This ppt will be helpful for the Ph.D. Research Scholars and students pursuing M.Ed. and M.A. Education and other PG courses.

1. Coding, Segmenting and Categorizing in
Qualitative Data Analysis
Dr. Sarita Anand
Assistant Professor
Department of Education
Vinaya Bhavana (Institute of Education)
Visva-Bharati, Santiniketan, WestBengal, India
sarita.anand@visva-bharati.ac.in

2. Think about Qualitative Analysis “It is about
reducing data without losing its meaning”
-Philip Adu

3. Qualitative Data Analysis
Qualitative data analysis is the process of examining and
interpreting qualitative data to understand what it represents.
Qualitative data is defined as any non-numerical and unstructured
data; when looking at customer feedback, qualitative data usually
refers to any verbatim or text-based feedback such as reviews,
open-ended responses in surveys, complaints, chat messages,
customer interviews, case notes or social media posts

4. ● Content analysis: This is the most common example of qualitative data analysis.
It refers to the categorization, tagging and thematic analysis of qualitative data.
This can include combining the results of the analysis with behavioural data for
deeper insights.
● Narrative analysis: Some qualitative data, such as interviews or field notes may
contain a story. For example, the process of choosing a product, using it,
evaluating its quality and decision to buy or not buy this product next time.
Narrative analysis helps understand the underlying events and their effect on the
overall outcome.
● Discourse analysis: This refers to analysis of what people say in social and
cultural context. It’s particularly useful when your focus is on building or
strengthening a brand.
Types of Qualitative Data Analysis

5. ● Framework analysis: When performing qualitative data analysis, it is
useful to have a framework. A code frame (a hierarchical set of themes
used in coding qualitative data) is an example of such framework.
● Grounded theory: This method of analysis starts by formulating a theory
around a single data case. Therefore the theory is “grounded’ in actual
data. Then additional cases can be examined to see if they are relevant
and can add to the original theory.
Types of Qualitative Data Analysis

6. —Saldana, 2013
“A code is word, phrase, sentence that represents aspect(s)
of a data or captures the essence or features of a data”
Code= Assigning labels to Data
Data in Qualitative Research= Interview transcripts, Field Notes,
Documents or Artifacts etc.

9. Coding
● Coding is usually the first phase in data analysis of qualitative data, where codes are
assigned to features in the data.
● Coding is the process of labelling and organizing your qualitative data to identify
different themes and the relationships between them.
● When coding any kind of feedback, you assign labels to words or phrases that
represent important (and recurring) themes in each response. These labels can be
words, phrases, or numbers; we recommend using words or short phrases, since
they’re easier to remember, skim, and organize.

10. ● The origin of the codes used is usually distinct in confirmatory
research (where predetermined codes are often derived form the conceptual
framework before data collection), and in discovery research (such as
in grounded theory studies) where the codes are derived from the data
itself: open coding.
Coding
Now, question comes …what are
confirmatory research……
&
discovery research……

11. “Confirmatory research sets out to test a specific hypothesis to the exclusion of
other considerations; whereas discovery research seeks to find out what
might be important in understanding a research context, presenting findings
as conjectural (e.g., ‘suggestive’, ‘indicative’) rather than definite”.
● Confirmatory research Questions are closed-ended.
Confirmatory Research

12. ● Discovery research is concerned with theory generation (i.e., it is an inductive
process) rather than hypothesis testing.
● Coding has been described within a grounded theory perspective as- “Coding:
The analytic process through which data are fractured, conceptualized, and
integrated to form theory”
● Discovery or exploratory research questions are open-ended.
Discovery Research

13. Open Coding
01.
Axial Coding
02.
Selective Coding
03.
Memos*
04.
Types of Coding

14. Types of Coding

15. ● Open coding is a procedure of coding data that does not rely upon a preconceived set
of codes, but rather is open to the analyst using whatever codes seem to best work
(fit) for the data being analysed.
● Open coding is common in interpretive research using qualitative data.
● Open coding is important in grounded theory studies as the first stage in the
analytical process known as constant comparison. Effective open coding relies upon
the theoretical sensitivity of the analyst.
● “The analyst codes for as many categories as fit successive, different incidents, while
coding into as many categories as possible. New categories emerge and new
incidents fit into existing categories” (Glaser & Holton, 2004, 48)
Open Coding

16. ● Substantive codes:
● Open coding supports the development of ‘substantive’ categories, i.e. categories
close to the empirical level
● “The conceptualization of data through coding is the foundation of GT development.
Incidents articulated in the data are analyzed and coded, using the constant
comparative method, to generate initially substantive, and later theoretical,
categories.... Theoretical codes conceptualize how the substantive codes may relate
to each other as hypotheses to be integrated into the theory.” (Glaser & Holton, 2004)
Open Coding

17. • Axial coding is a stage in grounded theory analysis (‘constant comparison’) after open
coding, where the researcher seeks to make links and find relationships between the
concepts and categories derived from open coding.
• “Coding gets the analyst off the empirical level [i.e. towards the theoretical level] by
fracturing the data, then conceptually grouping it into codes that then become the
theory that explains what is happening in the data.” (Glaser & Holton, 2004)
Developing theoretical codes and categories
After substantive codes are developed through the process of open coding, these are
related through the development of theoretical codes.
Axial coding

18. • Selective coding is a stage in grounded theory analysis (constant comparison) which is
undertaken once a core variable has been identified
•
• “Selective coding means to cease open coding and to delimit coding to only those variables that
relate to the core variable in sufficiently significant ways as to produce a parsimonious theory.
Selective coding begins only after the analyst is sure that he/she has discovered the core
variable.” (Glaser & Holton, 2004)
•
• At this point theoretical sampling is focused on developing theory around the core variable
• “Subsequent data collection and coding is thereby delimited to that which is relevant to the
emergent conceptual framework. This selective data collection and analysis continues until the
researcher has sufficiently elaborated and integrated the core variable, its properties and its
theoretical connections to other relevant categories.” (Glaser & Holton, 2004)
Selective coding

