What is Mixed Methods Research?
Summary
TLDRJohn Creswell from the University of Nebraska Lincoln introduces mixed methods research, a field he's contributed to for 25 years. Mixed methods research combines qualitative and quantitative data to provide a more comprehensive understanding of social and health science issues. Creswell discusses the importance of rigorous data collection and analysis, and the integration of both data types. He outlines various designs for mixed methods research, including convergent, explanatory sequential, and exploratory sequential designs, emphasizing the approach's growing relevance in the scientific community.
Takeaways
- 🎓 John Creswell is a leading expert in mixed methods research, with 25 years of experience and a co-founder of the Journal of Mixed Methods Research.
- 🌟 Mixed methods research is an approach that combines both qualitative and quantitative data to provide a more comprehensive understanding of research problems.
- 📊 It draws insights from various fields, including social sciences, education, and health sciences, and is exemplified in documentaries like Al Gore's 'An Inconvenient Truth'.
- 🏀 The script uses the example of basketball player Shane Battier to illustrate how qualitative data can enhance the understanding of quantitative statistics.
- 🌪 It also references real-world events like Hurricane Sandy to show how stories and statistics are often presented together in the media.
- 🔍 Mixed methods research involves collecting and analyzing both types of data using rigorous methods, suggesting a more scientific and complete approach to research.
- 📚 Creswell emphasizes that mixed methods research is not just about using the term 'mixed methods' without following rigorous procedures.
- 🔄 It is more than just having both types of data; it requires integrating them in a meaningful way to augment the understanding of the research problem.
- 📊 The script outlines different designs for mixed methods research, such as convergent, explanatory sequential, and exploratory sequential designs, each with its unique approach to data collection and analysis.
- 🏛 Advanced mixed methods designs can incorporate elements like experiments, social science theories, or community-based participatory research to enrich the study.
- 🌐 Creswell invites further exploration into mixed methods research, indicating its growing importance and application in various research fields.
Q & A
What is mixed methods research?
-Mixed methods research is an approach that combines both qualitative and quantitative data in a single study or series of studies. It aims to provide a more comprehensive understanding of research problems by using both statistical trends and the stories of people's lives.
How long has John Creswell been working in the field of mixed methods research?
-John Creswell has been working in the field of mixed methods research for almost 25 years.
What is one example John Creswell gives to illustrate mixed methods research?
-John Creswell uses Al Gore's documentary 'An Inconvenient Truth' as an example, where Al Gore combines personal stories with statistical trends to discuss global warming.
What is the importance of mixed methods research in the social and health sciences?
-Mixed methods research is important in the social and health sciences because it allows researchers to combine the strengths of both quantitative and qualitative approaches, leading to a more complete understanding of complex issues.
What are the four key features of mixed methods research that John Creswell discusses?
-The four key features of mixed methods research discussed by John Creswell are: 1) Collecting and analyzing both qualitative and quantitative data, 2) Using rigorous approaches in data collection and analysis, 3) Integrating the two forms of data, and 4) Often framing these designs within a larger perspective such as an experiment, theory, or community participatory research approach.
What does John Creswell mean when he says mixed methods research is not just using the name without a rigorous procedure?
-John Creswell means that simply labeling a study as 'mixed methods' does not make it so. It requires a rigorous and systematic approach to both the collection and analysis of both qualitative and quantitative data.
How does John Creswell differentiate between quantitative and qualitative data collection?
-Quantitative data collection is usually predetermined by the researcher, based on instruments, and involves statistical analysis. Qualitative data collection, on the other hand, involves open-ended questions, interviews, observations, and document analysis, and is more interpretive and context-dependent.
What are the advantages and disadvantages of quantitative research as described by John Creswell?
-The advantages of quantitative research include its efficiency in studying large numbers of people, its ability to examine relationships and causality, and its control over bias. The disadvantages include its impersonal nature and lack of detailed participant voices.
What are the advantages and disadvantages of qualitative research as described by John Creswell?
-The advantages of qualitative research include its ability to provide detailed voices of participants, understand experiences in context, and build perspectives from the participants' viewpoints. The disadvantages include reliance on small samples and being highly interpretive, which can introduce researcher bias.
Can you explain the convergent design in mixed methods research?
-The convergent design in mixed methods research involves collecting and analyzing both quantitative and qualitative data separately and then merging the data to compare and contrast the results, looking for convergence or corroboration between the two datasets.
What is the explanatory sequential design in mixed methods research?
