This document discusses qualitative research methods. It defines qualitative research as seeking to understand opinions, experiences, and feelings through subjective data rather than numerical data. The document outlines several key characteristics of qualitative research, including that it takes place in natural settings, collects non-numerical data like words or illustrations, is concerned with processes, and analyzes data inductively by drawing out general ideas. It also discusses the need for qualitative research, ethics, and ways to link qualitative and quantitative research approaches.

1. Qualitative Research Methods
By Asst Prof Anil Sharma
7990189234

2. Unit 1
• Qualitative Research: Nature, Relevance,
Need, Characteristics and Limitations of
Qualitative Research, Ethics in Qualitative
Research, Interrelationship of Qualitative and
Quantitative Research, Linking Qualitative and
Quantitative Research in One Design,
Combining Qualitative and Quantitative Data,
Combining Qualitative and Quantitative
Methods, Linking Qualitative and Quantitative
Results, Triangulation. (5)

3. Introduction
• Researchers more comfortable with quantitative
• research
• Quantitative methods deal with the collection
and processing numerical data
• Answer questions
– How often? To what extent?
– How much? How many … but cannot answer questions
on – Why? how? In what way?

4. Relevance
• Understanding opinions, experiences, feelings of
individuals or communities to produce subjective
data to make generalizations
• Exploring social phenomenon or issues by
examining people or communities in their natural
settings
• Describing cultures, social stratifications and
social groups in their natural settings
• Exploring relationships between individuals or
communities, cultural norms, and economic and
political ideas

5. • Qualitative research can provide insight which is
not
• possible to elucidate with purely quantitative data
– A means for exploring and understanding the
meaning individuals or groups ascribe to social
or human problems
– Study human behavior and social world
• Help us to understand the world in which we live
• and why things are the way they are

6. • Qualitative research answer questions on:
– Why people behave the way they do
– How opinions and attitudes are formed
– How people are affected by the events that go on
around them
– How and why cultures have developed
The difference between social groups

7. What is qualitative research?
• Development of concepts which help us to
understand social phenomena in natural
(rather than experimental) settings, giving
due emphasis to the meanings, experiences
and views of the participants.
Pope & Mays

8. • Fraenkel (2007) defined qualitative research
as research studies that investigate the quality
of relationships, activities, situations, or
materials.
• It is described by its aims, methodology, and
the kind of data collected to understand the
different facets of social life.

9. • Qualitative approaches to research are
universal and holistic. They follow these
beliefs: -A single reality is not observed. -
Reality is based upon concepts that are
distinct for each person and change over time.
-What we perceive has meaning only within a
given situation.

10. Dimensions of qualitative methods
Understanding context
• How economic, political, social, cultural, environmental
and organizational factors influence health
Understanding people
• How people make sense of their experiences of health
and disease
Understanding interaction
• How the various actors involved in different public
health activities interact each other

11. Characteristics of Qualitative Research
• 1. The direct source of data is the natural
setting and the researcher is the key
instrument in qualitative research.
Researchers go directly to the particular
setting of interest to observe and collect the
needed data.

12. • 2. Data collected are in the form of words or
illustrations rather than numbers. The kinds of
data collected may include, but not limited to,
audio recordings, diaries, field notes,
memorandums, official records, personal
comments, photographs, textbook passages,
transcripts of interview, videotapes, and
anything else that convey actual words or
actions of people.

13. • 3. Qualitative research is concerned with
process as well as product. The primary
interest of a qualitative researcher is on how
things happen and on people’s interaction
with one another.

14. • 4. Analysis of data is taken inductively. It starts
with the specific concepts of the respondents
to draw out general idea or theory. To do this,
a considerable amount of time is spent in
collecting data before the important questions
are considered.

15. • 5. Qualitative research deals with how people
make sense out of their lives. The perspective
of the subjects of a study is a major concern.

16. Need of Qualitative Research
• Draw meaningful information about beliefs, feelings,
values, and motivations that support behavior.
• Learn directly from people and what is important to
them.
• Provide the context required to elicit qualitative
results.
• Identify variables important for further studies.
• Determine one’s genre as a primary step to develop a
quantitative survey.
• Assess the usability of websites, databases, or other
interactive media/services.

