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Researching Diffusion of

Innovations Using a Mixed

Methods Design

Video Title: Researching Diffusion of Innovations Using a Mixed Methods Design

Originally Published: 2017

Publishing Company: SAGE Publications Ltd.

City: London, United Kingdom

ISBN: 9781473975736

DOI: https://dx.doi.org/10.4135/9781473975736

This PDF has been generated from SAGE Research Methods.

https://dx.doi.org/10.4135/9781473975736

Hi, my name is Tad Foster. I'm a Professor at Indiana State University in the Department of Human

Resource Development. I'm going to talk to you today about a research project that I did several years

ago-- in fact, one of my earlier research projects-- in which I used mixed methods. The decision to

use that technique was based on the kinds of information

that I was looking for. We'll get into that in just a moment. For today, for this presentation, I'm going

to give you a little bit of the background-- a little bit of the context of this study-- but we're going to

focus our attention on the design, the procedures that were used, the data collection, data analysis,

and then wrap up on the findings and conclusions. We'll end with the lessons that I learned,

and there were several lessons in this project. In practically every project you do there will be multiple

lessons, some of which you intended to get because you were asking certain questions of your

subjects and of your design, but others that you're going to learn because you have those oh, dang

moments-- or some other-- that have taught you

something that you weren't expecting to learn. In this particular case, we're looking at the

microcomputer. Back in the day when I did this, this would have been the way we would have talked.

I did a study on the use of the microcomputer

by public schools teachers in the high schools of Illinois. I basically was able to scan the entire state

by using a specific selection process of the school districts that were going to be employed. What I

was looking at was based on the work of E. M. Rogers. I was trying to find out what was going on

at the psychological level with teachers as they were thinking about this innovation. Rogers wrote

several books on the issue of diffusion of innovations. How do innovations start from, they're out there

in the world and we become aware of them to the point at which it's actually being employed and

used in the social unit?

He's been studying that for a long, long time. He's now passed away, but his books are still used in a

lot of research contexts. It takes a look at what I always argued as an aerial view, or a sociological

view, of the issue-- of looking at it, say, from above and looking at the various nuances of the system.

What I wanted to do was to get down inside because one of the things that I did have concern about

with regard to Rogers' work is the issue of people's personality types. He went through great lengths

to talk about innovators, early adopters, early majority, late majority, and laggards. As you read his

book you get the impression

that these are psychological constructs. In other words, an individual who is an innovator is an

innovator in all aspects of his or her life. I couldn't buy that proposition without additional data and

went into it to do that. One of my concerns was that I was unsure that I would be able to get enough

data to answer all

the questions that I needed to know by just simply asking questions in a survey-- handing out a

questionnaire and having people give it back to me. And we're going to basically talk about putting

together two designs that some would argue shouldn't be put together, and others will argue, yes,

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they work together quite well. If we think about mixed methods in general, first of all quantitative

designs are such that we want to state in advance, prior to doing anything-- in fact, we call it a priori

designs-- because we are designing everything.

We are choosing all of our variables, we are choosing how we're going to relate those variables,

we're going to choose how we collect the data, from whom, and then-- once we have the data-- what

we're going to do with that data. We have all those decisions made before we collect one bit of data.

On the qualitative side, we tend to take the argument

that we want the situation to speak to us. We're not wanting to say what we're going to find, we want

to go in there and find it. Again, we're going at it from, perhaps, a completely different philosophical

position. Whereas in the first case, we seem to be arguing, we know what's important, we know what

we need to collect,

and we know what we need to do with it once we collect it. We are more concerned about specifying

the effect of something on something else, or the relationship of something on something else when

we do this in a constructivist point of view. But when you're doing it from more of an existential point

of view you're trying to let the situation speak to you.

What's important to them? What's going on there? And the variables-- the themes-- will emerge out

of that qualitative data collection and analysis. Recently, the mixed methods approach has gained a

great deal of popularity. We now have a professional organization

that is holding conferences. Books are being written. SAGE Publications has several books on mixed

methods now, as do other publishers. We are recognizing that there are reasons why we would start

out by wanting to mix the two together. Now, in this case, Creswell, in his most recent book, talked

about three primary reasons.