-The explanatory sequential design begins with quantitative data collection and analysis, followed by a qualitative phase that aims to interpret and provide deeper understanding of the initial quantitative findings.
Outlines
📚 Introduction to Mixed Methods Research
John Creswell, from the University of Nebraska Lincoln, introduces the concept of mixed methods research in this video presentation. With nearly 25 years of experience in the field, Creswell outlines the basics of mixed methods research, which combines both qualitative and quantitative data to provide a more comprehensive understanding of research problems. He discusses the importance of using various types of evidence, such as stories and statistics, to study issues in social sciences, education, and health sciences. Creswell uses examples from documentaries, sports, and media to illustrate how mixed methods research can offer a more complete picture of a situation.
🔍 Clarifying Misconceptions about Mixed Methods
Creswell clarifies misconceptions about mixed methods research, emphasizing that it is not merely using the term without following rigorous procedures. He distinguishes mixed methods from multi-method research, which involves gathering multiple forms of either qualitative or quantitative data. Creswell highlights the importance of viewing data as part of a larger research picture, considering both the type of information gathered and the philosophical assumptions underlying the research. He contrasts the methods and assumptions of quantitative and qualitative research, noting the advantages and limitations of each approach.
🧩 The Integration of Qualitative and Quantitative Data
In this section, Creswell discusses the importance of integrating qualitative and quantitative data in mixed methods research. He outlines different design procedures for collecting and analyzing data, such as experiments, surveys, and ethnographies. Creswell explains the need for rigorous methods in data collection and analysis, whether statistical or through qualitative software packages. He introduces various mixed methods research designs, including convergent, explanatory sequential, and exploratory sequential designs, and how they can be advanced by incorporating frameworks like experiments, theories, or community-based participatory research. Creswell concludes by emphasizing the value of combining different forms of data to enhance the understanding of research problems.
Mindmap
Keywords
💡Mixed Methods Research
💡Qualitative Data
💡Quantitative Data
💡Convergent Design
💡Explanatory Sequential Design
💡Rigorous Procedures
💡Data Integration
💡Research Design
💡Community-Based Participatory Research
💡Grounded Theory
Highlights
Introduction to mixed methods research by John Creswell.
Creswell's extensive experience in mixed methods research, including co-founding the Journal of Mixed Methods Research.
Definition of mixed methods research as combining qualitative and quantitative data.
Example of mixed methods in Al Gore's documentary 'An Inconvenient Truth', showcasing the combination of stories and statistics.
Application of mixed methods in sports analytics, exemplified by Shane Battier's basketball performance.
Use of mixed methods in media reporting, such as stories alongside statistics during Hurricane Sandy coverage.
The importance of combining stories and numbers for a more complete understanding in research.
Mixed methods as an emerging approach in social and health sciences.
Key features of mixed methods research, including collecting and analyzing both types of data.
Clarification of what mixed methods research is not, such as simply using the term without rigorous procedures.
The necessity of viewing data as part of a larger research picture.
Differences in assumptions and methods between quantitative and qualitative data collection.
Advantages of quantitative research, like efficiency and ability to study large groups.
Advantages of qualitative research, such as capturing detailed voices and experiences.
The rigor required in mixed methods research, including design, data collection, and analysis.
Integration of qualitative and quantitative data as a critical aspect of mixed methods research.
Description of convergent design in mixed methods, where both data types are collected and analyzed separately before integration.
Explanatory sequential design, starting with quantitative data followed by qualitative for interpretation.
Exploratory sequential design, beginning with qualitative data to guide subsequent quantitative research.
Advanced designs in mixed methods, such as incorporating theories or community-based participatory research.
Conclusion and invitation for further exploration of mixed methods research.
Transcripts
- Hello, this is John Creswell.
Well, I'm speaking to you
from the University of Nebraska Lincoln
in the United States.
I am in the Department of Educational Psychology,
and I'm going to talk a little bit today about
what is mixed methods research.
This'll just be a short video presentation.
I've been working in the field of mixed methods research
for almost 25 years.
I co-founded the Journal of Mixed Methods Research.
We've established a research office here.
I've written textbooks on mixed methods research,
and I've been teaching it for almost 20 years now.
So I'm just going to kind of run through
some of the basic ideas,
of four points about what mixed methods research is.
And hopefully you'll find this informative and educational
and learn a little bit about mixed methods research.
The thing is we might start with the broader question of
what kind of evidence do we use to study the problems today
in the social sciences,
in education, in the health sciences?
