EDUR 7130
Educational Research On-Line
Introduction to Qualitative Research
1. General Comparison of Quantitative and Qualitative Studies
Qualitative research represents a collection of investigative techniques that
enable one to gain a broad understanding of group culture and/or individual
behavior within natural settings and environments. Stated differently,
qualitative research can be used to describe, in some detail, how individuals or
members of a defined group function and behave within their natural setting.
Qualitative researchers are often interested in creating a verbal portrait of
the lives or experiences of individuals or groups.
Qualitative research is an emergent field that has grown in popularity over the
past few decades. The methods of qualitative research have also expanded during
this time. Unlike quantitative research and statistical analysis, however, the
methods of conducting research and analyzing data in qualitative research are
not clearly distinct or universally defined. There is much overlap in methods of
collecting data (e.g., sometimes it can be difficult to clearly identify and
label a study as ethnography, case study, phenomenological study, or ground
theory) and in data analysis. One problem is that qualitative researchers do not
always agree on the definition or defining characteristics of data collection or
analysis methods. Thus, the specifics of qualitative research appear to vary
depending upon which author one chooses to read.
To help illustrate how qualitative research differs from quantitative research,
consider the following components of research identified below.
Quantitative Research
Recall the Matrix of Quantitative Methods. Typically correlational, ex post
facto, and experimental research may be classified as quantitative research
because they use or require:
(a) Ideas/Questions/Hypotheses/Theories
Quantitative research often employs a priori formulation of hypotheses/theories;
the research is developed specifically to test formally those
hypotheses/theories. Given the emphasis on testing and evaluating
theories/hypotheses, knowledge of prior research is important because this
knowledge helps build theoretical understanding. Presentation of literature
reviews is a key component of quantitative reports/proposals because these
reviews typically help justify the study purpose.
(b) Participants
When participants are sampled, often large, representative samples are sought so
quantitative study results can be generalized or inferred back to some target
population from which participants were sampled. Randomized selection procedures
are encourage since such selection is assumed in statistical hypothesis testing,
and since randomized selection is often better for obtaining representative
samples.
(c) Design Implementation
Studies in the quantitative domain may be quite controlled, especially
experimental studies. Often researchers develop treatments that are administered
to study participants in an attempt to learn how participants react to those
treatments. In studies where manipulation of treatments is not employed,
quantitative studies nevertheless are usually designed to learn how specific
variables relate to other variables. The focus of most quantitative studies is
to examine variable relationships.
(d) Data Collection
The quantitative study of variable relationships requires precise measurement of
those variables. Extensive knowledge now exists on how to measure variables and
how to provide evidence for validity and reliability of scores used to measure
variables. Data are usually collected to form scores of some type, and a common
means of collecting such data is via instruments and scales. Sometimes
preexisting data may be used (e.g., school records of attendance and dropout
status), and sometimes researcher observation is employed to collect data, but
in almost every case the data will be used to form variables for analysis.
(e) Data Analysis
For most quantitative studies data analysis takes the form of statistical
analysis. This is true whether presenting simple descriptive information (e.g,
graphical displays, central tendency, variability), or presenting results of
complex variable relationship analyses (e.g., factor analysis, regression
equations).
(f) Conclusions/Results
Results from quantitative studies usually include focus on whether hypotheses
posed at the outset of the study were supported and how these results fit within
theory tested. Often it is important to explain how results obtained are
consistent with or discrepant from prior research in the area examined, and this
is done to help build generalized knowledge.
The essence of much quantitative research is formulation and testing of
theories/hypotheses. This represents a deductive approach to research: formulate
research questions or hypotheses derived from theory, empirically test those
research questions or hypotheses, and then assess the degree to which research
questions or hypotheses were supported empirically. Not all quantitative
research is deductive, but most studies in this domain do follow this pattern.
Qualitative Research
Much of qualitative research takes a different approach to discovery; often
researchers in the qualitative domain follow an inductive approach. With
inductive research one may first collect data to help address a general research
question that may or may not have been formed from a theory. Data are collected
to address this general research question, and theory or explanation is formed
from the data derived. So the inductive process is reverse of the deductive
approach. With deductive data are used to test theory or ideas, but with
inductive data are used to develop or derive theory or ideas.
Not all qualitative research, however, is used to develop theories. Often
qualitative research functions simply to describe events or settings for
individuals and groups, and it can be used to help illuminate important
phenomena for individuals or groups.
