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9: Computers and Qualitative Analysis

9: Computers and Qualitative Analysis

Tải bản đầy đủ - 251trang

198 Chapter 11


Figure 11.2 Coded Text in MaxQDA

models, and theories. Researchers can relate the various

materials by coding relevant sections of text, by linking them,

or by writing about them.” Software allows you to enter

codes, sort by codes, add comments to texts, run multiple

analyses by adding or dropping different categories, and

generate a variety of custom reports. In other words, they

work similarly to quantitative analysis programs.

Software packages also facilitate team projects. By setting up a software “project,” users create a shared space in

which all data files, code systems, supporting materials,

queries, and output are kept and managed. With a common interface, multiple users can update or view the data

without overwriting each other’s work.

Figure 11.2 shows a screenshot from MAXQDA in

which the text of an interview has been coded by the

researcher, with paragraph numbers inserted by the program. In this excerpt, the entire section of the interview

is marked with the code “work issues,” while the one

paragraph shown is marked with the codes for “interests”

Figure 11.3 Network Output in ATLAS.ti

and “education.” Users can perform searches for all data

within any project folder with specific codes or combinations of codes. You can also run summary information

for each case (interview). In the screenshot shown in the

figure, you can also see that the researcher has attached a

note (■) to the paragraph.

Qualitative software programs also offer a variety of

visual displays of data in multiple forms, often interactive.

Figure 11.3 shows a network view of links among different

data sources, produced by ATLAS.ti. The visual representation is informative on its own, revealing connections among

different data segments. Additionally, the user may select

which codes are included or excluded from the output, in

which combination. In the language of the software, this

view shows different data objects and their relationships.

Qualitative analysis software packages offer a variety

of visual displays to help researchers discover, analyze,

and present relationships within their data. Figure 11.4

shows a word tree relating a single-code category to the


An Introduction to Content Analysis 199

Figure 11.4 Word Tree in NVivo

and whether that’s from overfishing

high rises . multi - family buildings


as diseases . like dermo . and


becoming poorer with

being reduced

which is being squandered

definition Paragraph 6 : Effects

deteriorating because

and development



out what the rivers bring quality . or has been ? Dorothy

almost destroyed due

priceless and vulnerable

like stormwater . Oysters grow by

. I really don’t know . Agriculture


just mentioned ? Robert I’m sure

I can’t tell you . But


due to chemical runoff from

from over development

has something to do with

industries .

problems on sea turtle nesting

Section and introduction Paragraph 7 :

Understanding . assessing . and resolving light

places and ways in which that code occurs throughout the

data. Importantly, however, we must remember that the

software can only give us back interpretable versions of

what we put in. The researcher defines the codes, identifies

the data to associate with them, and defines the queries

concerning the relations among them. The pictures in the

examples given here do not reveal the “truth” of the data.

They show the relations coded by people and entered into

a program.

The following is a list of just a few Internet sites that

might allow interested readers to begin their journey into

the vast world of qualitative research tools.

1. QualPage, a resource listing for qualitative researchers:


2. Qualitative Report, an online journal that also provides

an alphabetized listing of helpful qualitative research

Web sites on a variety of interesting topics: www.nova.


3. ATLAS.ti, a software site designed for qualitative text,

audio and video data: http://www.atlasti.com/

4. CAQDAS Network, a general listing of computerassisted qualitative analysis Web sites: http://caqdas.


5. MAXQDA, qualitative data analysis software: http://


11.10: Why It Works

11.10 outline the advantages of content analysis

Perhaps the most important advantage of content analysis

is that it can be virtually unobtrusive (Webb, Campbell,

Schwartz, & Sechrest, 2004). Content analysis, although

useful when analyzing depth interview data, may also be

used nonreactively: No one needs to be interviewed; no

one needs to fill out lengthy questionnaires; no one must

enter a laboratory. Rather, newspaper accounts, public

addresses, libraries, archives, television shows, movies,

and similar sources allow researchers to conduct analytic


Nonreactivity means that the information that we are

coding existed before we came along and was not influenced at all by our research process or objectives. When

we analyze a speech, it is a form of communication chosen

and presented entirely by the speaker and not shaped

by our questions. When we examine the lyrics to songs,

these songs were deliberately written and presented to

the public for their own communication value. Our work

is “clean.”

An additional advantage is that content analysis is

cost-effective. Generally, the materials necessary for conducting content analysis are easily and inexpensively

accessible. One college student working alone can effectively undertake a content analysis study of written public opinions, whereas undertaking a national survey, for

instance, might require enormous staff, time, and expense.