I think we can draw some clues
from looking at recent documentaries.
Take for example, Al Gore's documentary,
An Inconvenient Truth.
And this is a documentary of course, about global warming.
But when you look at this documentary,
it's a mixed methods documentary
because Al Gore
combines both the stories as well as statistical trends.
For example, he shows some pictures
of how the glaciers have changed over time
and talks about that story of change over the years.
And then in the next slide,
he is showing us some graphs,
some pictures of how these changes have occurred.
We can find it also in the sporting world today
when we look at the evidence.
For example, there's this well-known basketball player
in the United States, Shane Battier.
He was as a seventh grader,
the fourth best in the nation.
He graduated from high school.
He was considered the best.
He went on to a very illustrious college career.
Now, when he went into the professional basketball realm
and people began looking at his statistics
on how he performed,
he didn't score many points.
He didn't really snag many rebounds.
He stole a few balls, really dished out few assists,
but yet his team was winning.
But then when they started bringing in
qualitative information,
such as looking at how he blocked the opponent's vision,
how he looked at, whether the players drove left or right,
whether he talked to teammates
and how he talked to teammates,
we the qualitative evidence
that begins to supplement or augment
the statistical evidence
to have a greater understanding of Shane's potential.
We see this too in everyday events
that are portrayed in the media,
such as the stories about Hurricane Sandy and New York City,
where we get the passionate, tragic stories
of individuals who've lost property
and some have lost lives.
And those are then presented alongside the newscasters
that show the statistics about Hurricane Sandy
and give us the numeric information.
So again, we have stories and numbers
been portrayed in the media.
This leads to mixed methods research,
which in the simplest way of thinking about it
is just simply putting together the stories
of people's lives,
as well as the numbers,
the statistics of what occurs.
It's an emerging mixed methods approach
in the social and health sciences.
It combines both these statistical trends
and the stories people have developed
a complete methodology around this concept.
The whole idea is that combining both statistics,
as well as the stories,
gives us a more complete understanding
of our research problem and just one by itself.
So, I want to go through now
four key features that really illustrate to me
what mixed methods is all about.
First of all,
it's collecting and analyzing
both qualitative and quantitative data
using rigorous approaches in collecting those methods.
Combining the two forms of data,
and then perhaps framing it within a broader framework.
And what I'm gonna do now
is take each one of these four points
and I'm going to break them down
and talk about them specifically.
It's helpful too at the beginning
to think about what mixed methods is not
because there's a lot of commentary out there
about what mixed methods is,
what it is not.
Here's some of my thoughts about what it's not.
It's not simply just using the name mixed methods
without the more rigorous procedure.
In research methodology, people do that.
They drop in the term such as grounded theory,
but they really don't have the rigorous procedures
behind it.
It's more than just having
both quantitative and qualitative data available.
And it's also more than just gathering both forms of data
and analyzing them separately
without bringing them together.
Also, it's not just gathering
multiple forms of qualitative data
or multiple forms of quantitative data.
There's a term for that in the literature
called multi-method research.
So now let me go through these four points.
First of all,
what does it mean to collect and analyze
both qualitative and quantitative data?
We need to view data
as part of a larger picture of doing research.
It's the type of information we gather and analyze
to answer our questions.
It's then framed within larger questions
and framed within larger philosophical assumptions
of doing research.
So my focus is gonna be on
how we treat that data,
how we combine it in integrated
in mixed methods research,
but we need to recognize it
as part of a larger approach to doing research.
It's just one step in the process.
Now, when you gather quantitative data and qualitative data,
there are certain different assumptions that are operating
two different forms of gathering evidence.
Quantitative data
is usually predetermined by the researcher.
Is based on instruments.
We gather those instruments.
Measuring performance attitudes, observations.
We then do statistical analysis
and we make an interpretation.
Qualitative has the different type of methods going on.
It's an emerging methods
where we don't necessarily start
with a predetermined instrument.
We ask very open-ended questions.
We often conduct interviews, observations.
We look at documents,
we might look at email messages.
We might listen to sounds.
The Ray of qualitative methods
that are collected data that's collected is very broad.
Then we take that information and we analyze it.
I say, we analyze text or image data,
and we build up a picture of what theme or patterns emerge
from talking to people.
So I see the methods for quantitative and qualitative
being very different and having distinct features.
Now both methods have advantages.
Take quantitative research for example,
it's really useful for studying large numbers of people
across a wide geographic area.