How does qualitative research differ from the general quantitative flow
presented above? Below are some comparisons.
(a) Ideas/Questions/Hypotheses/Theories
With quantitative studies hypotheses and theories often drive study designs.
However, qualitative studies are unlikely to be designed to test hypotheses or
theories. Instead, qualitative studies are developed to help understand people,
events, or processes. Qualitative researchers may begin with a simple research
question (a foreshadowed problem) and often end with broad understandings that
may be used to develop speculations (or a theory) based upon (or grounded in)
the data collected (such inductive work is sometimes referred to as grounded
theory). Given that qualitative studies can be used to generate theory or ideas,
and given that qualitative studies are seldom developed to test hypotheses or
theories, it is not uncommon for qualitative reports to have little theoretical
or literature based background presentation, and this is in sharp contrast to
expectations for quantitative research where a sound, thorough literature review
is usually expected. Often qualitative studies provide a brief introduction to
the purpose of the study, and then moves to description of participants and the
context for the study. A literature review plays a small role in such a study.
(b) Participants
Rather than large samples, qualitative researchers work with very small samples,
say a few individuals, groups, or organizations (see case studies) that are
often chosen through judgment or purposive sampling procedures; as a result,
large representative samples are uncommon and would be impractical to work with
due to data collection techniques used; note that generalization or inference to
a target population is not an important feature of qualitative studies; instead,
qualitative researchers wish to provide detailed description of those involved
in the study, frequently using participants’ (or informers’) own words via
quotations.
(c) Design Implementation
Rather than controlled and manipulated settings found in quantitative designs
(especially experimental designs), qualitative studies are almost universally
executed in a natural environment with little research manipulation or control.
The idea is that researchers will learn from participants and the environment
without interfering or altering the setting. Also, unlike quantitative studies
that focus almost exclusively on examining relations among measured variables,
qualitative studies focus not on measuring variables, but on understanding
setting, context, participants’ thoughts and feelings, and learning this through
a holistic approach via interviews, observations, and examination of site
artifacts and documents.
(d) Data Collection
As noted above, qualitative researchers collect data via interviews (i.e.,
usually through multi-session, unstructured interviews), observations in the
field (i.e., detailed field notes), review of documents/artifacts, and
participation with those involved in the study. It is common practice for
qualitative researchers to claim they are the instrument for data collection.
There is rarely any attempt to collect information from participants via
questionnaires, instruments, or scales; however, it is possible that a
qualitative researcher would incorporate such information if it is already
available (e.g., school psychologist’s records for selected students) and would
provide additional information for learning about participants or how such
information may shape behavior, attitudes, or beliefs.
Since instruments are seldom used, data validation does not result from the
traditional methods of validity and reliability assessment techniques discussed
with quantitative research; rather, qualitative researchers are more interested
in the credibility of their data and interpretation of those data; one method
for assessing this credibility may be from triangulation of data (i.e.,
collecting data from multiple sources, time points, methods, or observers to
cross-check findings and interpretations).
(e) Data Analysis
In qualitative research data are often words/stories derived from interviews,
but may also be derived from various artifacts and documents, and/or
observations in the field; data analysis can be complex and require significant
time and insight to produce useful and credible information; data analysis often
follows a pattern of first identifying general categories for data, then
organizing those categories into concepts, then finding patterns and linkages
among concepts. This can be a laborious process that normally begins once data
collection commences.
(f) Conclusions/Results
Conclusions drawn in qualitative research encompass presentation of theory or
ideas of behavior, or may present useful, "thick" descriptions of events or
processes, participants (informants) and their lives. The focus with qualitative
research is not how a particular hypothesis was or wasn’t supported by the
collected data, instead, focus is on how collected data describe events or
suggest patterns or theory.
2. Qualitative Sampling Strategies.
As noted above qualitative researchers don’t attempt to take results from a
sample and generalize to a population; inference to populations is not a concern
in qualitative studies. Instead, qualitative researchers focus on describing the
lives, significant events, or experiences for individuals or groups.
Given this design focus, selection of participants or informers is critical and
usually is not left to random chance. Rather, researchers employ purposive (or
purposeful or criterion-based) sampling strategies that will maximize selection
of participants who will most likely provide insightful information (i.e.,
information rich) regarding the phenomena under investigation.
