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 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: F : F5
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
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... 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.Counting frequencies of occurrence 2.Noting patterns and themes 3.Seeing plausibility 4.Clustering 5.Making metaphors 6.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 Briefing Sampling Associating Hypothesis development Hypothesis testing Immersion in the data Categorizing Incubation Synthesis Culling Interpretation Writing Rethinking
METHODOLOGICAL TOOLS FOR ANALYZING QUALITATIVE DATA Analytic induction Constant comparison Typological analysis Enumeration