They're not exclusive reasons-- they may not have even come up when I was thinking about them--

but they do make a nice qualification system. Let me just run through them real quickly. First of all, he

calls some studies convergent studies, where we're trying to compare data from the multiple sources

and collect it holistically-- collecting it and bringing

it to bear on the questions that we're trying to answer. The second category was explanatory

sequential. Essentially what we're using is the qualitative data set to help us explain the quantitative

data. I would say that the study I'm going to talk to you about was that kind of study.

I needed multiple bits of data. The quantitative data was going to tell me what the teachers were

willing to do at that time-- what they were willing to say to me. I have great reservations, personally,

when it comes to the survey design. I don't want to go so far as to suggest that all people are

liars, but all people tend to put themselves in the best context, so I needed to be able to analyze the

data in ways I felt deeper than I could get if I were just going to compare variable A against variable

B, or the number of independent variables that I collected

and comparing them to the dependent variables. I'm going to learn a lot-- it's unequivocal-- and I'm

very comfortable and confident that I will learn what I need to know by that, but then it becomes the

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business of, how do I interpret it? I don't know the context that these people live in, and so I've always

argued through my years of working

with graduate students that we should not only collect the data that we absolutely need, but we should

know the context. And there are many situations-- in fact, much of graduate education, where people

are trying to get graduated in a reasonable length of time-- requires them to use methods that are

quick

and, consequently, they tend to be dirty. That is helped if we can find ways to provide context-- so

using the qualitative data to help us explain the quantitative data that we have received. The final

category is exploratory sequential. Here you're basically arguing that we don't know enough

about the situation, and that if we'd collected some data in advance, qualitatively, from a group of

subjects, we could then start to narrow in on the variables that were important. Then we can build the

measures necessary to do the quantitative analysis of that same phenomenon

that we're taking a look at. We're not sure what our independent and dependent variables are. We're

not sure what's really important in this context, and so before we start looking at cause and effect or

correlational relationships, we are simply going to try to narrow down the variables

that we're going to need to be looking at. This could be likened to when you build a survey instrument.

It's not uncommon to go out with a survey instrument and say to a group of people, just write in your

answers, I'm going to just ask you a big question like why don't you vote? Put down whatever comes

to your mind

and then from that you can extract the important issues that people are bringing up. Then you can

build the variables that you would be looking for that you would go out and survey a much broader

population or sample of people. In this case, again, we are going to be taking a look at why public

school teachers were

or were not using the microcomputer. As I said earlier, I'm trying to provide a psychological dimension

to the diffusion of innovations research. Since then, I have branched that out into multiple directions,

but at this point I was relatively new to the concepts-- to the ideas-- and trying to understand this

whole business of,

it is possible to change? Everything that I had read up to that point said, most people don't want to

change. OK, but I still couldn't answer why, at least definitively. There were lots of good studies that

had been done, there was a lot of research available at that time, but I was

unsure on a number of occasions, a number of issues, such as, for example, I tend to be an early

adopter, but am I an early adopter always, under every circumstance? I don't know this. And why are

people early adopters? Rogers had some ideas, but there was not enough research

out there to adequately answer these questions, so I decided as a part of-- in fact, it was my

dissertation research-- to take a look at a group of people being asked to change. It just so happened

that I was an educator at that time, and, therefore, focusing my attention on teachers. It could have

been any group. It could have been truck drivers.

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It could have been nurses at hospitals. It could have been a variety, but I had a good working

relationship in the public schools, and I knew that I could get the data that I needed, and so therefore

I chose that as my population. In order to do this study-- as you will with any study--

you've got to ask yourself questions such as, what data do I need? The literature is speaking about

what is important, but the literature also has holes in it, and those holes are important because they

identify the reason why you're going to do the study in the first place. So I've got a reason for doing

the study, and I've defined a population that I'm

going to use for this study. But I realized that I couldn't make the argument that any school district

or any set of teachers in the state would be reasonable. I wanted to be able to generalize to a much

broader group than just, say, going to the local high school where I was a former teacher,

for example, or going to a variety of high schools near the university where I was going to school. So

I created a much more complex randomization system. We refer to it typically as a strategic random

sampling, or a categorical random sample is sometimes used.

So what I'm going to do is I'm going to stratify my sample on two important variables. I felt that there

would obviously have to be a difference in the size of the schools that the teachers were teaching in.

