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16 Cards in this Set
- Front
- Back
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The overall process of data analysis begins by |
identifying segments of the data which is a potential answer to part of the research question. These segments are called units of data |
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Units of data must be |
1. relevant 2. interpretable |
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After finding units of data that can potentially answer part of the research question, the research then |
looks for recurring regularities in the data, and classifies them into categories |
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What are the FIVE steps of the process of analysis in qualitative research? |
1. CATEGORY CONSTRUCTION (CODING) / UNITS 2. SORTING CATEGORIES AND DATA / CODES 3. NAMING THE CATEGORIES 4. DECIDING ON NUMBER OF CATEGORIES / THEMES 5. BECOMING MORE THEORETICAL (THEMATIC) / FINDING AN OVERARCHING THEME |
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Step 1: Category construction / coding. This is done by |
taking note of comments, observations, and accounts that strike me as being important and relevant to my study. Note that there is a difference between coding and open coding. The former is not note bits of data that are potentially relevant, the latter is to label most data with an open mind |
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Open coding takes into consideration |
all interesting bits of data towards answering my research question |
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Grouping units of data / codes into more general categories is called |
Axial / analytical coding |
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Units of data should not be considered |
categories, that is, categories should not consist of just one unit of data |
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Step 2: After forming categories, then categories need to be sorted. This is done by |
deciding which categories become the main 'themes' in my study |
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Sorting categories into themes is where qualitative data shows |
its multiple levels of abstraction, through moving from inductive (open-ended) to deductive (established categories) |
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Step 3: Naming the categories is like |
labelling each group of groceries as 'fruit', 'dairy products', 'vegetables', 'canned food' |
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Category names come from |
1. Me as the researcher 2. Participants themselves 3. Previous literature, though caution must be exercised with imposing previous themes on my own data |
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What are the FIVE CHARACTERISTICS of good categories? |
1. RESPONSIVE TO THE PURPOSE OF THE RESEARCH: answers part of RQ 2. EXHAUSTIVE: all codes can be placed into all categories derived from analysis 3. MUTUALLY EXCLUSIVE: each unit of data should only fit into one category 4. SENSITIZING : elicits reader interest 5. CONCEPTUALLY CONGRUENT: does it make sense? take note of whether one category can be put under another? |
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The fewer categories used to capture the essence of the research, the better - T/F |
TRUE, as Parsimony is valued (conciseness of themes) |
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The FINAL step of qualitative data analysis is to |
link all categories into explaining a story that answers the research question. The researcher has to CONNECT THE DOTS to answer the research question |
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The explanation of the researcher's findings can be done through |
a thematic map or a model |