Some commonly employed sampling strategies, all of convenience-purposive form,
include the following.
(a) Maximum Variation Sampling
Here the sampling strategy is to select those individuals (or groups, documents,
artifacts) who will provide a wide range of information, wide range of variation
of in whatever dimensions are under investigation. You may select certain
criteria for study, such as teaching ability, level of interest in school,
desire to learn to read, or some other factor. Once these criteria are
identified, one selects cases based upon whether those cases are near the ends
of the continuum, and perhaps in the middle too, for the criteria. To goal is to
ensure maximum differences among the criteria identified for purposive
selection.
Example: To learn what makes for good instruction, I will select both master
teachers and weak teachers, and perhaps a few identified as average. I will observe
each teacher in an attempt to identify
patterns of instructional differences between those groups examined.
(b) Extreme or Deviant Cases
"This person is very unusually in her ability find to gifts in students…"
"I’ve never seem anyone work with weak learners like her…"
"That school is the worst in the state…"
"He learns languages so easily I cannot believe it…"
"That girl can perform math calculations faster than other students can use a
calculator…"
"If you want to study a successful football program, go to Southside High
School…"
Each of the above quotations suggests extreme or deviant cases that may be worth
investigating through case or narrative studies. Sampling cases based upon their
extremeness --- how they differ, often dramatically from others on some set of
criteria --- represents this type of sample selection. Unlike maximum variation,
extreme case sampling typically involves selecting a participant or group of
participants who lie at one end of the continuum for the criteria used to select
individuals. For example, I will interview only those students with perfect GPA
as seniors; I selected this student because he had more school absences than
anyone else; or this teacher's class showed the most dramatic change in
standardize test scores over the past year.
(c) Typical-case Sampling
Unlike extreme case sampling, this approach is used to select cases that are
common and typify those dimensions or criteria under study.
Example: I want to know what the typical student thinks of Southside High
School, so I will ask teachers to recommend some of their average students for
interviews. I don’t want the highly gifted or the severely handicapped, instead,
I want the average student.
(d) Homogeneous Sampling
With this approach one is interested in selecting groups of cases or
participants that share very common beliefs, behaviors, or characteristics ---
that is, participants have similar stances on whatever criteria are used to
select cases. This approach helps reduce variation in responses and allows one
to more easily identify common themes and patterns among themes. Unlike maximum
variation sampling, the goal here is to select participants who are very similar
on select criteria (age, race, grades, work ethic, etc.), so homogenous sampling
will minimize variability in participants on those criteria employed for sample
selection.
Example: To help streamline data collection, I will employ focus groups of
people with similar attitudes and beliefs. For my first group, I will select
those students who tend to take seriously school and who also desire to attend
college. For my second group I will select students who work after school, have
little interest in college, and show marginal or low interest in high school.
(e) Snowball (or Chain or Network) Sampling
This type of sampling uses informants/participants to suggest other individuals
for inclusion in the study.
Example: Asked of a study participant ---
"Who knows a lot about working with Internet applications in the classroom at
this school?"
or
"Can you help me find other people who might know a lot about using Accelerated
Reader with students with disabilities? I want to interview anyone who has good
experience with this, someone who has worked with a number of students. Can you
offer any suggestions?"
(f) Theoretical Sampling or Opportunistic Sampling
This approach to sampling involves collecting data from those cases first
selected, and then as data analysis begins the researcher may learn of other
important aspects that should be examined, so other cases are selected as
needed. The process is continued until a saturation point is reached and no
further useful data are collected.
Example: In a study of Accelerated Reader (AR) I interviewed two teachers who
regularly use this in their second grade classrooms. I learned from these
teachers that AR may not be as useful in fourth grade classrooms, so I sought to
interview two teachers from fourth grade as well.
(g) Critical-case Sampling
The logic with this sampling strategy is to select those who will serve as a
"test" case for study. The common notion that "if they can do it then anybody
can do it" applies in this sampling strategy. With this sampling strategy the
qualitative researcher is hoping those selected will help generalize to other
possible participants.
Example: Southside High School adopts a new attendance policy. To help
communicate this policy to parents, the school develops a glossy pamphlet for
parents that explains the policy. As a first test case to determine whether the
pamphlet gets important points across to parents, several well-educated parents
are interviewed to determine what they understand of the policy. The logic for
selecting well-educated parents follows: if this group of parents cannot
understand material in the pamphlet, then it is unlikely less-well educated
parents will understand the pamphlet presentation. If this is the case, then
revision will be needed.
