Qualitative Research Methods

Department of Informatics Engineering
UNIVERSITY OF COIMBRA

A CONCISE INTRODUCTION TO
QUALITATIVE RESEARCH METHODS
IN INFORMATION SCIENCES & TECHNOLOGIES

© A. Dias de Figueiredo, 2010 PhD Program in Information Sciences & Technologies - Research Methods

1. QUANTITATIVE vs QUALITATIVE METHODS
2. A TYPICAL QUALITATIVE RESEARCH APPROACH
3. QUALITATIVE RESEARCH METHODS

4. DATA COLLECTION TECHNIQUES
5. DATA ANALYSIS TECHNIQUES: CODING
6. TRIANGULATION AND MIXED METHODS RESEARCH
7. RELIABILITY AND VALIDITY

University of Coimbra, Ph.D. in Information Sciences & Technologies Research Methods 2009/2010
© A. Dias de Figueiredo, 2010 Slide 2

1. QUANTITATIVE VS QUALITATIVE METHODS

Research in Information Sciences and Technologies is traditionally
supported by two radically distinct categories of methods:

Quantitative Methods

Qualitative Methods

Although they are sometimes said to be incompatible
(namely by members of the quantitative camp),
they should be seen as complementary to each other.



The articulation between the two visions – quantitative and
qualitative – is actually leading to a ‘third major research paradigm’:

Mixed Methods


Quantitative methods are traditionally used in the natural sciences to study
natural phenomena with mathematical rigor, namely using statistical analysis.

A limited amount of variables is always assumed, and these
variables are seen as independent from external factors, measurable,
and holding mathematical relationships between each other.

Quantitative research generally emphasizes planning,
hypotheses, large random samples, and objective measures.

It assumes the existence of a distinction between
researcher and subjects, and aims at ‘generalizing’, i. e.
at producing laws applicable to much broader realities.


Qualitative methods are being used increasingly in the social and human
sciences for the study of highly complex and contingent phenomena, where
the numbers of variables is too high to be handled by quantitative methods.

In the past, the social and human sciences, for fear of
looking less respectable, tended to resort mainly to the
quantitative methods of the natural sciences.

Today, they are putting increasing emphasis on qualitative
research and, as a consequence, obtaining much richer results.

The growing attraction of Information Sciences and Technologies
toward qualitative methods results, to a large extent, from the increasingly
complex, social and human, nature of the phenomena they deal with.



The Information Systems discipline is considered, today, a
socio-technical discipline, founded on the need to
reconcile technological solutions with the social and human
dimensions of business and the organizational reality.

The main international Information Systems journals, such as
MIS Quarterly, clearly show this tendency, and so does
The Communications of the ACM, one of the most popular
Information Science and Technologies journals.

The same happens with most journals and
conferences devoted to Information Systems.



The field of Human-Computer Interaction (HCI) is also receiving
similar influences from the social and human dimensions of technology use.

A few years ago, user interfaces tended to be developed from rather
mechanistic perceptual and cognitive models. Today, social
and organizational models of interaction have become essential.

Most usability studies are conducted today on the basis of
socio-technical approaches inspired by those used in the social sciences.

In the meantime, we witness a shift of interest from usability – seen
as just effectiveness, flexibility, and satisfaction – toward a
concern with the human experience of living with technology.


A similar evolution is occurring in Software Engineering.
In fact, it started almost thirty years ago:

“Personnel attributes and human relations activities provide by far the
largest source of opportunity for improving software productivity” (Boehm, 1981)

New software development approaches, such as Agile Programming
and Extreme Programming, have in common the characteristic of putting
social and human issues at the center of the development process.

Concepts such as social norms, values, beliefs, symbolisms, representations,
patterns of behavior, which were looked with suspicion in the past,
are considered today as essential to the success of technological projects.



PLOTTING THE QUANTITATIVE vs QUALITATIVE CAMPS IN
STACEY’S CERTAINTY & AGREEMENT REFERENCIAL

Certainty - cause

Disagreement
and effect linkages
can be determined

Uncertainty -
cause and effect
linkages cannot
be determined
and situations
are unique.

Agreement – the level

Agreement
of agreement between
all the parts involved
varies along the axis.

Certainty Uncertainty


Berg, B. L. (2007)

Data Dissemi-
Literature Design Analysis
Ideas Collection nation
Review


Berg, B. L. (2007)

Data Dissemi-
Review

•  Research begins with rough Ideas that turn slowly into research questions.


Berg, B. L. (2007)

Data Dissemi-
Review


•  The Literature Review gradually builds up knowledge about the research ideas.