That a school district that had 14 teachers in it-- like my first high school that I taught in-- I

was one of 14 teachers in the school district that taught high school. Then I moved to another district

that had 120 teachers in it. I knew of districts in the state of Illinois that had only high schools--

they were actually an entire district, and that community had an elementary district, a middle school

district,

and a high school district. Just in terms of how much money teachers in those districts had a chance

to spend was enough of an indication that I needed to include some from each of those. So using a

definition that the state put out, I said, I'm going to have some small schools, I'm going to have some

middle-sized schools,

and I'm going to have some large schools. In addition to that, in the state of Illinois-- as it is in many

states around the country-- you have a city and a lot of other much smaller cities. We had the Chicago

School Corporation school district, and we had Springfield, we had Champaign, but as soon as you

leave Chicago and leave

the suburbs and the city proper, you go down in size precipitously. These are much smaller school

districts, so I also employed on the second level-- in the second arm of the stratification-- the urban,

suburban, or rural. I wanted to make sure that I got differences

in ways of living in addition to the size of the budget, and went with both sides of those. Now I took

the state's list of schools and I basically put every school district in the state into one of these six

categories. Then I selected at least two from each of those categories

and went out and started collecting data. This was a way for me to be able to argue that I have

adequately polled the state. In other words, every school district in the state had a chance to be in

the subject pool. I wasn't leaving anyone else out. The ones that were in there were in there because

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of chance.

They were randomly selected, so therefore when I got done I could at least argue that every district

in the state of Illinois ought to pay attention to my findings. Now I actually thought that it would

generalize much broader than that because I don't think that there is really that much difference,

but, technically, according to research methodology, I would have to argue that my population is high

school

teachers in the state of Illinois, and I had randomly selected an appropriate grouping so that I could

argue back to that group when I got done my work. Let's take a look at procedure. How do you go

about-- now that you've got the study arranged-- you know what you want to do.

I'll get into the exact questions that I was looking for in just a moment, but let's take a look at

procedure and I'll build those two together. Procedure and design, we'll build them together as we go

on here. The first thing that I knew was important was getting support. Today, we have the issue of

IRBs-- Institutional Review

Boards-- which make it much more demanding to ensure that you have done a great deal of work in

advance so that you have the right to go into that environment and work with human subjects-- that

you have taken the necessary precautions. In the day that I did this study it was not required.

This was before IRB requirements and so I needed to put together all of the procedures. And keep in

mind-- and at that time the most important thing was, am I going to be successful in getting the job

done? I'm concerned about such things as, am I going to be allowed in the door?

Now, as I said, I was a high school teacher myself for many years, and I had lots of colleagues around

the state. I was a president of a state organization, I knew a lot of people throughout the state of

Illinois at that time, and I knew I could get my foot in the door. But now, remember, I have randomly

selected a group of school districts that I'm going to be working with

and I don't know all of those people. And I do know that superintendents and principals tend to get

a little bit concerned when strangers start walking the halls. In fact, you are not allowed-- even back

then-- you were not allowed to do that. You had to check in at the office. Without permission I knew

that I couldn't get this study done. So that was the first step.

I also thought that getting this permission and support would help me in getting returns from the

teachers themselves. I didn't want to have to take the time-- it turned out that there were going to be

604 teachers that I was going to be surveying. Talking to 604 people and getting their permission is

rather impossible, so the permission

was going to be at the front. If you complete this instrument you are giving permission to participate

in the study. But, again, before I could go in the door I needed to lay this out, so I took my proposal in

a very tidy, little abstract, to school boards and superintendents, got their permission to do the study.

Here's how I'm going to protect people's confidentiality. I'm not going to get into anyone's way. I am

going to do this in innocuously so that the teachers aren't bothered, the students aren't bothered, your

educational process is not going to be affected by me being there. In addition, I wanted to show them

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what

I thought I could do for them. As a result of my work, you will get a copy of the data, you will get some

assessment information about your school district and about what's going on in your high school with

regard to computers, and I think you'll find this information valuable. So I laid out the study in front of

them and got their permission.

Then from the superintendents and boards I went to the individual building principals and got their

support. At this level I thought that it would be very helpful if, together, the principal and I told the

teachers what was going on and why we were doing it.

What's the study all about? Why are you being asked to participate? And, oh, by the way, it is now

being sponsored by the school district. They are on my team, if you will, and I felt that that would in

fact improve my return rate when I gave the teachers the questionnaire that I was going to give them.

It turned out that I was right.