The above list of sampling procedures in qualitative research is not exhaustive,
but does provide a general idea about the types of sampling employed by
qualitative researchers. Some other sampling strategies you may encounter
include negative-case (confirming or disconfirm sampling), intensity, criterion,
politically important, and mixed or combination purposeful.
3. Qualitative Data Collection Methods/Role of Researcher
In quantitative research data collection typically follows a formal,
well-designed plan. For example, with experimental studies there will often be a
pretest, some treatment implementation, and a posttest. There will be protocols
to follow for each of these phases, and one may expect that failure to follow
these protocols can jeopardize study execution and data interpretation. In
short, study validity is determined by protocols and study execution.
In qualitative research data collection plans may be revised mid-stream during
the data collection phase. For example, qualitative researchers may learn of
important aspects of their cases they had not considered prior to implementation
of their study, so they must be flexible and creative enough to make changes
that will allow them to collect from these new data sources. Fortunately for the
qualitative researcher, they themselves are the data collection tool or
instrument, so flexibility is an option.
In addition to flexibility, the qualitative researcher engaged in prolonged
studies, such as ethnographies, tries to assimilate into the environment of
their study participants. Thus, studying in a natural setting is an important
characteristic of qualitative studies because it allows access to data and
phenomena that may not otherwise be available. This contrasts with an
experimental researcher, for example, who attempts both to control and
manipulate the environment in which study participants are located.
How do qualitative researchers collect their data --- normally through
observation/participation, interviews, and review of documents/artifacts.
Observation (Fieldwork)
In the field a qualitative researcher engaged in observation can take several
roles, which can be classified into three or four general categories:
(a) Participant observer is one who attempts to assimilate into the environment
or setting. This type of research involves having the observer actually become
part of --- a participant or member --- the group being studied. For example, a
qualitative researcher may become a teacher in high school to learn better the
process of teacher initiation and the first year experience. Participant
observers become insiders and participate fully in activities at the study site.
This allows one to observe and experience rituals and activities that regular
members experience. One limitation with this role is that it may be difficult to
take notes while participating so some of the experience may be lost due to lack
of recorded data. Another possible limitation is that participation may
introduce some bias, or subjective influence, to interpretation of events
experienced. The more immersed one becomes, the less likely one can be
objective, and this should be acknowledged by researchers when they become
complete participants.
Note also that participant observation may be either overt, covert, or some
combination of the two. The more covert the observation, the more authentic the
actions observed should be, but the tradeoff may be less objectivity on the part
of the researcher. For ethical reasons it may be difficult to justify covert
participation.
(b) Non-participant observer is one who maintains separation from study
participants, does not engage in study site activities, and therefore remains an
outsider. In some situations members of study sites may be more comfortable with
researchers adopting this role rather than attempting to become a full
participant. A limitation with this approach is that the researcher must rely on
observation and interviews rather than experience to learn about study site
activities.
(b) Mixed participant-observer is another role that can be adopted by the
qualitative researcher. Some qualitative researchers identify refined labels for
this type of observation including observer-as-participant and
participant-as-observer. The subtle distinction of these can be found on-line or
in various texts, but the main point with a mixed participant-observer role is
that the researcher is neither fully participant nor fully non-participant and
therefore fluctuates between these roles in given situations. For example, for
intense or dangerous activities researchers may choose to remain complete
observers; similarly, study site participants may prevent the researcher from
becoming a participant to some activities for fidelity reasons to keep the
activity pure, such as group initiations or pledges of allegiance. For other
activities the researcher may be allowed to participate fully, such as engaging
in meals or sharing stories.
Interviews
In addition to observations, qualitative researchers use open-ended or
unstructured interviews (sometimes call ethnographic interviews) to obtain data.
Such interviews frequently result in rich information about how people view
their world and how they come to understand and interpret important events in
their life (e.g., being arrested, gaining acceptance into a university). Note
that the terms open-ended and unstructured refer to interviews in which there
are not set questions or lines of inquiry. Such interviews are free to explore
whichever avenues become available during the interview. Such flexibility is a
characteristic that often distinguishes between qualitative and quantitative
research. Note that interviews can be both formal (planned ahead with
participant) or informal (spontaneous and convenient).