17. Ethics in Qualitative Research
• The researcher can expect to deal with the following ethical
issues
• Worthiness of the project
• Informed consent
• Benefits, costs, reciprocity
• Honesty and trust
• Privacy, confidentiality, and anonymity
• Researcher integrity and quality
• Ownership of data and conclusions
• Use and misuse of results
• Intervention and advocacy

18. Interrelationship of Qualitative
and Quantitative Research

19. Qual Vs Quan: Basic differences
Qualitative Quantitative
Purpose To describe a situation,
gain insight to particular
practice...
To measure magnitude-How
widespread is a practice...
Format No pre-determined
response categories
Pre-determined response
categories, standard measures
Data In-depth explanatory data
from a small sample
Wide breadth of data from large
statistically representative sample
Analysis Draws out patterns from
concepts and insights
Tests hypotheses, uses data to
support conclusion
Result Illustrative explanation &
individual responses
Numerical aggregation in
summaries, responses are
clustered
Sampling Theoretical Statistical

20. Qual Vs Quan: Analytic approaches
Quantitative Qualitative
Research question Fixed/Focused Broader, contextual,
flexible
Expected outcome Identified
in
advance
Usually not
predefined, emergent
research question
Hierarchy of phases Linearity Circular
Confounding factors Controlled
during design
& analysis
Searched in the field
Time dimension Slower Rapid to slower

21. Qual Vs Quan: Data collection
method
Quantitative Qualitative
Sampling Random sampling Open ended and less
structured protocols
(Flexible)
Tools Structured data
collection
instruments
Depend on
interactive
interviews
Results Produce results that
generalize,
compare and
summarize
Produce results that give
meaning, experience and
views
21

22. DEDUCTIVE & INDUCTIVE REASONING

23. Deductive thinking (Quantitative)
THEORY
HYPOTHESIS
OBSERVATION
CONFIRMATION

24. Inductive thinking (Qualitative)
OBSERVATION
PATTERNS
HYPOTHESIS
THEORY

25. Linking Qualitative and Quantitative
Research in One Design
• Integration is an intentional process by which the
researcher brings quantitative and qualitative
approaches together in a study. Quantitative and
qualitative data then become interdependent in
addressing common research questions and
hypotheses.
• Quantitative, Qualitative, and Mixed Methods
• If the researcher uses numbers, they are using a
quantitative measure; if they use a descriptive
style, it is qualitative measure; and if they are
somewhere in between, it is a mixed method.

26. • Combining qualitative and quantitative methods. In
practice, most researchers agree that combining
quantitative and qualitative techniques (sometimes
called “mixed method” research) produces a richer and
more comprehensive understanding of a research area.
• Using a combination of qualitative and quantitative
data can improve an evaluation by ensuring that the
limitations of one type of data are balanced by the
strengths of another. This will ensure that
understanding is improved by integrating different
ways of knowing.

27. Purpose
• Enriching: using qualitative work to identify issues
or obtain information on variables not obtained
by quantitative surveys.
• Examining: generating hypotheses from
qualitative work to be tested through the
quantitative approach.
• Explaining: using qualitative data to understand
unanticipated results from quantitative data.
• Triangulation (Confirming/reinforcing; Rejecting):
verifying or rejecting results from quantitative
data using qualitative data (or vice versa)

28. Approaches to Linking
• Several researchers have described ways that
qualitative and q
• Four major approaches:
• I. Antecedent or sequential;
• 2. Encapsulated or nested;
• 3. Concurrent;
• 4. Primary/secondary combinations.

29. I. Antecedent or sequential
• Antecedent or sequential which generally refers to using qualitative
data first to develop quantitative instruments, offers many benefits.
• The contributions made by analyzing qualitative data prior to
quantitative data collection lie in rationalizing a study and
identifying issues that need to be measured.
• For example, the use of focus groups to begin to narrow a topic and
develop questionnaire items is a common antecedent practice
(Krueger, 1988). In this case, broad questions are used to develop
survey items that can be used to assure greater validity.
• Austin, Hoge, and - Austin (1990) used an open-ended format to
obtain information from students about the advantages,
disadvantages, or other associations that students saw resulting
from serving persons with disabilities in community recreation
programs. From these responses, a fixed-format instrument titled
the Leisure Service Student Questionnaire was developed.

30. 2. Encapsulated or nested
• Encapsulated or nested linkages can provide a conceptional
framework for verifying and clarifying findings. Researchers may
embed in-depth interviews within a quantitative study to provide a
context and check on the validity of quantitative procedures.
Qualitative data, for example, can aid in interpreting statistics and
deciphering puzzling responses.
• McAvoyet al. (1989) used encapsulated data in studying integrated
wilderness adventure programs. They used structured interviews as
a follow-up after pre, post, and follow-up quantitative data had
been collected about trait anxiety reduction.
• Forty individuals from the sample of 121 individuals used to collect
quantitative data were interviewed to help the researchers
understand the process of how adventure programs can result in
attitude and lifestyle changes.