11.11: Why It Fails

11.11 recall causes why content analysis may fail

The most serious weakness of content analysis may be

in locating appropriate unobtrusive content relevant to

the particular research questions. In other words, content

analysis is limited to examining already-recorded messages. The unobtrusive nature of the work means that we

200 Chapter 11


rely on existing content rather than generating our own.

Although these messages may be oral, written, graphic,

or videotaped, they must be recorded in some manner

in order to be analyzed. We are therefore often limited

to the examination of records that others have decided

were worth preserving. Of course, when you undertake

content analysis as an analysis tool rather than as a complete research strategy, such a weakness is minimal. For

example, if researchers use content analysis to analyze

interview data or responses to open-ended questions

(on written questionnaires), this weakness is virtually


A variation on this problem is that long before we

begin our data sampling, the available pool of data has

been limited to just that which has been compiled or

created through the work of filters that we can’t see. As

an obvious example, I might want to look at the comments section of a news Web site to see how readers

have responded to news stories on a particular topic. But

would anyone seriously suggest that the pool of people

who leave comments online in any way represent the

population of readers? My guess is that no matter what

topic you chose, from news about abortions to news

about kittens, the overwhelming trend of online comments would indicate that readers are angry about that

thing. The analysis might be excellent, but the data itself

has already been invisibly filtered through the social

world of the Internet.

Another limitation (although some might call it a

weakness) of content analysis is that it is often ineffective for testing causal relationships between variables.

Researchers and their audiences must resist the temptation

to infer such relationships unless the data collection has

been particularly designed around this relationship, as

might be the case with interview data. This issue reiterates the point made previously about motivations: We can

use content analysis to say what is present, but not why.

Causality may be suspected or suggested by the patterns

of association among measured phenomena, but other

means must be used to test that idea.

Trying iT OuT

Suggestion 2

Without writing their names on the paper, have everyone in your

class write a response to the following question: If you could

change one thing in the world today, what would it be?

Ask each classmate to write his or her gender or age at the

bottom of the response, but remind them not to write their names.

Have each person make enough photocopies to distribute one

copy to every person in the class. Now everyone has a set of data

to work with.

Next, go through the responses and see if you can locate any

patterns of similarity or difference. Sort the responses into groups

according to the patterns or themes that emerge as you read

through the responses. Try to make the following assessments:

1. How many times have students identified the same (or very

similar) things they would change if they could?

2. What proportion of the class used identical words to describe

what they would change?

3. Are patterns any different if you first sort them according to


4. Are patterns any different if you first sort them into the following age groupings: young, older, oldest?


Chapter 12

Writing Research: Finding

Meaning in Data

Learning Objectives

After studying this chapter, you should be able to:

12.1 Evaluate the evils of plagiarism.

12.2 Relate the identification of the research

purpose to the identification of the

research question.

12.3 Illustrate the contents of the typical

sections of a research paper.

12.4 Identify common terms and language for

things related to publications.

12.5 Describe two major outlets for the

dissemination of social scientific research


Suppose you were to do extensive research on people

trying to solve the Rubik’s Cube. And suppose you discovered something from that. Would you want to tell the

world, “I just learned something about the Rubic’s Cube”?

Or, would you rather say, “I just learned something about

how people solve puzzles”?

Qualitative research can result in improved social

scientific understanding, in trivial descriptions of things

nobody needs to know, or even in meaningless gibberish.

Which of these outcomes you get depends on two things:

the quality of work you do and your ability to explain it.

This chapter is about the second part. It is designed to help

researchers to offer up their work for inspection by others

in an understandable and meaningful fashion—to tell the

world what you have found and why it matters. But writing about research involves far more than just posting your

data somewhere. The goal of this chapter is to enable you

to write up the research so that it can be disseminated in

an understandable form to appropriate audiences. Before

actually getting to the mechanics of writing up research

papers, I believe it is important to write a few lines on the

perils of poor writing.

12.6 Recognize the importance of making the

research writing interesting.

12.7 Examine the relevance of multiple drafts of

the research writing.

12.8 List the common mistakes made

by students while writing research


12.9 Summarize the points that need to be

highlighted while writing about


Even the best research can be rendered useless by poor

communication. It is hard enough for nonresearchers to

understand the implications of our work when it’s clearly

presented, as I have stressed already in earlier chapters.

With less than clear reporting, misunderstandings are

pretty much guaranteed.