Berg, B. L. (2007)

Data Dissemi-
Review


•  The Design is the plan to be followed in order to carry out the research.
It must include strategies for the selection of the samples.


Berg, B. L. (2007)

Data Dissemi-
Review


•  The Design is the plan to be followed in order to carry out the research.
It must include strategies for the selection of the samples.
•  The Data Collection and Organization phase is devoted to gathering the data for
the research and organizing it, so that it can be properly analyzed. These are difficult
tasks, since the volume of data collected in qualitative research can be enormous.


Berg, B. L. (2007)

Data Dissemi-
Review

•  The Analysis includes three concurrent flows of action:
•  Data Reduction, which focuses, simplifies, and
transforms raw data into more manageable forms;
•  Data Display, which presents the data as organized and compressed assemblies
of information that permit conclusions to be analytically drawn; and

•  Conclusions & Verification, where the researchers review and finalize all their
conclusions and make sure that they satisfy the requirements of validity.


Berg, B. L. (2007)

Data Dissemi-
Review

•  Dissemination takes the form of very well written
and detailed documents, so that other researchers
can evaluate the analysis and conclusions obtained
and decide if they trust the results and want
to use them to feed their own research.


From a large variety of qualitative research methods used in the
social and human sciences, five stand out as more relevant
in Information Sciences and Technologies research:

Case Studies

Ethnographic Research

Grounded Theory

Action-Research

Design-Based Research


Case studies
Case Studies
Case studies are the most common kind of qualitative method
Ethnographic Research used in Information Sciences and Technologies research.
Grounded Theory They let us study a phenomenon in its real context, specially when
the boundaries between phenomenon and context are not clear.
Action-Research

Design-based Research Typically, the researcher studies a case or variety of cases of real-world
organizations where information sciences and technologies are being
used and concludes about its impacts on the organizational context.

Case studies can also be used for quantitative research, in which case
they tend to follow a positivist approach. One of the best known books
on case studies (Yin, 1994) corresponds to this option. Other authors,
on the contrary, take constructivist and interpretivist approaches.


Ethnographic research
Case Studies
Ethnographic research is inspired by the practices of cultural
Ethnographic Research and social anthropology, where the researcher integrates for a
period of time the community where the study is taking place.
Grounded Theory
This practice is common, not just in Information Sciences and Technologies
Action-Research research, but also in Human-Computer Interaction, in projects that try to
Design-based Research understand the behavior of the users, so that better interfaces can be developed.

It is also being used to understand the behavior of Software
Engineering teams (namely large, complex, distributed, and multi-
national teams) and improve their performance.

The approach is very common when developing and assessing information
systems. E.g., to understand how the 4200 workers of a company react to the
setting up of an CRM solution so as to improve that solution and make
sure that future solutions do not suffer from similar problems.


Grounded Theory
Case Studies
Grounded Theory is a research approach proposed the sociologists
Ethnographic Research Barney Glaser and Anselm Strauss, who claim that research should
depart “from the ground”. The researcher categorizes empirically
Grounded Theory
collected data in order to build a general theory that fits the data.
Action-Research In essence, it is based on the generation of theory from data.
Design-based Research This approach radically defies the traditional positivist
approaches, which claim that the researcher must depart from a
theory, establish hypotheses that conform to the theory, and than
get to the field to confirm the hypotheses in light of the theory.

The models developed by using Grounded Theory are
quite distinctive from the traditional ones in that
they reveal a strong foundation on the concrete.


Action-research
Case Studies
Action-Research is today one of the more promising qualitative research
Ethnographic Research approaches in Information Sciences and Technologies research.
Grounded Theory In essence, it consists of repeatedly going through the cycle:
Action-Research Planning => Action => Reflection

Design-based Research We start by making a plan of our action in a crude first approximation,
we act following that plan, and we then reflect on the results obtained.
From this reflection, we correct our previous plan, act in agreement
with the new plan, and reflect on the results we have now obtained.
The cycles go on, repeatedly, until we are happy with the results.

Action-research corresponds to what John Dewey
called the Principle of Intelligent Action.


Design-based Research
Case Studies
Design-based Research is a research method where
Ethnographic Research knowledge is built in successive approximations while
designing, building, and evaluating an artifact.
Grounded Theory
The artifact may be almost anything: a piece of equipment, a
Action-Research
software application, the solution to a social or technical
Design-based Research problem, a theoretical framework, or even a whole theory.

In essence, it consists of repeatedly going through the cycle:
Awareness of Problem => Suggestion =>
Development => Evaluation => Conclusion

The successive improvements introduced in the artifact as it
is put to test represent opportunities for consolidating the
knowledge that emerges from its design and application.