Two common formats for interviews are one-on-one and focus group. One-on-one
interviews include the researcher and a study participant. This can be a very
time consuming activity, but often produces the most detailed information
especially if a number of one-on-one interviews are conducted. Focus groups are
interviews conducted among several (e.g, 4 to 8) participants simultaneously.
Field notes
Once a qualitative researcher begins observation (whether as a participant or
non-participant) the data observed must be recorded. The use of field notes or
journals is one of the more common tools used by qualitative researchers. Field
notes should include detailed, written descriptions of what was observed by the
researcher. Such a description may include words, pictures, symbols, or whatever
is necessary to adequately relate the actions and settings in which the
observation occurred. For example, one may record a conversation between two
participants. To better record and understand this conversion, it would be
necessary to indicate where and when it occurred, physical appearance of the
participants, facial expression, mannerisms, etc.
In addition to the above, field notes should also include reflective
information. Such information includes researcher speculations, feelings,
impressions, etc. One may also include ideas about emerging themes or patterns
in the data. Usually such information is noted as observer comments.
Documents, Images (Visual Data), and Artifacts
Often qualitative researchers collect artifacts --- data in the form of personal
documents (e.g., diaries, letters), official documents (e.g., minutes of
meetings, student files and records), objects (e.g., logos, tools), and
video/photographs (e.g., images of students in a classroom during instruction,
teacher facial reactions when told of a new policy) --- to provide information
that may be difficult to obtain in the field or to provide further evidence (for
triangulation) of patterns that emerged from observations.
4. Qualitative Data Analysis
Analysis Process: Quantitative vs. Qualitative
In quantitative research data usually consists of numbers that represent
variables. Among quantitative researchers there are nearly universally agreed
upon approaches for the analysis of numbers, or variables, given the type of
variables examined, the research process that generated those variables, and the
complexity/level of variables and sampling strategies employed. In quantitative
research there are standardized procedures for analysis of data.
Qualitative data usually consists of words taken from interviews, used to
describe observations, descriptions of settings or study sites, or descriptions
of ideas, thoughts, or feelings of the researcher. How does one analyze words?
In qualitative research there does not appear to be standardized, agreed upon
procedures for data analysis with the exception of ground theory, but even here
there are various departures to a standard track. Despite the lack of a
systematic, standardized procedure, there are, however, some general steps many
use to analyze data. These will be outlined below.
Generic Steps for Qualitative Data Analysis
(a) Data Preparation
Since most qualitative data are in the form of words, it is important that
interviews, field notes, documents, etc. be transcribed and recorded in such a
way that can be easily accessed and read.
First note that data analysis in qualitative research is often cyclical and may,
perhaps should, begin once data collection commences. The cycle of collecting
data and analyzing data during the data collection phase is known as interim
analysis (analyzing data during the interim while data collection continues).
Beginning data analysis early can help identify important themes or areas that
should be explored.
At this initial stage researchers should read all their data carefully, and then
re-read, then repeat again (and again). Why? The more familiar researchers are
with their data, the more easily they can begin spot or identify important
concepts in those data and see connections between concepts. With each reading
researchers should record their impressions of the data, record their thoughts
and interpretation of the data. These recordings will help build one’s memory
and provide insight when sorting/collecting data into broad categories and
concepts.
(b) Develop Initial Codes and Code Data
At this stage the researcher will begin coding data; this means labeling
relevant or important data points with unique labels to help separate data into
unique and meaningful components. The researcher, when coding, is attempting to
identify key ideas, behaviors, interactions, incidents, and terminology/phrases
available in the data.
Codes used for labeling data may be derived in several ways:
A priori/Preset Codes --- The researcher develops a classification scheme of
codes prior to collecting data. This approach may not allow important new
information to be identified; probably few qualitative researchers employ this
approach.
Post hoc/Emergent Codes --- Codes for classifying data are developed while
reading and coding the data. This approach allows the data to speak and
potentially enables the richness of the data to be revealed.
Mixed Present and Emergent Codes --- This approach represents a combination of
the two in which researchers develop an initial classification scheme with
codes, but adds to these codes as new information is learned.
Coding data and developing codes is an iterative process and requires much time
and effort. When data from multiple interviews or long interviews are used, one
can expect the this coding process to last many hours or even days.
