Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Data analysis – qualitative data presentation 2
1. Qualitative Data
Analysis (QDA)
Presented by :
Kartena Kontesta Binti Arifen
2011160899
Nurul Yasmin Binti Mohamad Yusof
2011192333
2. The Nature of Qualitative
Research
• The term qualitative research refers to
studies that investigate the quality of
relationships, activities, or situations.
• The natural setting is a direct source of
data and the researcher is a key part of
the instrumentation process.
• Qualitative data are collected in the form
of words or pictures and seldom involve
numbers.
3. The Nature of Qualitative
Research (Conti…)
• Coding is the primary techniques used in
data analysis.
• Qualitative researchers are interested in
how things occur and particularly in the
perspectives of the subjects of a study.
• Qualitative researchers, do not, usually,
formulate a hypothesis beforehand and
then seek to test it. Rather, they allow
hypotheses to emerge as a study
develops.
5. What is Qualitative Data Analysis?
• Qualitative Data Analysis (QDA) is the
range of processes and procedures
whereby we move from the
qualitative data that have been
collected into some form of
explanation, understanding or
interpretation of the people and
situations we are investigating.
6. Observation
• Observational data refer to the raw materials an
observer collects from observations, interviews,
and materials, such as reports, that others have
created.
• Data may be recorded in several ways: written
notes, sketches, tape recordings, photographs,
and videotapes.
7. What to look for when doing
observation?
1.Physical setting.
2. Activities.
3. Human, social environment. The way in which human beings
interact within the environment. This includes patterns of
interactions, frequency of interactions, direction of
communication patterns, decision-making patterns.
4. Formal interactions.
5. Informal interactions and unplanned activities.
6. Nonverbal communication.
8. What are field notes?
• Field notes refer to transcribed notes or the written account
derived from data collected during observations and
interviews.
• There are many styles of field notes, but all field notes
generally consist of two parts:
• descriptive - in which the observer attempts to capture a word-
picture of the setting, actions and conversations;
• Reflective - in which the observer records thoughts, ideas,
questions and concerns based on the observations and
interviews.
9. Sample of Field Notes
http://www.louisianafolklife.org/Resources/main_prog_models.html
Sample Fieldnotes: Teen Memories of Grade School Traditions
By Maida Owens, Louisiana Folklife Program
These fieldnotes and interview transcript are provided for
teachers and students as an example of how one folklorist took a
research idea and developed it.
It is difficult to predict exactly how a field project will develop,
where ideas will come from, who will cooperate, and who won't.
Teachers should note that fieldnotes are highly personal and
vary among researchers. This format is similar to journaling and
uses two-column, steno pad format.
10. Develop coding categories
• A major step in analyzing qualitative data is
coding speech into meaningful categories,
enabling you to organize large amounts of text
and discover patterns that would be difficult to
detect by just reading observer commentary.
• Always keep the original copy of observer
commentary.
11. Develop coding categories
(Conti…)
• Next, conduct initial coding by generating
numerous category codes as you read
commentary, labeling data that are related
without worrying about the variety of
categories.
• Write notes to yourself, listing ideas or
diagramming relationships you notice. Because
codes are not always mutually exclusive, a
phrase or section might be assigned several
codes.
12. Develop coding categories
(Conti…)
• Last, use focused coding to eliminate, combine,
or subdivide coding categories and look for
repeating ideas and larger themes that connect
codes.
• Repeating ideas are the same idea expressed by
different respondents, while a theme is a larger
topic that organizes or connects a group of
repeating ideas.
14. Developing your codes
• Coding is a process for categorizing your
data. Develop a set of codes using both
codes that you predefine and ones that
emerge from the data.
• Predefined codes are categories and
themes that you expect to see based on
your prior knowledge.
15. Coding your data
• Closely review and code your data. If possible,
have more than one person code the data to
allow for different perspectives on the data.
• As you proceed you may find that your initial
codes are too broad. Create subcategories of
your codes as needed. Or you may find that you
have created codes that are too detailed and
that attempt to capture every possible idea. In
that case consider how you can pull categories
together into a broader idea.