Four data collection techniques are more relevant
in Information Sciences and Technologies research:

Document Analysis

Interviews

Participant Observation

Surveys


Document Analysis
Document Analysis
Document Analysis covers a broad range of techniques
Interviews devoted to the analysis and interpretation of the
documents used as primary data sources.
The term “document” is understood very broadly, including
Surveys
not just texts, but also sound, photos, videos, and any
materials that carry relevant messages.
Typical varieties of document analysis include:

•  Conversational Analysis
•  Discourse Analysis
•  Narrative Analysis
•  Objective Hermeneutics


Interviews
Document Analysis Interviews are used to collect data from the
subjects interactively, usually one-on-one.
Interviews

They are time consuming, but they are more flexible and adaptable
than surveys. They can present various levels of structure:
Surveys
•  structured interviews
•  semi-structured interviews
When many people are
interviewed simultaneously •  unstructured interviews
and participants are free to
interact with each other, we They are particularly useful to clarify the meaning of a phenomenon to
talk about focus groups. the subjects and to obtain personal accounts about the development
of a process in which the subjects are engaged.

They are also useful to support the exploratory work that precedes a
quantitative study and to clarify and enrich the results of quantitative studies.


Document Analysis
In participant observation the researchers observe first-
Interviews hand the activities of the subjects under study and
collect data from this observation.
There are two basic forms of participant observation:
Surveys
•  overt
•  covert

The technique works well when the activities observed
are frequent, the groups observed are small, and
there is little risk of disturbing the subjects.

It is a time consuming technique, but it is generally
more accurate than post-hoc self-reporting.


Surveys
Document Analysis
In surveys the subjects complete a survey form
Interviews without the intervention of the researcher.
Participant Observation Surveys are particularly useful when the subject population is
Surveys large (or distributed geographically), majority opinions are
sought, and the subjects are motivated to respond.

Surveys can include closed and open questions, but the
number of open questions should be reduced to a minimum.

Special care must be taken to minimize the length of the
survey, manage the choice of words and terminology, look after
the balance of its structure, fully plan the strategies for its
subsequent analysis, and test-pilot it thoroughly.


Codes are tags that categorize the data collected
during a study to assign meanings to them.

Coding makes it easier to search the data, make comparisons
and identify patterns that require further investigation.

It can also be used to extract quantitative data from qualitative data.

Codes can be based on: themes, topics, ideas, concepts, terms,
phrases, or keywords found in the data, but they can also correspond
to passages of audio or video recordings and to parts of images.

A large variety of coding schemes exist, as well as
many software tools – like NVivo and Atlas TI – used to assist
in coding and in helping to organize the resulting patterns.



research research
ideas findings
Research Process


TRIANGULATION With triangulation, the
same issue is studied in
various perspectives
that complement and
verify each other.

research research
ideas findings


TRIANGULATION
4 main kinds of triangulation

Multiple Theories

research research
Multiple Methods findings
ideas

Multiple Data

Multiple Researchers


TRIANGULATION
The new research paradigm
of Mixed Methods has
emerged from this kind of
triangulation
Multiple Theories

research research
Multiple Methods findings
ideas

Multiple Data

Multiple Researchers


Mixed Methods Research (also called, by some authors,
Multiple Method Research or Multimethod Research)
is becoming the third major research approach,
along with quantitative research and qualitative research.

Janice Morse (2003) provides the following distinctions:

Mixed methods design - the incorporation of various qualitative
and quantitative strategies within a single project, that
may have either a qualitative or quantitative theoretical drive.

Multimethod design - the use of two or more research methods,
each conducted rigorously and complete in itself, in one project.
The results are then triangulated to form a complete whole.


For multimethod designs Morse (2003) defines three principles:

Principle 1: identify the theoretical drive
(inductive or deductive) of the project.
Principle 2: develop overt awareness of the dominance (QUAN
or QUAL, and simultaneous or sequential) of each project.

Principle 3: observe methodological integrity.
Multimethod designs, according to Morse (2003)


Two major trends in the debate about rigor
and validity in qualitative research:

•  The exclusive trend, for which the qualitative paradigm is so
radically different from the quantitative paradigm that a new
language must be used to express its rigor and validity.
(Guba & Lincoln, 1981; Guba & Lincoln, 1982; Guba & Lincoln, 1989)

•  The inclusive trend, which argues that the credibility of qualitative
research can only be widely accepted if the language of mainstream
(quantitative) research is maintained, although operationalized
to meet the new conditions and circumstances.
(Yin, 1994; Morse, Barret, Mayan, Olson, & Spiers, 2002, Creswell, 2009)


THE EXCLUSIVE TREND

The proponents of the exclusive trend claim that the terms
‘validity’ and ‘reliability’ from qualitative research do not
make sense in qualitative research, so they should be replaced:

Quantitative Research Qualitative Research
internal validity credibility
external validity transferability
reliability dependability
objectivity confirmability



Credibility is achieved when the results are seen
as believable by the participants in the research.
The participants decide about credibility.