(c) Organize Data into Categories
At this stage most data will be identify via codes (although the process is
iterative so new codes may be identified still or data may be labeled or
relabeled with existing codes), so now the process combining like codes into
categories begins. Here one attempts to identify redundancies in codes and
create subsets of codes to form broader categories of data. This reduction
process helps to bring meaning to data; it allows one to more succinctly grasp
key ideas found in the data.
(d) Further Refinement: Categories to Themes/Concepts
In many cases one will be able to organize categories into still boarder
concepts. Sometimes this may not be possible, or categories may be concepts (the
two overlap). The notion, however, is that if there are many categories of data,
it may be possible to further combine these into more general concepts that
better reveal important information or meaning in the data. At this point some
categories may be discarded as unimportant or because these categories provide
little relevant, helpful information for telling the story of this research.
(e) Find Relations among Concepts and Categories
Often one may be able to identify how various concepts interrelate for study
participants and researchers. This can lead to significant meaning and reveal
important findings.
Illustrated Example of Data Analysis
Below is an example showing how data from an interview may be coded to identify
important concepts.
(a) Data Preparation
The interview between a researcher and teacher is transcribed and presented
below.
Interviewer:
"Please tell me what it was like to work under your previous principal, and how
is it different with your current principal."
Teacher:
"Wow, the difference is like night and day. Mr. Sykes was so controlling. He had
to approve . . . like everything we did. If I wanted to try something new, maybe
a new computer program with my students, I had to get his permission. Uh, I
remember once . . . I wanted try a new workbook that I downloaded from the
internet. One day he was observing me teach, and he asked about it in kind of a
disapproving way. I don’t know, but it just seems he was so oppressive and
didn’t want us to try new things. I kind of lost interest in teaching when he
was here."
"Now with Mr. Rosen things are so different. When he first arrived he said he
wanted us to explore new ways of teaching, you know, to try different things in
the classroom. I wasn’t sure I believed him. So I asked him about using some
stuff I found on the web and he said ‘Sure, go for it and let me know if it
works.’ So I did and now I am constantly trying new things to help my students.
It is much more exciting now to be in the classroom because I can teach the way
I want."
(b) Develop Initial Codes and Code Data
Using an emergent design, note following codes within brackets [ ] and
highlighted in yellow were added to the teacher’s transcribed response.
"Wow, the difference is like night and day. Mr. Sykes was so
controlling. [authority control] He
had to approve . . . like everything we did.[authority
approval] If I wanted to try something new, maybe a new computer
program with my students, I had to get his permission.[authority
permission] Uh, I remember once . . . I wanted try a new
workbook that I downloaded from the internet. One day he was observing me teach,
and he asked about it in kind of a disapproving way.[authority
questioning] I don’t know, but it just seems he was so
oppressive and didn’t want us to try new things.[authority
oppressive] I kind of lost interest in teaching when he was
here. [teacher interest lost]"
"Now with Mr. Rosen things are so different. When he first arrived he said he
wanted us to explore new ways of teaching,
[authority explore] you know, to try different things in the
classroom.[classroom experiment] I
wasn’t sure I believed him.[teacher disbelief]
So I asked him about using some stuff I found on the web and he said ‘Sure, go
for it and let me know if it works.’[authority
approval/flexibility] So I did and now I am constantly trying
new things to help my students.[teacher explore]
It is much more exciting now to be in the classroom because I can teach the way
I want.[teacher excited/freedom]"
(c) Organize Data into Categories
Below I attempt to organize the codes identified above into categories. Note
there is some overlap and also one code is not used, [teacher disbelief],
because it does not seem relevant to the categories that are emerging.
Control
-- authority control
-- authority approval
-- authority permission
-- authority questioning
-- authority oppressive
-- authority approval/flexibility
Autonomy
-- teacher explore
-- authority approval/flexibility
-- authority control
Motivation
-- teacher interest lost
-- teacher excited/freedom
(d) Further Refinement: Categories to Themes/Concepts
As I think about this teacher’s responses and descriptions, and review those in
light of the codes and categories presented above, it seems there are two
general concepts presented in these data:
Teacher Autonomy Support --- In what ways does this teacher believe she is
supported to be autonomous in her classroom? In what ways does she believe her
level of classroom autonomy is being suppressed or controlled?
Teacher Motivation --- While this is a category identified in the previous step,
I think it also represents an important concept for this teacher. Does this
teacher demonstrate motivation or de-motivation to teach in her classroom?
