mixed methodology Flashcards
points of qualitative research
Context and setting
Phenomenology and understanding
Inductive
Theory development
Exploratory
“rich and deep” data
Systematic and rigorous
points of quantitative research
Deductive
Test theories of hypotheses
Measures
Objective
Measurable evidence
Assumes a knowable reality.
Replication, generalizability.
mixed methods
Gather evidence based on the nature of the question and theoretical orientation; Intentional collection of qualitative and quantitative data; strengths of approaches to answer the research questions. (Creswell et al., 2011).
Six main deigns for mixed methodology research
The sequential explanatory method employs two different data-collection time points; the quantitative data are collected first and the qualitative collected last.
The sequential exploratory design is best for testing emergent theory because both types of data are interpreted during the data integration phase.
The sequential transformative approach has no preference for sequencing of data collection and emphasizes theory.
Concurrent triangulation is the ideal method for cross-validation studies and has only one point of data collection.
The concurrent nested design is best used to gain perspectives on understudied phenomena.
The concurrent transformative approach is theory driven and allows the researcher to examine phenomena on several different levels.
Strengths of mixed method designs
One major strength is that it is seen to solve the ‘weaknesses’ that both quantitative and qualitative research suffer from
Quantitative: weakness is not taking into account the context of the participants talk; their voices are not ‘heard’ in the final analysis
Qualitative: weakness is the potential interference of the researcher in the analysis – they are heavily involved in coding/interpreting the findings; cannot generalise to wider population
Mixed methods – researchers have the possibility to use a wide variety of data collection/analysis which could arguably solve the issues described above.
Characteristics of the deductive approach
- emphasizes scientific principles.
- moves from theory to data.
- Seeks to explain casual relationships between variables.
- collection of quantitative data.
- highly structured methodology.
- researcher independence.
- operationalization of concepts.
- reductionist.
- generalization.
Characteristics of the inductive approach
- moving from data to theory.
- understanding the meanings humans attach to events. Maybe more importantly from their perspective.
- close understanding of the research context.
- collection of qualitative data.
- Flexible structure to permit changes of research emphasis as the research progresses. More fluid.
- realization that the researcher is part of the research process.
- less concern with the need to generalize.
epistemology
Important to understand what your approach is.
Realist vs social constructionist.
realist analysis
themes that categories the nature of the social world.
constructionist analysis
theorizes socio-cultural contexts and structural conditions that enable individual accounts.
thematic analysis
A method for identifying, analyzing and reporting patterns within data.
Organizes and describes data in detail.
Interprets various aspects of the research topic.