I received 67% of the instruments back completed in a way that I could use them, and a 67% is a

reasonable return rate-- in fact, today it's a rather sizable return rate. My students are often struggling

with 25% and 30% return rates and having to do Herculean efforts to get their return

rate up high enough to be able to report their findings. So getting a 67% return rate and having all the

other qualitative data that I collected, I really felt like I had something that I could argue with and work

with as I went forward with my data analysis and writing up my final report.

Now we're going to go in and survey the teachers-- all the teachers-- and we're going to case study

the school. Again, this is a modified case study because I'm not able to let the system talk to me. I'm

not going in to spend six months or a year.

I'm not going to allow all of this to just come to me. I'm going in with a very specific purpose. Let's

take a look at that purpose and you'll see what I mean. I have to modify the case study methodology

in order to fit my need, and that's why we're not going to refer to this as a case study, per se, but more

as a mixed methods research design. We're basically going to look at a number of independent

variables and compare them to an important dependent variable, and that is, to what extent are

teachers using the microcomputer? I'm going to look at such things as age, gender,

educational level, years of teaching experience, the kind of subject that they're teaching, their

perceptions with regard to a computer, their use of AV equipment-- for example, I thought, well if

people don't use overhead projectors and they don't use slide projectors and other things that we

currently have available, why would the microcomputer be treated any different?

I wanted to get their own perceptions of self-efficacy based on Bandura's work and others. There was

this topic at that time talked about regarding computer anxiety, and a great deal of attention was being

paid on how anxious does this machine make people feel? I also wanted to know their perception--

their personal perception-- of innovativeness. How innovative did they consider themselves to be?

And finally I wanted to see how engaged they were beyond simply teaching and doing a job.

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Were they, in fact, engaged in professional organizations? Did they stay in the literature? Were they

involved in any kinds of other things outside it

that improved their professionalism? So those were my independent variables that were going to be

compared to the dependent variable degree of computer use. Now, again, this is the quantitative side

of the study. I'm simply going to be looking at, how can I compare these variables? If I find a serious

variance in the amount of use

of the computer, which of these independent variables give me a good explanation as to what is going

on? But I think you can already see that, yes, that's all fine and well, but you still don't know enough.

You're not going to be able-- when someone answers all my questions and I've thought up

what I thought was important with regard to computer anxiety, do I really understand what's going on

in that person's mind? And the answer is no. And I know, as a counseling psychologist, that I'm not

going to be able to get inside until I start talking with people. So this is one instrument that allows me

a shortcut, but it's a snapshot in time-- in their frame of mind

at that point in time-- and I felt that I needed more data. So this was the other side of the coin, and that

is the research questions that guided the case study. The modified case study side of the study was,

what is the history of computer use in this district and by this individual? And how is the computer

being introduced-- or how was

it introduced-- into the environment? How did they learn of this innovation? And how do they even

define this innovation, which you'll find is different for whomever you talk to. You'll see that as we look

at some of the data that came out of the study. And then the history of innovation--

is this an institution that you would say is traditional or is this an institution that you would say is

cutting-edge? Again, see how subjective this is. I'm allowing the system to talk to me and making

some understandings based on what I've learned in collecting this qualitative data. Finally I wanted

to know where all the computers were,

who was using them, how were they being used, what courses were being taught, and all of those

kinds of things. Again, remember this study was done-- what we would say-- early in the diffusion of

the microcomputer process. This was well in advance of inexpensive microcomputers. It was well in

advance-- years, in fact,

it was more than a decade in advance-- of the internet, so we're talking about a very early stage in

this particular innovation. That's another issue that would come out of this study-- that, as the age of

the innovation changes and it gets older and older and more and more developed, things change as

to people's reactions

to it. That's why Rogers' model goes in this direction. It talks about innovation over a period of time.

All right, so on the first day of this study I would show up at the school district, I would sign in, I would

get my name badge, and be ready to go about the halls. I would have a cardboard box with me,

and I would have one instrument for every teacher in that school. I would turn to their mailboxes, and

I would put a survey in each person's mailbox. Again, this was back before internet, this was back

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before e-mail-- none of the SurveyMonkey or Qualtrics or any of those kinds of things. This was pencil

and paper.

It was a seven page instrument. I was very concerned about that, but nonetheless, 67% return rate,

seven pages wasn't too much and they were willing to do it. Put them all in their mailboxes with

instructions that, throughout the day, when they finish it, just put it in the box which was on the counter.

