ORGANIZING AND PRESENTING
QUALITATIVE DATA
© LOUIS COHEN, LAWRENCE
MANION & KEITH MORRISON
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
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.
Q7: Strengths and weaknesses of English language teaching
Students started learning English at a very young age
1. P1
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
These respondents all commented that individual
2-6: P6
schools had great autonomy over syllabus design.
Consequently, some syllabus contents were too rich to
7-9: F3 be covered within the limited time span. Therefore, it
was hard to make adjustments, though students could
10-12: not cope with the learning requirements. This put
pressure on both teachers and students. Worse still,
F5
some schools made students learn other foreign
languages apart from English, and that made the
learning of English more difficult.
SEVEN WAYS OF ORGANIZING AND
PRESENTING DATA ANALYSIS
1.
2.
3.
4.
5.
6.
7.
By groups of people
By individuals
By issue or theme
By research question
By instrument
By case studies
By narrative account
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.
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
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
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
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
SELECTIVITY IN QUALITATIVE
ANALYSIS OCCURS BECAUSE OF . . .
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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
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
TWELVE TACTICS IN ANALYSIS
1.
2.
3.
4.
5.
6.
Counting frequencies of occurrence
Noting patterns and themes
Seeing plausibility
Clustering
Making metaphors
Splitting variables
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
CONTENT ANALYSIS
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Briefing
Sampling
Associating
Hypothesis development
Hypothesis testing
Immersion in the data
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Categorizing
Incubation
Synthesis
Culling
Interpretation
Writing
Rethinking
METHODOLOGICAL TOOLS FOR
ANALYZING QUALITATIVE DATA
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Analytic induction
Constant comparison
Typological analysis
Enumeration