31. 3. Concurrent
• When data collection occurs concurrently and interpretation is done
simultaneously, the data can help to understand phenomena to a broader
and deeper extent. Bullock et al. (1992) used concurrent data in an
evaluation of the Easter Seals' mainstreaming model
• To get data about this pro gram, Consumer satisfaction surveys, provider
satisfaction surveys, and in-depth interviews with campers, campers, and
service providers were used concurrently.
• Bedini et al. (1993) administered quantitative questionnaires to students,
parents, and teachers along with a content analysis of the implementer's
notes and in depth interviews with a subsample of students to measure the
results of a leisure education program. The different data sets served to
corroborate the outcomes measured with each type of data. Researcher
must be aware, however, that sometimes contradictory information occurs
in linking two types of data concurrently. The researcher must be prepared
for this possibility and will be required to address what the meaning of the
contradictions if they arise.

32. 4. Primary/secondary combinations
• Data can also be used in a primary (secondary combination within a study.
In this form of linkage, a study may be primarily qualitatively driven but
quantitative data are used for background.
• For example, quantitative data can be used prior to the collection of
qualitative data to determine what representative cases ought to be
further explored. The statistics obtained from quantitative data can provide
a basis for exploring issues in greater depth through qualitative data.
• Quantitative information can also provide leads for future qualitative
questions, correct the elite bias effect of articulate respondents, and help
to confirm hypotheses or themes that emerge from qualitative data.
Although neither form of data seemed to be more primary than the other,
Malkin et al. (1989) based their selection criteria for open-ended
interviews with female suicidal psychiatric patients on the demographic
subgroups that were identified through initial quantitative data collection.

33. Combining Qualitative and Quantitative
Methods, Linking Qualitative and
Quantitative Results

34. • Mixing qualitative and quantitative methods is neither new
nor controversial. In fact, there’s a journal dedicated to mixed-
method research, aptly named, The Journal of Mixed Method
Research.
• Customer research lends itself well to the triangulating that a
mixed-methods approach offers: identifying areas of
convergence among methods to, in turn, increase the
usefulness and validity of the findings.
• While you can combine qualitative and quantitative methods
at various points—data collection or data analysis, for
example—we typically use the following three research
designs (also called topologies).

35. Triangulation

36. Explanatory Sequential Design
• An explanatory sequential design emphasizes
quantitative analysis, which we follow with
interviews or observation (qualitative
measures) to help explain the quant findings.

37. • For example, we conducted a large comparative
branding study with an internet retailer on attitudes
toward the shopping experience on five mobile
websites. After statistical analysis and cross-tabbing on
experience levels to gauge brand attitudes, we came
up with topics to further explore. We then recruited a
new set of 16 participants for 1-on-1 sessions in which
participants interacted with the sites used earlier and
discussed their attitudes toward those sites.
• This enabled us to look more closely into trends we
observed in the larger sample. In this study we used a
new set of 16 participants; you can also use a subset of
participants from the first survey phase and dig deeper
into any interesting patterns. To remember, the
explanatory sequential design, think of qual explaining
quant.

38. Exploratory Sequential Design
• An exploratory sequential design starts with
the qualitative research and then uses insights
gained to frame the design and analysis of the
subsequent quantitative component.

39. • For example, to develop a new questionnaire, start with a
qualitative phase where you interview participants and
identify phrases, questions, or terms used to help derive
the items used. We used this approach to develop the
SUPR-Q.
• Exploratory sequential design lends itself well to usability
testing. We often start with 5 to 10 participants in a classic
think-aloud, moderated usability test. This exposes
problem areas for which to create new tasks and survey
questions, which in turn helps us refine our understanding
of customer attitudes. We then launch a larger-scale, un
moderated study to get a better idea of the magnitude of
the problems in the larger customer population.
To remember the exploratory sequential approach, think of
qual to enable research questions followed by quant for
validation.

40. Convergent Parallel Design
• If you collect qualitative data and quantitative data
simultaneously and independently, and if you then analyze
the results, you’re executing a convergent parallel design. In
the analysis phase, you often give equal weight to the quant
and qual data—you look to compare and contrast the results
to look for patterns or contradictions.

41. • For example, one team may conduct
ethnographic research at customer locations
while another launches a survey to a set of
global customers on the same product
experience. The teams then converge and
compile the findings to generate insights.

42. • Thank you