The principal's secretary kept an eye on the box,

and people would put their surveys back in there. Then I would get my notebook out and I would start

walking the halls of the school. So for the rest of day one, after I'd done that, I'd introduce myself, I'd

start walking around, explain why I'm there, and just started interviewing everybody on my list. I felt

that it was important to interview the principal,

to interview the guidance counselors, and to interview anyone who was in any way connected

to a computer. So I went around the building, I found where the computers were, I scheduled

appointments with the teachers, I even watched some classes as they were going on, but I made

sure that I had an interview guide sheet in advance. If I were going to talk to teachers,

what do I need to know from them? If I were going to talk to an administrator, what do I need to know

from that individual? If I talk with students, what would I need to know from them? What would I think

that I need to know? Because, again, with the qualitative methods, what we're going to do is we're

going to listen, and listen carefully. And this leads to a data collection and data analysis

issue. One of the things that I don't like doing is to spend my time making notes. I also don't like to

use a recording device primarily because a recording device changes the situation with the individual.

Individuals being recorded tend to get nervous

and, consequently, I want it to be a natural setting. I want to sit down and I want to talk with the

person. I want to help them to recognize I'm one of them. I understand their daily routine. I understand

how important their free time is. I understand and I wanted to have this to be an open conversation

between two colleagues

and I used all of my interviewing skills to do that. I'm a counseling psychologist, I've been practicing

years and years on how to ask the appropriate questions, how to get feedback, but I don't know what

they're going to say. So I may have a set of questions in front of me and I'm ready to ask these

questions, but before that interview is over

they may turn a light bulb on for me and, suddenly, I'm making a little note to the side that I need to

ask more questions about this because if this is true then I've really got something here that I need to

pay attention to. As I went on, the interview guide sheet is going to be adjusted-- and I want to make

sure that I do this for everyone--

but I'm learning things. I'm going to start with my basic questions, but I will end up with an ultimate list

before I'm done. So I'm listening to you, I'm interviewing you, and I'm getting answers to my questions.

I'm making notes, but I make minimal notes basically focused on facts-- facts that I am likely to forget.

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So I've got a pad here, I've got my questions, and I'm going to write down-- without, perhaps, even

stop looking at you-- I'm going to keep looking at you and write without looking at my notes, and make

those brief little comments there. Then the important thing happens-- and I've got my nickname for

it-- called the brain dump. I'm going to leave this interview

and I'm going to find a way for me to get to my computer or to my notebook and sit down and write

the answers to the questions fresh in my mind. I've got the interview guide sheet and I can go back--

all right, what did the person say about this? And start writing. Now I recognize that some things drop

out,

but I have found that I don't lose that much. If I can get to a machine quickly or to my notebook

quickly after the interview, I can then write out my notes, get the answers to the questions, even get

the quotes that I'm going to need to make this real when people read it later on from that interview

without having

to spoil the interview by writing notes all the time. Again, I don't like to interfere with a recording

device. I don't like to interfere by not looking the person in the eye. I want to get a dialogue going with

the individual and get them sharing honestly and openly.

Here's what I found. First of all, I found that there was limited access. We were talking about an

innovation that had struck. We were talking about an innovation that was clearly relevant to teachers,

clearly relevant to basically everyone at that point in time. Today we can't live without it-- most people

agree--

there was no question about it whatsoever, but in this day there was a huge question as to why this

was needed. In fact, one of the important things that I learned was the definition of the innovation

change depending on who I was talking to. If I talked to a math teacher, the computer

was needed because that person was teaching students how to think logically, and programming was

essential. They were going to program. They were going to use mathematical algorithms to develop

software. If I talk to business teachers, I heard about management information systems,

and I heard about databases, and I heard about word processing-- making what they used in

business. If I talked with superintendents and principals, I heard, we need computers because our

students need to be computer literate. When I talked with teachers, I virtually never heard about what

benefit it was to their students.

I only heard what benefit it was about to them. So here we were talking about an innovation and one

of the first things that I learned was, but whose perception of the innovation are we talking about? A

single innovation is not a single innovation. Even your telephone is not just a telephone-- and today,

with our smartphones. We clearly understand that innovation is multiple things to multiple people. So

it was very important when I went into a district and learned that the superintendent and the board

of education's goal was to have computer-aided instruction so that they could eliminate a number of

teaching positions

and reduce their budget. Wow, that was an incredibly important finding because what I was hearing

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from the teachers was, there is no way that a machine can do my job better than I can do my job, and

immediately could see that, well why would someone want to use something to eliminate their jobs

so that they would have to do something else?

