Methods Designs

Rationale for mixing

Consensus on terms and concepts

Research questions and their importance

Explanatory, exploratory, and triangulation designs

Rationale for Mixed

Methods

Why mix in the first place?

Qualitative = depth
Consensus?
Not Even in Mixed

Methods

Small and big disagreements

Statistical analysis, how much to mix…

A lengthy undertaking
No Hard Answers, But Some Direction

Questions guide your
designs

Questions guide the
collection of data

Questions guide your
analyses
From Questions to Design

What makes for good mixing?

Aren’t descriptive statistics acceptable?

Do I need to actually define a design or can I just
incorporate methods like surveys, interviews, and
focus groups?
Explanatory

Personal reflections…

Where’s the emphasis?

Why?

Design:

Quantitative data collected followed by qualitative data collection;
qualitative analysis helps explain quantitative results
Quantitative data
collected
Qualitative helps to
analyze
quantitative results
Qualitative data
collected
Exploratory

Where’s the emphasis?

Why?

Design:

Qualitative data collected; then quantitative collected; quantitative
analysis explains qualitative results
Qualtitative data
collected
Quantitative helps
to analyze
qualitative results
Quantitative data
collected
Qualitative and
quantitative collected
together and then
analyzed together!
Triangulation

Triangulation is corroboration

Where’s the emphasis?

Why?

Design:

Quantitative and qualitative data collected and analyzed then both
quantitative and qualitative analysis techniques are used to explain the
results
Wait a Minute?

Terminology!
Wrap

Up:
Final Thoughts and Critical Questions

When mixing methods, is there a good rationale provided by the
researcher? What is it?

What are the guiding questions and, if relevant, hypotheses?

How has reliability and validity been addressed within the study? (Hint:
the principles within each approach are the same).

What approach ultimately was taken? Why? Does it align with the
research questions?

Are there appropriate designs identified? If not, why? Can you identify
the designs if they are not identified?

What analytical methods are appropriate to it all?
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