Study unit 9: Qualitative data analysis and interpretation: steps, practical examples and pointers Flashcards
what is qualitative research
qualitative research means any type of research that produces findings not arrived at by statistical procedures or other means of quantification. It can refer to research about persons’ lives, lived experiences, emotions and feelings as well as about organisational functioning, social movements, cultural phenomena and interactions between nations. For Ezzy (2002:31), qualitative research methods aim to facilitate the discovery of, or the hearing of, the voice of other, or people, or experience being studied.
what is the aim of qualitative research
qualitative research aims to give privilege to the perspectives of the research participants and to “… illuminate the subjective meaning, action and context of those being researched.” Fundamental to qualitative research is whether participants’ perspectives have been authentically represented in the research process and the interpretations made from the information gathered (primarily through interviewing and observation).
Qualitative researchers concern themselves with the interpretation of subjective meaning, the description of social contexts, and the privileging of lay knowledge
what is qualitative data analysis
working with data [which are textual, non-numerical and unstructured], organising it, breaking it into meaningful units, synthesising it, searching for patterns, discovering what is important and what is to be learned, and deciding what to tell others”. Leedy (1997:165) refers to McMillan and Schumacher who are of the view that qualitative data analysis is mainly an inductive process1 of organising data into categories/themes and identifying patterns among the categories/themes. Babbie (2007:378) and Corbin and Strauss (2008:1) concur with the aforementioned definitions and refer to qualitative analysis as a non-numerical process of examining and interpreting of data in order to elicit meaning, gain understanding, and develop empirical knowledge
qualitative data analysis is all about the “taking apart” or de-contextualising, sifting, and sorting the masses of information acquired during the process of data collection, and organising or re-contextualising it in such a way that the themes/categories and interpretations that emerge from this process address the research problem(s) and the ensuing question(s) posed at the outset of the research.
When in the qualitative research process does one start with data analysis?
Creswell, (2009:184) states that data analysis is always an ongoing process that routinely starts prior to the first interview
Streubert Speziale and Carpenter (2007:46–47, 96) note that in qualitative research, the process of data analysis commences when the process of data collection begins.
texts on qualitative data analysis begin their discussion with what to do after data have been collected. He cautions that if data analysis only begins after the data have been collected, researchers will have missed many valuable opportunities that can be taken only at the same time as they are collecting their data. (This does not only ring true for when one uses the grounded theory as strategy of inquiry, but it also applies to most of the other designs that are interpretive, inductive and exploratory.) While engaging in the process of data analysis, whilst collecting data, the researcher might discover and notice unanticipated issues.
data analysis will be conducted as an activity concurrently with data collection, data interpretation, and narrative report writing. In this respect qualitative data analysis differs from quantitative data analysis where one divides and engages in separate activities when it comes to data collection, analysis and writing the results
When data collection begins, so too, does data analysis. In practice, we find that data analysis only occurs when data saturation becomes noticeable. In other words, when multiple interviews have been conducted and/or observations have been made and patterns and themes start recurring, or no new information emerges, the data are then said to have achieved “saturation
How qualitative data are analysed and interpreted
the process of data analysis is eclectic, and there is no “right way”. Leedy (1997:165) concurs and comments that there is no standard procedure for qualitative analysis, but add on that this does not mean it is not systematic and rigorous.
He further points qualitative researchers to the fact that in qualitative data analysis, a linear procedure is not followed. Instead, qualitative data analysis tends to occur in several cyclical, overlapping phases in which the researcher moves back and forth between different levels
provide THE STEP-WISE FORMAT OR PLAN FOR QUALITATIVE DATA ANALYSIS AS PROPOSED BY TESCH (in Creswell 1994:154–155, 2009:186)
Before the step-wise format or plan as proposed by Tesch (in Creswell 1994 and 2009) can be followed the collected data must be organised and be prepared for analysis
STEP 1: Once you have organised and prepared the data for analysis, read through all the transcriptions carefully. Make notes of some ideas as they come to mind
STEP 2: Select one document (one transcribed interview) — the most interesting/the shortest/the one on top of the pile. Go through it, asking yourself: What is this about? Do not think about the “substance”/content of the information, but its underlying meaning. Write down your thoughts in the margin.
STEP 3: When you have completed Step 2 for several participants,
make a list of all the topics. Put similar topics together. Form these
topics into columns that might be grouped as “major topics”,
“unique topics”, and “leftovers”.
STEP 4: Take this list of topics and assign to each topic an abbreviated and identifiable code.3 Now take this list of topics with its abbreviated codes and go back to your transcribed data and write the codes next to the data segments that correspond with the codes.
STEP 5: Find the most descriptive wording for your topics and turn them into themes/categories.4 (Look for ways of reducing your total list of themes/categories by grouping topics that relate to each other. Perhaps draw lines between your categories to show interrelationships.)
STEP 6: Make a final decision on the abbreviation for each theme/category and alphabetise these codes
STEP 7: Using the cut-and-paste method, assemble the data material belonging to each theme/category in one place and do a preliminary analysis
STEP 8: If necessary, recode the existing data. If not, start on interpreting and reporting your research findings.
what is first level/ open coding
“first-level coding” or “open coding”. “First-level coding refers to a combination of identifying meaning units, fitting them into themes/categories and assigning codes to the themes/categories” Tutty et al (1996:100).
So what is a “meaning unit”. Meaning units are segments (or chunks) of information that are the building blocks of a classification scheme.
comment on the interpretation of qualitative data
“Interpretation is a productive process that sets forth the multiple meaning of an event, object, experience, or test. Interpretation is transformation. It illuminates, throws light on experience. It brings out, and refines, as when butter is clarified, the meaning that can be sifted from the text, an object, or slice of experience.” He continues by stating that “meaning, interpretation, and reinterpretations are deeply intertwined with one another”
what steps follow when presenting findings
13When presenting your research findings, you need to first provide a biographical profile relating to the sample group
14After you presented the sample group’s biographical details, you may introduce the themes one at a time. You need to provide storylines to underscore/highlight or emphasise these themes and then provide appropriate literature to confirm and/or contrast the research findings