It was an important revelation and had to be factored into the theoretical underpinnings that I was

dealing with as I was thinking about the study. So I found that there was limited access to the

computer, I found that there was differences in the opinion as to why the computer was needed, but I

did find that approximately 60%

of the teachers were in fact using the computer. They were using the computer primarily as a word

processor. They had no need for computer-aided instruction, they had no need for databases, they

had no need for spreadsheets-- at least they didn't think they had any need for those things. But they

did have need for handouts. They had a need for tests.

They had need for quizzes. They had need so that they didn't have to type it over and over and over

again, which is what I was used to. We were in a day of typewriters and ditto masters, where you

mass-produced with spirit duplicating machines. And here was a device that had a memory, and I

could record my test and put it on a disk

and I could replicate my work and become more effective. Personally, my job got easier and a little

more fun. I didn't have to worry about all of this, am I ready for class? No, I can just bring it off the

computer and go in. So I'm learning this as we went along here. On the other side, when we got to

the quantitative side

of things, I learned a great deal there as well. First of all, the old adage that you can't teach an old

dog new tricks is not true. There is no relationship between age and an individual's willingness to use

innovations. As a matter of fact, even in that day you could go to community-based training programs

for this new innovation called the microcomputer

and you would find as many older people as you would younger people. Age in many studies has

dropped out to the point where, from this study on, I did not use age as a variable again. We can

argue that we've settled this issue. When it comes to doing things differently, a young person is no

more likely to do something

than an older person is. The same thing can be said true for gender. It is no more likely that a

man is going to do something differently than a woman. The same thing went for education level.

Interestingly, this variable-- educational level-- was 100% different from what Rogers argued that his

innovators and early adopters

tended to be high early educated and more affluent individuals to be able to afford and have the

wherewithal to participate in new innovations. That doesn't seem to hold in this particular context and

had to be factored into our theoretical thinking. Everything else, however, was strongly related.

Your perception of the value of the innovation obviously is going to impact whether or not you want to

use the innovation-- your anxiety levels, your abilities, your confidence levels in yourself. The issue of

innovativeness did show up to be statistically significant and strongly related to the willingness to use

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the microcomputer,

but I immediately recognized that this variable is contrary to what's really going on. Let me put it this

way-- it goes back to the issue about using a survey to ask people what they think. The people tell

me on the survey that they're highly innovative. Their behavior tells me that no, they're not.

In fact, you can read study after study after study that will say to you, a human's reaction to doing

things differently is to resist or to reject it. To find ways to say no. Since then I've come up with a

model that argues that. I think what's going on is that, in most cases,

when you first start looking at an innovation, the costs of implementation-- of buying it, of learning it--

to your sense of self-- I'm a really good typer, I know how to do it until I get on this computer and now

I'm incompetent. All of those things weigh in on the costs side.

So the costs are extremely high, especially early in the innovative process. And that has to be

weighed against the benefits side. What are the benefits? It can do this a little bit better. Yes, a little

bit better. And people are talking about what it can do for others. And, oh, by the way, the employer

in most cases

is going to get a lot more out of this than I'm going to get out of this. I'm just going to be doing more

with less. All of these are really good-- costs with minimal benefits. It's like saying, are you willing to

spend $50 to get $5 worth of merchandise? And the answer is, of course not. That would be silly. I'm

looking for a sale.

It is usually the case that when people are presented with the opportunity to change-- to do something

different-- to employ an innovation that has been out there for quite some time, that they're going

to say no. Those reasons are based on previous experience. Those reasons are based on their

perception of the cost-benefit analysis and whether or not that innovation has any personal relevance.

That's exactly what I learned when I did this study. It's led me to further studies and developing of a

theoretical adjustment to what Rogers and others have done at that time. In this study, we had the

opportunity to collect data from multiple sources

and use the qualitative data to analyze and interpret the quantitative data. We learned a great

deal from this, collected a lot of the data in a short period of time, and were able to add to the

understanding of what goes on when innovations are being diffused through a social unit.

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Page 12 of 12 Researching Diffusion of Innovations Using a Mixed Methods Design

Researching Diffusion of Innovations Using a Mixed Methods Design