16. Coding your data (Conti…)
• Coding is a process of reducing the data into
smaller groupings so they are more manageable.
• The process also helps you to begin to see
relationships between these categories and
patterns of interaction.
17. Finding themes, patterns, and
relationships
• Step back from the detailed work of
coding your data and look for the
themes, patterns, and relationships
that are emerging across your data.
• Look for similarities and differences
in different sets of data and see what
different groups are saying.
18. Summarizing your data
• After you have coded a set of data, such as
transcripts of interviews with faculty or
questionnaire responses, write a summary of what
you are learning.
• Similarly, summarize the key themes that emerge
across a set of interview transcripts. When available,
include quotations that illustrate the themes.
• With your data coded and summarized you are
ready to look across the various summaries and
synthesize your findings across multiple data
sources.
21. Content Analysis
• An approach to identify repeated and consistent themes,
images, metaphors, and other meaningful traits within
documents and other communication media.
• Refer to an analysis of the content of a communication.
• It enables researchers to study human behavior in indirect
way by analyzing communications.
22. Reasons conducting content
analysis
• To obtain descriptive information
• To analyze observational and interview data
• To test hypotheses
• To check other research findings
• To obtain information useful in dealing with educational
problem
24. Qualitative Data Collection
• Rather than developing an instrument to use, the researcher
itself is the instrument.
• Collection of data:
• Tape recorder
• Videos
• Photographic data
• Interview must be transcribed.
25. Qualitative Data Analysis
• The analysis is on going process.
• During the organization of the data, researchers will read the
data and get a sense of the whole.
• The ways to interpret content analysis data are:
4.Frequencies
5.Coding to develop themes
6.Computer analysis
26. Coding
• A coding system tells how to distinguish the content from the
medium.
• Sections of text transcripts may be marked by the researcher
in various ways (underlining in a colored pen, given a
numerical reference, or bracketed with a textual code).
• This section contains data which the researcher is interested
in exploring and analysing further.
• In the early stages of analysis, most if not all sections of the
text will be marked and given different ‘codes’ depending on
their content.
• As the analysis progresses these codes will be refined or
combined to form themes or categories of issues.
27.
28. The Coding Process
Initially read
through text
data Divide the text Label the segments
into segments of information Reduce overlap
of information with codes and redundancy Collapse codes
into themes
29. Themes
• A theme is generated when similar issues and ideas expressed
by participants within qualitative data are brought together by
the researcher into a single category or cluster.
• This ‘theme’ may be labelled by a word or expression taken
directly from the data or by one created by the researcher
because it seems to best characterise the essence of what is
being said.
30. Interviewer : What do you perceive as strengths of Greenfield as a community and
how that relates to schools?
Lucy : Well, I think Greenfield is a fairly close-knit community. I think
people are interested in what goes on...
We like to keep track of what our kids are doing, and feel a connection to them because
of that. The downside of that perhaps is that kids can feel that we are looking TOO
close....you said the health of the community itself is reflected in schools...I think... this
is a pretty conservative community overall, and looked to make sure that what is being
talked about in the school really carries out the community’s values.... “And I think
there might be a tendency to hold back a little bit to much because of that idealisation
of “you know, we learned the basics, the reading, the writing, and the arithmetic”). So
you know, any change is threatening....sometimes that can get in the way of trying to
do
different things.
Interviewer : In terms of looking at leadership strengths in the community, where
does Greenfield set in continuum with planning process...forward thinking, visionary
people...
Lucy : I think there are people that have wonderful visionary skills. I would
say that the community as a whole....would not reflect that...I think we have some
incredibly talented people who become frustrated when they try to implement what
they see as their...”
31. List of codes:
1. Close-knit community
2. Health of community; Category:
community values The Community
Look through your list of codes, and identify those that would
inform this categories of ‘the community’. Then look back
through the interview transcript and see if there are any other
references that you have missed.