2.3.3: Mixed-Methods Designs
- Page ID
- 225905
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- Define mixed methods research.
- Differentiate between qualitative and quantitative data within the mixed methods approach.
- Compare and contrast sequential and concurrent mixed methods designs
Mixed methods are research approaches that combine both qualitative and quantitative data collection and analysis methods within a single study. This type of approach aims to gain a more comprehensive understanding of phenomena. There are two categories of mixed methods designs: sequential and concurrent (Creswell & Plano Clark, 2007).
Sequential Designs
Explanatory Design
The explanatory design starts with quantitative data and results, and is followed by qualitative data and results, before drawing conclusions. An example of this is the Ages and Stages Questionnaire. Parents or professionals initially rate children based on specific developmental skills and whether those skills can be done not at all, sometimes, or always. At the end of the questionnaire, open-ended questions are asked to provide more context for how the assessor scored the child.
Figure \(\PageIndex{1}\): Explanatory Design by Heather Carter is licensed CC-BY-SA 4.0.
Exploratory Design
Exploratory design is the opposite of explanatory- the design starts with qualitative data and builds to collecting and analyzing quantitative data before drawing conclusions. An example of this is rooted in the process for determining whether children need developmental services. The process usually starts with observations to determine what a child can and cannot do. Let's pretend the child is having difficulty getting dressed, feeding, and self-regulating. The Vineland Adaptive Behavior Scales can be used to quantify a child's adaptive skills and assign a score. The score is interpreted to aid in determining the diagnosis of an intellectual or developmental disability, as well as to determine whether the child qualifies for developmental services.
Figure \(\PageIndex{2}\): Exploratory Design by Heather Carter is licensed CC-BY-SA 4.0.
Sequential Embedded Design
In this design, qualitative data collection occurs first, followed by a quantitative intervention, and then another round of qualitative data collection after the intervention. Typically, the initial phase informs the next phase, so they are "embedded" in a sequence, with one phase building on the findings of the previous one. This approach allows researchers to deepen their understanding by using different types of data to explore a topic more thoroughly.
For example, in phase 1, you might observe a child struggling to navigate spaces. You recommend that the parent have their eyes checked. In phase 2, the parent takes the child to the optometrist, where an eye exam is conducted using quantitative measures. It is then determined that the child needs corrective lenses. In Phase 3, you observe the child, now wearing the corrective lenses, to see if they can navigate spaces with ease.
Figure \(\PageIndex{3}\): Sequential Embedded Design by Heather Carter is licensed CC-BY-SA 4.0.
Concurrent Mixed Methods Designs
Triangulation Design
In triangulation design, both qualitative and quantitative data are collected and analyzed simultaneously to examine a topic from different angles. The purpose of using this design is to see if the two types of data support each other, or "triangulate," leading to a more robust and comprehensive understanding of the research problem.
In a triangulation design, researchers compare the results from both data types at the end of the study. If both data sources agree (or "converge"), it strengthens the findings. If they disagree, it can provide insights into why differences exist or highlight different aspects of the research topic that might have been missed with only one method.
Figure \(\PageIndex{4}\): Sequential Embedded Design by Heather Carter is licensed CC-BY-SA 4.0.
Embedded Design
In this design, quantitative data collection happens first, followed by a qualitative intervention process, and a quantitative post-test. This is similar to the sequential embedded design except that the type of data collection is flipped.
For example, in phase 1, a reading assessment might be given to incoming first graders to determine how many sight words they know. The number is identified and determined to be low; so, in phase 2, the professional applies reading intervention strategies. After two weeks of support, the professional moves to phase 3 by administering the reading assessment again to determine if the strategies were effective for the child, as evidenced by the comparison between the new score and the previous one.
Figure \(\PageIndex{5}\): Sequential Embedded Design by Heather Carter is licensed CC-BY-SA 4.0.
References, Contributors and Attributions
Creswell, J. & PLano Clark, V. (2007). Designing and conducting mixed methods research. Sage.