For example, suppose your work showed that elder

retirees who participate in social activities with people

they like have greater health outcomes. (I don’t know if

that’s true, but it seems likely.) And suppose that you did

your research in conjunction with senior centers, distinguishing between those seniors who regularly participated

in activities and those who didn’t. If you merely report

the outcomes, that active members of senior centers were

doing better, people will think that health depends on

senior centers, missing the real point that health depends

on social life. Reporting the “what” of a study is trivial.

The real work is in demonstrating the “why.”

A further difficulty we face as research writers is that

people may read our work with more of a defensive eye

than a merely critical one. We can’t assume that our conclusions speak for themselves. We have to make a strong


202 Chapter 12


case. And we have to remember as we do so that most

people are not in the habit of analyzing data. Until we are

trained, people are actually pretty bad at drawing logical

conclusions from subtle patterns hidden within masses of


On the other hand, one thing that people are surprisingly good at is justifying our own beliefs. We might like

to imagine that we look at the evidence and then draw

conclusions. Yet, often it seems that we do the opposite:

attach ourselves to a conclusion and then search for evidence to justify it. Was a novel that you recently read dense

and hard to follow? That was probably because the author

ignored conventional structure and messed around with

chronology. Was a different book brilliant and captivating?

That’s probably because the author ignored conventional

structure and chronology. Either way doesn’t matter, as

long as I can use the observed fact to support my conclusion. That’s how justification works. In the case of research,

as I find with my students, people are happy to trust the

methodologies and analyses of work with which they

agree, but are highly critical and suspicious of anything

that draws a challenging conclusion. If they don’t like the

results, then there must have been something wrong with

the sampling.

As researchers, our first challenge is to get away from

that kind of thinking. That can be difficult. Our second

challenge is to present our evidence in such a clear and

compelling fashion that we can overcome other people’s

tendency to only see in it what they want to see. That is

much harder. And third, we need to be aware of and more

or less follow the rules and conventions of scientific writing. We’ll start this chapter with some rules. The first and

most important of which is to clearly distinguish between

other people’s work and our own original contributions

to the topic. Failure to do so constitutes plagiarism, and it

thoroughly invalidates whatever else we might be trying

to communicate.

12.1: Plagiarism: What It Is,

Why It’s Bad, and How to

Avoid It

12.1 Evaluate the evils of plagiarism

Ironically, depending upon the source, you are likely to

find a range of meanings and definitions for the term

plagiarism. Regardless of these variations, at their root

these definitions share the notion that plagiarism involves

passing off the ideas and words of others as your own

without clearly acknowledging the actual source of those

ideas and words. Importantly, in academe as in the world

of the social sciences, journalism, the arts, the natural sciences, and virtually everywhere else, plagiarism is considered very bad regardless of whether it is done intentionally or unintentionally.

The label of plagiarism can describe any of the following actions:

• Turning in someone else’s written work as your

own (regardless of whether you have their permission to do so)

• Purchasing a written work from a professional paper

mill, your sorority or fraternity, the smart kid in class, or

any other source, and passing it off as your own work

• Copying sentences, paragraphs, or whole pages from

a textbook, Web site, or other written source without

indicating the actual source of this material

• Copying sentences, paragraphs, or whole pages from

a textbook, Web site, or other written source without

including proper quotation marks, page references,

or indentation (in the case of longer excerpts)—even

when proper citation of the actual source is offered

• Paraphrasing sentences, paragraphs, or whole pages but

failing to provide proper citation of the original source

• False paraphrasing (changing one or two words) in

sentences, paragraphs, or whole pages and failing to

provide proper citation of the original source

12.1.1: Why Plagiarism Occurs

It is likely that much of the plagiarism that occurs in colleges

and universities, and perhaps even among some professional

researchers, is what we classify as innocent or just stupid plagiarism; still, some is intentional and undertaken for a variety

of reasons. Some of the more common intentional reasons

for plagiarism include the following: “I was running out of

time, and the source said exactly what I wanted to say.”; “The

source said it so much better than I possibly could have.”; “It

was a stupid assignment, and I have more important things

to do with my time.”; “Everybody else was doing it.”

From time to time we also hear about professional

researchers, writers, or journalists who are also found to

have plagiarized other works. Among the most common

explanations given by these authors is that they were

writing from their notes, not the original sources, and

could not clearly distinguish between the words they

had come up with on their own while writing these notes

and the phrases they had simply copied over more or less

unchanged. This sort of plagiarism is understandable, but

just as stupid. Surely, after a writer has struggled once or

twice with the inconvenience of having to return to the

original source just to find the one sentence they wanted to

quote, you would hope they would have developed more

careful note-taking practices.