Techniques for establishing credibility include: prolonged
engagement, persistent observation, triangulation, peer debriefing,
negative case analysis, referential adequacy, and member checking.

Transferability exists when the results
can be applied to other contexts.

The researcher should describe in detail the context and
underlying assumptions of the research (thick description), so that
transferability is possible, but the person who transfers the results
to a different context is responsible for the transfer.


Dependability emphasizes the stability of the data over time.

The researcher must be able to account for the permanently changing context in which
the research takes place, describing any changes that occur and how these changes
affect the research. This requires what is sometimes called progressive subjectivity.

Confirmability demonstrates that the inquiry is free of bias, values and
prejudice, i.e. that the data interpretations and outcomes are rooted in
contexts and persons apart from the researcher and are
not mere products of the researcher’s imagination.

The researcher must document the procedures, so that others can check
and recheck the data throughout the study. Techniques that may be used
to strengthen confirmability include: prolonged engagement, persistent
observation, peer debriefing, negative case analysis; and triangulation.

After the study, a data audit or external audit should be
conducted by a researcher not involved in the research process,
to examine both the process and product of the research study.


THE INCLUSIVE TREND

Many proposals exist within the inclusive trend.
The one summarized here is proposed by Creswell (2009):

Qualitative validity does not have the meaning used in quantitative
research: it just means that that the researcher checks for the
accuracy of the findings by employing adequate procedures.

Qualitative reliability indicates that the researcher’s approach is
consistent across different researchers and different projects.

Qualitative generalization is a term used in a limited way in qualitative
research, since the intent is not to generalize finds, but rather to
explore particular phenomena in the context where they occur.


Qualitative Validity

Creswell (2009) proposes the use of eight primary strategies:

  Triangulation
  Member checking
  Rich, thick description
  Avoidance of researcher bias
Two strategies to avoid researcher   Negative case analysis
bias are reflexivity (researcher self-
awareness and self-reflection) and   Prolonged engagement
researcher journaling (detailed and
  Peer debriefing
timely documentation of the
researcher thoughts).   External auditing


Qualitative reliability

Yin (2003) suggests that qualitative researchers should:
  document the procedures of their case studies
  document as many steps of the procedures as possible
  set up a detailed case study protocol and database

Gibbs (2007) suggests several reliability procedures:
  Checking transcripts for mistakes
  Check the persistence of the meaning of the codes
  Coordinate communication among coders
  Cross-check codes developed by different researchers


REFERENCES:

• Berg, B. L. (2007). Qualitative Research Methods for the Social Sciences (6th Ed.). Pearson Education.
• Boehm, B.W. (1981). Software Engineering Economics. Englewood Cliffs, N.J.: Prentice-Hall.
• Creswell, J. W. (2007). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (3rd Ed.), Sage.
• Gibbs, G. R. (2007). Analyzing Qualitative Data. In U. Flick (Ed.). The Sage Qualitative Research Kit. Sage.
• Guba, E. G. (1981). Criteria for assessing the trustworthiness of naturalistic inquiries, Educational Communication
and Technology Journal, 29 (2), 75-91.
• Guba, E. G., & Lincoln, Y. S. (1981). Effective evaluation: Improving the usefulness of evaluation results through
responsive and naturalistic approaches. San Francisco, CA: Jossey-Bass.
• Guba, E. G., & Lincoln, Y. S. (1982). Epistemological and methodological bases of naturalistic inquiry. Educational
Communication and Technology Journal, 30 (4), 233-252.
• Guba, E. G., & Lincoln, Y. S. (1989). Fourth generation evaluation. Newbury Park, CA: Sage.
• Morse, J. M., Barret, M., Mayan, M., Olson, K., & Spiers, J. (2002). Verification strategies for establishing reliability and
validity in qualitative research. International Journal of Qualitative Methods, 1(2), 1-19.
• Morse, J. M. (2003). Principles of Mixed Methods and Multimethod Research Design. In Tashakkori, A, & Teddlie, C.
(Eds.). Handbook of Mixed Methods in Social and Behavioral Research. Sage. 189-208.
• Yin, R. K. (1994). Case Study Research: Design and Methods (2nd Ed.). Sage
• Yin, R. K. (2003). Case Study Research: Design and Methods (3rd Ed.). Sage


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