(e) Find Relations among Concepts and Categories
Given this teacher’s responses it appears that the level of autonomy support
offered by the principals directly influenced her motivation to teach. As
evidence, consider her statements:
"Mr. Sykes was so controlling. He had to approve . . . like
everything we did."
"I kind of lost interest in teaching when he was here."
"Now with Mr. Rosen things are so different. When he first
arrived he said he wanted us to explore new ways of teaching, you know, to try
different things in the classroom."
"It is much more exciting now to be in the classroom because I can teach the way
I want."
Additional Reading
To learn more about qualitative data analysis, see Taylor-Power and Renner’s
(2003) brief summary entitled "Analyzing Qualitative Data:"
http://www.bwgriffin.com/gsu/courses/edur7130/qualitative/10_Qual_Data_Analysis_2.pdf
Donald Ratcliff (2002) offers very brief discussion --- essentially highlighted
points --- to 15 different types of methods for qualitative data analysis here:
http://www.bwgriffin.com/gsu/courses/edur7130/qualitative/10_Qual_Data_Analysis_3.pdf
5. Study Design Comparison Illustrated
Drawing from the example sited above, suppose we wished to examine teacher
behaviors, or reactions, to different levels of support from principals. How
would quantitative and qualitative studies differ? Below is a brief comparison
to highlight some key differences.
(a) Study Purpose and Research Questions
Quantitative
Focus would be on variables and identifying the nature of the association.
Perhaps a hypothesis would be formulated and tested: There is a positive
relation between level of teacher autonomy support and teacher motivation.
Qualitative
Focus would be on teachers’ experiences working with different principals with
different leadership and support styles. A very general question may direct this
study: What are teachers’ experiences working with principals with different
styles of leadership?
(b) Sampling
Quantitative
Perhaps a cluster sampling procedure would be used to randomly select 10 or so
schools, then all teachers in those schools would be asked to participate in the
study. Alternatively, a convenience sample of schools with recent changes in
principals may be selected for inclusion in this study. The goal would be to
select a large sample to provide adequate power for statistical testing and
generalization to the target population of teachers. Sample size target may be
150 to 300 teachers, or more.
Qualitative
A number of purposive sampling options could be employed here. One example would
be typical-case sampling to select teachers who seem to be representative of
other teachers within a school. Perhaps 4 to 10 teachers could be selected for
interviews.
(c) Data Collection
Quantitative
Since variables included in the study were specified at the outset, the
researcher must include measures---scales or instruments---that will provide
valid and reliable scores for teacher autonomy support and teacher motivation.
It is important to select scales that are brief and easy to administer. Perhaps
administration could be executed during faculty meetings, through mail, or
perhaps electronically. Steps must be taken to increase response rates since
mailed and email questionnaires often have low response rates. These steps may
include multiple mailings or e-mailings, reminder cards or e-mails, or chance
for a randomly drawn gift such as $50 gift card to motivate participants to
submit questionnaires.
Qualitative
Once participants are identified and agree, researcher must organize times and
meeting locations for one-on-one interviews. Focus group could also be used, but
one-on-one interviews may provide richer data, and since they are conducted
singularly, time between interviews (often days) can be used to review collected
data and learn whether other avenues of questions or data sources should be
sought on subsequent interviews.
(d) Data Analysis
Quantitative
Data will have to be entered into software for analysis, or if collected
electronically data will be software ready. After data cleaning occurs,
statistical analysis can be performed to test hypothesis about relation between
teacher autonomy and motivation. Pearson’s correlation coefficient could be used
if only two variables are included, or if other control variables were measured
too, such as years of experience, teaching efficacy, etc., then multiple
regression or some form of ANCOVA may be used to determine how autonomy predicts
motivation while statistically controlling for other variables.
Results of the analysis will focus on whether the data support or fail to
support the hypothesis, and how these results align or differ from theory and
prior research. General purpose is to expand literature by supporting or
refining theory of motivation.
Qualitative
As illustrated above, interviews must first be transcribed, including researcher
notes and impressions, and then data analysis may begin (although data analysis
should begin immediately with the first interview). The data analysis example
posed above suffices as a generic approach to qualitative data analysis for this
example, and the results show that for the teacher interviewed, there appears to
be a connection between principal autonomy support of that teacher and her level
of motivation to teach.
