING DATA ANALYSIS
1. By groups of people
2. By individuals
3. By issue or theme
4. By research question
5. By instrument
6. By case studies
7. By narrative account

6. NARRATIVE APPROACHES TO DATA
ANALYSIS
• Humans make meaning and think in terms of
‘storied text’, which guides their actions.
• Narrative analysis, together with biographical data,
can give the added dimension of realism,
authenticity, humanity, personality, emotions,
views and values in a situation.

7. NARRATIVE APPROACHES TO DATA
ANALYSIS
• Narratives
– pass on information
– bring information to life
– meet people’s psychological needs in coping
with life
– help a group to crystallize or define an issue,
view, value or perspective,
– can persuade or create a positive image,
– help researchers and readers to understand the
experiences of participants and cultures
– contribute to the structuring of identity

8. BIOGRAPHICAL APPROACHES TO
DATA ANALYSIS
• Biographies
– tend to follow a chronology
– report critical or key events and moments
– report key decisions and people
– can establish causality
– May restore broken identities or shattered
futures

9. NARRATIVE AND BIOGRAPHICAL
APPROACHES TO DATA ANALYSIS
• Narratives and biographies are selective , based
on:
– Key decision points in the story or narrative
– Key, critical (or meaningful to the participants)
events
– Themes
– Behaviours
– Actions
– People
– Key experiences
– Key places

10. SYSTEMATIC APPROACHES TO
DATA ANALYSIS
• Comparing different groups simultaneously
and over time
• Matching the responses given in interviews to
observed behaviour
• Analyzing deviant and negative cases
• Calculating frequencies of occurrences and
responses
• Assembling and providing sufficient data that
keeps separate raw data from analysis

11. SELECTIVITY IN QUALITATIVE
ANALYSIS OCCURS BECAUSE OF . . .
• Data overload
• First impressions
• Availability of people
• Information availability
• Positive instances
• Internal consistency
• Uneven reliability
• Missing data
• Revision of hypotheses
• Confidence in judgement
• Co-occurrence (may be mistaken for association)
• Inconsistency

12. STAGES IN ANALYSIS
• Generating natural units of meaning
• Classifying, categorizing and ordering these
units of meaning
• Structuring narratives to describe the contents
• Interpreting the data

13. TWELVE TACTICS IN ANALYSIS
1. Counting frequencies of occurrence
2. Noting patterns and themes
3. Seeing plausibility
4. Clustering
5. Making metaphors
6. Splitting variables

14. TWELVE TACTICS IN ANALYSIS
7. Subsuming particulars into the general
8. Factoring
9. Identifying and noting relations between
variables
10.Finding intervening variables
11.Building a logical chain of evidence
12.Making conceptual/theoretical coherence

15. CONTENT ANALYSIS
• Briefing
• Sampling
• Associating
• Hypothesis development
• Hypothesis testing
• Immersion in the data
• Categorizing
• Incubation
• Synthesis
• Culling
• Interpretation
• Writing
• Rethinking

16. METHODOLOGICAL TOOLS FOR
ANALYZING QUALITATIVE DATA
• Analytic induction
• Constant comparison
• Typological analysis
• Enumeration