It's a very efficient method of data collection.
We can start looking at the relationship
among concepts or variables.
We can even look at whether something causes something
cause and effect.
We can control for bias carefully,
and people tend to like numbers,
but we also know there's a downside
to quantitative research.
It tends to be impersonal dry.
We really don't hear the words participants.
Often we don't go out to the actual setting
where things are occurring.
It's largely driven by the researcher.
Now qualitative research
has some distinct them just too,
we can hear those detailed voices of people.
We can understand their experiences
and their actual settings where things are occurring.
Your whole idea in qualitative
is to build the perspective up
from the views of participants,
not from the researcher's perspective.
So it's more realistic and people like stories.
Some of this limitations,
well, it often draws on small samples,
so we can't really apply it across a large number of people.
It's also highly interpretive.
And it also relies on the researcher's interpretation
to make sense of these stories that individuals provide.
So mixed methods secondly, is rigorous.
What constitutes a rigorous quantitative study
and a rigorous qualitative study?
We need to attend to different perspectives about design,
such as using a design procedure.
In quantitative, this will mean experiment
or correlation or survey.
Whereas in qualitative, it might mean
using a design such as ethnography, grounded theory,
phenomenological study.
We also need to attend to how we collect the data
from sites, permissions,
a systematic or a purposeful sampling,
an adequate N or number of people that we study.
We need to have multiple forms of data collection.
We need to go through a rigorous procedure
of analysis of the information,
whether it's a statistical analysis,
such as descriptive, inferential,
using statistical packages.
On the qualitative side,
whether it's using qualitative software package
and then building from the codes to the themes,
to the larger perspectives.
So we need some rigorous methods
when we do mixed methods research.
That gives it more of a scientific form.
Third, and this is maybe one of the most important
and one of the most confusing parts
of mixed methods research.
We need to integrate these two forms of data.
We need to bring the qualitative
and the quantitative together.
Now there are some designs out there
in the mixed methods field that have emerged.
And these have developed over maybe the last 20 years.
The first one we call a convergent design.
Basically what we're going to do here
is we're going to collect quantitative data, analyze it.
And at the same time,
we're gonna collect qualitative data and analyze it.
So the quantitative might be a survey.
The qualitative might be an open-ended interview
with some people.
We're gonna gather these two databases,
and then we're actually going to merge the data,
bring it together
and basically we're going to compare the results
to see when we ask people questions
and talk to them as in qualitative
and we gather information on instruments,
whether the results from these two databases merge
and are comparable,
that's a convergent design.
The next is an explanatory sequential design.
It's a very popular one
in the social sciences and health sciences.
We're gonna start by collecting quantitative data,
analyzing it.
And then from those results,
we're then going to build in a second qualitative phase
where we follow up.
So the whole idea in this design
is to interpret the quantitative results
using the qualitative data.
Now we can reverse this and we have an exploratory design
where we're gonna start not quantitatively
but we're gonna start qualitatively.
So we start with the qualitative data collection
we explore and come up with findings.
We then use those findings
to then follow up with a quantitative phase.
For example, we might use qualitative findings
to develop a new instrument
because there aren't existing instruments out there
to measure a certain phenomenon was a population.
So this is a good design for that.
So I call it qualitative exploration
then leading to a quantitative test.
Now there's one more step.
We can move beyond these three basic design
to more what we call advanced designs.
So within a basic design, we can add to it,
think about a basic design
that we're then going to surround it
with a more advanced design.
We're gonna put some more features into it.
For example, we might do an experiment
within which the conversion design is used.
We might do a case study,
we might use a theoretical model,
social change model for example.
We might use a social science theory model.
One of the popular approaches here is to do an experiment.
And within that to use a convergent basic design,
where we gather both quantitative and qualitative data
and bring them together.
Another one would be to use a social science theory
that surrounds an explanatory sequential design.
So the theory that kind of guides the entire study,
it provides a framework for which we then
start quantitatively and follow up qualitative.
Another popular one that's emerging
is a community-based participatory research.
That's a framework for engaging the community
and getting them involved in decisions
throughout the research process.
We might use that in an exploratory sequential design.
So those are four of the basic ideas
of what mixed methods research is.
It's collecting and analyzing
qualitative and quantitative data
using rigorous procedures
combining or integrating both forms of data.
And then framing often framing these designs
within a larger perspective,
such as an experiment of theory
or a community participatory research approach.
Thanks for your time.
We look forward to hearing more
about mixed methods from you in the future.
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