6. Contributions of Qualitative Research
For those trained in quantitative research it may be difficult to conceptualize
how qualitative research can contribute to the field since qualitative research
is not meant to generalize beyond the study site employed.
To help demonstrate the utility of qualitative research, several quotations are
offered below that describe ways that qualitative research results have
contributed to the field of special education.
The source for these quotations is Brantlinger, E., Jimenez, R., Klingner, J.,
Pugach, M., and Richardson, V. (2005), Qualitative Studies in Special Education.
Exceptional Children, 71, 195-207.
http://www.bwgriffin.com/gsu/courses/edur7130/qualitative/11_Qual_Exceptional_Child_Summary.pdf
This article is an easy read, not too technical, and is helpful to understanding
basics of qualitative research.
Brantlinger et al. describe how qualitative research become a liberating force
for "retarded" and disabled individuals who were housed in state institutions in
the 1960s:
"Another seminal qualitative study was conducted by anthropologist Robert Edgerton (1967). In order to understand insiders’ feelings about segregation and sterilization, Edgerton interviewed 48 adults classified as "retarded" who had spent much of their lives in institutions. The injustice and pain revealed in his Cloak of Competence: Stigma in the Lives of the Mentally Retarded inspired advocates to exert pressure on legislators and court officials to overturn the involuntary sterilization laws enacted in many states earlier in the century. The visual rhetoric of pictures taken at institutions in Christmas in Purgatory: A Photographic Essay in Mental Retardation (Blatt & Kaplan, 1966) provided poignant evidence of inhumane conditions experienced by people with disabilities who lived in large state hospitals. Collecting and interpreting pictorial data is considered an observational technique in qualitative work (Harper, 2000). These publications aroused widespread indignation and, thus, provided the impetus to arrange community alternatives for people with disabilities that was part of the deinstitutionalization movement. In England, Mattinson’s (1971) interviews with, and observations of, people released from institutions revealed that couples who lived together and shared their strengths were able to survive independently. These findings showed that laws prohibiting marriage for people with cognitive disabilities were not logical, cost effective, or ethical." (Pages 198-199)
For those interested in seeing Christmas in Purgatory: A Photographic Essay in Mental Retardation, follow this link (note, book is 3 MB download):
http://www.bwgriffin.com/gsu/courses/edur7130/qualitative/12_Qual_Christmas_in_Purgatory.pdf
(source of file: http://www.mnddc.org/parallels2/pdf/Xmas-Purgatory.pdf ).
Qualitative research was also helpful in bringing about alternative views of intelligence and labeling in schools:
"The idea that power imbalances that exist between
professionals and poor families result in minority and low-income children being
classified as disabled and/or placed in separated schools or classrooms at a
greater rate than White, middle class children was brought to attention by
Mercer (1973) in Labeling the Mentally Retarded. Mercer found that
African American children, who performed competently in their homes and
neighborhoods, still had IQ scores low enough to be labeled and treated as
mentally retarded. Her ideas about the "6-hour a day retarded child" (i.e.,
identified as disabled only through school tasks and psychological and academic
achievement tests) challenged the general faith in the validity and fairness of
IQ tests. Mercer’s work provided the rationale for requiring an adaptive
behavior measure for classification as mentally retarded. This was among the
studies that caused advocates to think about damaging aspects of the medical
model, which posits disability as a permanent, innate flaw in certain identified
children rather than a social construction that depends on context and the
nature of school and societal practices.
An ethnography, The Forgotten Ones: A Sociological Study of Anglo
and Chicano Retardates (Henshel, 1972), demonstrated that school
personnel’s assumptions about ethnicity influenced their referral, testing, and
placement procedures. Rosenthal and Jacobson’s (1968), Pygmalion in The
Classroom: Teacher Expectations and Pupils’ Intellectual Development
combined qualitative (interviews, observations, document analysis) and
quantitative methods (random sample, experimental design) to discern
that expectancies of teachers and students influenced Latino children’s school
achievement and educational outcomes. These qualitative studies focused on the
phenomenon of overrepresentation, which continues to be addressed by scholars
concerned about equity and a "do no harm" philosophy related to professional
practice (Connor & Boskin, 2001; Harry, Klingner, Sturges, & Moore, 2002)."
(Page 199)
Brantlinger et al. explain that studies like those cited above have been instrumental in providing "voice" to those who lack power or are marginalized in society, and as a result, corrective action has been undertaken to help those who are often unable to help themselves.