This document discusses approaches to qualitative inquiry and sampling methods in qualitative research. It describes five common approaches to qualitative inquiry: ethnography, grounded theory, case study, phenomenology, and historical approach. It then discusses the concepts of population, sampling, and different sampling strategies used in qualitative research, including extreme/deviant case sampling, intensity sampling, maximum variation sampling, homogeneous sampling, typical case sampling, critical case sampling, snowball sampling, criterion sampling, theoretical sampling, confirming/disconfirming sampling, stratified purposeful sampling, opportunistic sampling, purposeful random sampling, convenience sampling, and mixed purposeful sampling. The goal of sampling in qualitative research is an in-depth understanding of phenomena rather than generalization.

1. Finding Answers
through Data
Collection

2. - The process of structuring techniques and
strategies that help researchers solve their
problems or answer their inquiry.

3. Approaches to Qualitative Inquiry
1. Ethnography
- involves studying a particular group or
population in the natural setting or in their
habitat.
2. Grounded theory
- commonly used to elicit different
ideas, opinions, or beliefs from the
respondents when a unified theoretical
explanation is needed about an event, an
action, or a process that fits the situation
or actual work in practice.

4. 3. Case study
- it is done when a researcher would
want to know the deeper details about a
certain situation, event, activity, process,
and even a group of individuals.
4. Phenomenology
- describes the common meaning of
several individuals’ lived experiences
about a phenomenon.

5. 5. Historical approach
- is a systematic collection and
evaluation of information, which may
include documents, stories, and artifacts
to describe, explain, and eventually
understand events and actions that
happened in the past.

6. Sampling

7. Population
- It is the complete group of
persons, animals, or objects
that possess the same
characteristics that are of the
researcher’s interest.

8. 2 Kinds of Population
• Target Population
- is made up of all research
elements that the researcher
would want his/her findings to be
generalized to.
• Accessible Population
- is a group of research
elements within which the
research respondents will be
taken from.

9. oIs a group of individuals
that represents the
characteristics of a
population.
oData are collected from
some members of a
population.

10. Sampling
•The process of
choosing samples from
a population.

11. In quantitative research, the
purpose of sampling is to
generalize its findings in the
population; while in qualitative
research, the sampling
focuses on an in-depth
understanding of a
phenomenon or situation.

12. Advantages of
Sampling
• It saves time, effort and
resources.
• It minimizes casualties.
• It paves the way for
thorough investigation.
• It allows easy data
handling, collection,

13. Sampling in Qualitative
Research
1. Extreme or deviant case
sampling
- focuses at highly unusual
manifestation of the
phenomenon of interest. This
strategy tries to select
particular cases that would
gather the most information
about a given research topic.

14. 2. Intensity sampling
- involves information-rich
cases that manifest the
phenomenon intensely, but
not extremely. This type of
sampling requires prior
information on the variation of
the phenomena under study.

15. 3. Maximum variation sampling
- selects a wide range of variation on
dimensions of interest. The purpose
is to discover or uncover central
themes, core elements, and/or
shared dimensions that cut across a
diverse sample. It also provides an
opportunity to document unique or
diverse variations.

16. 4. Homogeneous sampling
- brings together people of
similar backgrounds and
experiences. It reduces
variation, simplifies analysis,
and facilities group
interview. This strategy is
used most often when
conducting focus groups.

17. 5. Typical case sampling
- focuses on what is typical,
normal, and/or average. This
strategy may be adopted when
one needs to present a
qualitative profile of one or more
typical cases. In this sampling, a
broad consensus is required
about what is “average”.

18. 6. Critical case sampling
- looks at cases that will produce
critical information. In order to use
this method, what constitutes a
critical case must be known. This
method permits logical
generalization and maximum
application of information to other
cases because what is true to one
case should also be true to all other
cases.

19. 7. Snowball or chain
sampling
- it is done by asking
relevant people if they know
someone or somebody
fitted or is willing to
participate in
a study.

20. 8. Criterion sampling
- selects all cases that meet
some predetermined criterion.
This strategy is typically applied
when considering quality
assurance issues. In essence,
cases which are information-
rich and which might reveal a
major system weakness that
could be improved may be
chosen.

21. 9. Operational construct or
theoretical sampling
- identifies manifestations of a
theoretical construct of interest
to elaborate and examine the
construct. This strategy is used in
grounded theory studies in
which people or incidents are
sampled based on whether or
not they manifest an important
theoretical or operational
construct.

22. 10. Confirming and
disconfirming sampling
- seeks cases that are both
“expected” and the “exception” to
what is expected. This strategy
deepens initial analysis, seeks,
exceptions, and tests variation.
Both confirming cases and
disconfirming cases must be found.
This strategy is typically adopted
after an initial fieldwork has
established what a confirming case
would be.

23. 11. Stratified purposeful
sampling
- focuses on characteristics and
comparisons of particular subgroups
of interest. In stratified sampling,
samples based on a characteristic are
stratified. Thus, in conducting a study
about academic performance, the
samples are clustered into below
average, average, and above average
learners. The main goal of this
sampling is to capture major
variations.

24. 12. Opportunistic or
emergent sampling
- follows new leads during
fieldwork, takes the advantage
of the unexpected, and is flexible.
This strategy takes advantage of
whatever is readily available for
the researcher and considers
other samples that may be useful
for the researcher as they come.

25. 13. Purposeful random
sampling
- looks at a random sample and
adds credibility to a sample when
the potential purposeful sample is
larger than one can handle. It uses
small sample sizes, its goal is to
increase credibility, not to
encourage representativeness or
the ability to generalize.

26. 14. Convenience sampling
- selects cases based on ease of
accessibility.
15. Combination or mixed
purposeful sampling
- combines two or more
sampling techniques.