Innocent or plain stupid plagiarism involves errors in

citation because the writers simply do not understand that

their actions constitute plagiarism. Either way, authorities

are typically no less sympathetic to stupid plagiaristic mistakes than they are to intentional ones. However, stupid

mistakes are easier to correct because once you learn the

errors of your ways, you can consciously avoid making

stupid mistakes of plagiarism.

12.1.2: How to Avoid Plagiarism

“So now that you know how it’s done, don’t do it!”1

Avoiding the first two items in the previous list seems

like a no-brainer. Obviously, if you go out and borrow

or buy someone else’s work, you have intentionally plagiarized these works, and there is no lenience for you.

These  are clear-cut examples of academic fraud. Some

people get away with it, but you should understand

that the action of intentional plagiarism is seldom taken

lightly, and in some schools, it can result in suspension

or expulsion. In the real world, getting caught in such an

act could result in the loss of a job or career, or at the very

least the loss of trust in your work, probably forever.

Let us therefore concern ourselves with the remaining

four items on the list, which do frequently occur among

students and other writers as stupid mistakes. The first

of these four items states: Copying sentences, paragraphs,

or whole pages from a . . . written source without indicating the

actual source of this material. In truth, this one walks a thin

line between a stupid mistake and an intentional one and

may from time to time fall into either of these camps.

However, in our combined 45 years of teaching in colleges

and universities, we have heard some very sincere students

claim they were unaware that lifting a few sentences or a

paragraph here and there and dropping them into their

own writing was plagiarism. Some of the blame for this

rests with certain elementary school teachers who insist

that their students look up the definition of words and

write out the full definition without citing the dictionary

as the source, or who encourage students to write topical

papers using an encyclopedia as a source. Students who

dutifully copy and paste the passages verbatim receive

an A for their efforts but, again, do not bother to cite their

source. Those teachers may have been trying to teach you

useful facts, but they did not help you learn to write.

Regardless of why many students believe this sort of

plagiarism is acceptable, it simply is not. It is plagiarism—

but with a simple fix. Never use someone else’s written

work without giving credit to that original author or

authors. Use it; but credit it. This brings us to the next item

on our list: Copying sentences, paragraphs, or whole pages from

a . . . source without including proper quotation marks, page references, or indentation—even when proper citation of the actual

source is offered.

Writing Research: Finding Meaning in Data 203

The usual rule of thumb is that when a quoted section

is five lines or less, you encapsulate it between quotation

marks (“quoted passage”). Following this quoted section,

you cite, in text, the name of the author, the date of the

publication, and the page reference where the original

work appears. If you are quoting more than five lines

of text, you should indent the passage on both sides—

but without quotation marks; it’s one or the other, not

both—either indent or use quotation marks. Following

the indented passage (typically on the next line and right

justified), the citation is enclosed in brackets ([citation

material]). Again, this citation should include the name of

the author or authors, the date of the publication, and the

page reference where the original passage appears. Since

the material you are referencing includes a specific set of

words exactly as they had appeared on some other page,

your citation has to include the page number.

The next item on our list is, Paraphrasing . . . but failing

to provide proper citation of the original source. Apparently,

many students believe that if they steal someone’s ideas,

but do not use every word in the same order as the

original author or authors set the material down, it is

not plagiarism; this is a very wrong assessment. This

one, however, is at least a bit more understandable as a

simple mistake. The fact of the matter is, if you take

another author’s idea(s), you need to reference that

author. In fact, in research citing someone else properly

is more about giving them credit for their ideas than for

their particular choice of words. This is often done with

what are hopefully familiar phrases, such as, “According

to Jo Jones (2006) . . . ” or “In a similar fashion, Marshal

and Cates (2006) found . . . ” The material following these

sorts of statements can be heavily paraphrased, almost

unidentifiable with the original, but if the main points

have actually been lifted from the original version, it

is proper to cite these original authors. It is also a solid

way to document your writing. However, if the ideas are

developed throughout portions of your source, rather

than in one particular paragraph, then there is no need

for a page reference in the citation. You are citing the

body of work, not a statement within it.

Here it is worth noting the relationship between credit

and credibility. If you wish to take credit for ideas that are

not your own, you obviously risk losing credibility if you

are found out. The reverse is also true. When you give

credit to others for the work that you are using, you gain

credibility. It shows that you are both honest and well read.

Researchers are supposed to be familiar with the work of

others. Building your work on a solid foundation of past

research is more respectable than trying to build your

whole project out of nothing. As well, it saves you from

having to justify some of your claims, since others have

already done that. This is particularly important when

what you are saying, using the other author or author(s)’

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