19. • Memoranda (memos) are used in everyday life as a record or communication of information.
• In some forms of research the analyst is encouraged to write analytic memos as part of the
process of analysing data.
• In grounded theory (GT) methodology writing memos is used as analytical technique to support
the construction of theory. Memos are a way of recording, reflecting on, and thinking through, the
ideas that arise during analysis.
• “Theory articulation is facilitated through an extensive and systematic process of memoing that
parallels the data analysis process in GT. Memos are theoretical notes about the data and the
conceptual connections between categories. The writing of theoretical memos is the core stage in
the process of generating theory. If the analyst skips this stage by going directly to sorting or
writing up, after coding, he/she is not doing GT.” (Glaser & Holton, 2004, ¶60)
• “The basic goal of memoing is to develop ideas on categories with complete freedom into a memo
fund that is highly sort-able. … Early on memos arise from constant comparison of indicators to
indicators, then indicators to concepts. Later on memos generate new memos, reading literature
generates memos, sorting and writing also generate memos—memoing is never done!” (Glaser &
Holton, 2004, ¶64)
Research (analytic) memos

21. • Choose whether you’ll use deductive or inductive coding.
• Read through the data to get a sense of what it looks like. Assign the first set of
codes.
• Go through all the data line-by-line to code as much as possible. Codes should
become more detailed at this step.
• Categorize the codes and figure out how they fit into the coding frame.
• Identify which themes come up the most — and act on them.
• Let’s break it down a little further…
How to manually code qualitative data

22. • Before start qualitative data coding, we need to decide which codes we’ll use.
Deductive coding vs. Inductive coding

23. Deductive coding
•Deductive coding means we start with a predefined set of codes, then assign those
codes to the new qualitative data. These codes might come from previous research, or we
might already know what themes we’re interested in analyzing. Deductive coding is also
called concept-driven coding.
•For example, let’s say you’re conducting a survey on customer experience. You want to
understand the problems that arise from long call wait times, so you choose to make “wait
time” one of your codes before you start looking at the data.
•The deductive approach can save time and help guarantee that our areas of interest are
coded. But we also need to be careful of bias; when we start with predefined codes, we
have a bias as to what the answers will be. Make sure that we don’t miss other important
themes by focusing too hard on proving our own hypothesis.

24. Inductive coding, also called open coding, starts from scratch and creates codes based on the
qualitative data itself. You don’t have a set codebook; all codes arise directly from the survey
responses.
Here’s how inductive coding works:
Break the qualitative dataset into smaller samples.
• Read a sample of the data.
• Create codes that will cover the sample.
• Reread the sample and apply the codes.
• Read a new sample of data, applying the codes you created for the first sample.
• Note where codes don’t match or where you need additional codes.
• Create new codes based on the second sample.
• Go back and recode all responses again.
• Repeat from step 5 until you’ve coded all of your data.
• If you add a new code, split an existing code into two, or change the description of a code, make
sure to review how this change will affect the coding of all responses. Otherwise, the same
responses at different points in the survey could end up with different codes.
• Inductive coding is an iterative process, which means it takes longer and is more thorough than
deductive coding. But it also gives you a more complete, unbiased look at the themes throughout
your data.
Inductive Coding

25. • Once we create our codes, we need to put them into a coding frame.
• A coding frame represents the organizational structure of the themes in our research.
• There are two types of coding frames: flat and hierarchical.
• Flat Coding Frame: It assigns the same level of specificity and importance to each
code. While this might feel like an easier and faster method for manual coding, it can
be difficult to organize and navigate the themes and concepts as we create more and
more codes. It also makes it hard to figure out which themes are most important,
which can slow down decision making.
• Hierarchical Coding Frame: It help us organize codes based on how they relate to
one another. For example, we can organize the codes based on our student’s feelings
on a certain topic
Categorize your codes with coding frames

26. Hierarchical Coding Frame
In this example:
The top-level code describes the topic (customer service)
•The mid-level code specifies whether the sentiment is positive or negative.
•The third level details the attribute or specific theme associated with the topic
•Hierarchical framing supports a larger code frame and lets you organize codes based on organizational
structure. It also allows for different levels of granularity in your coding.
•

27. Segmenting involves dividing the data into meaningful analytical units. When
you segment text data, you read the text line by line and continually ask
yourself the following kinds of questions:
Do I see a segment of text that has a specific meaning that might be important
for my research study?
Is this segment different in some way from the text coming before and after it?
Where does this segment start and end?
A meaningful unit (i.e., segment) of text can be a word, a single sentence, or
several sentences, or it might include a larger passage such as a paragraph
or even a complete document. The segment of text must have meaning that
the researcher thinks should be documented.
• Segmenting=Dividing data into meaningful analytical units
SEGMENTING AND DEVELOPING
CATEGORY SYSTEMS

29. Categorization is a major component of qualitative data analysis
by which investigators attempt to group patterns observed in
the data into meaningful units or categories. Through this
process, categories are often created by chunking together
groups of previously coded data.
Categorizing data in qualitative research

30. • Group responses based on themes, not wording
• Make sure to group responses with the same themes under the same code, even if they don’t use
the same exact wording. For example, a code such as “cleanliness” could cover responses
including words and phrases like:
• Tidy
• Clean
• Dirty
• Dusty
• Looked like a dump
• Could eat off the floor
• Having only a few codes and hierarchical framing makes it easier to group different words and
phrases under one code. If we have too many codes, especially in a flat frame, our results can
become ambiguous and themes can overlap.
• Manual coding also requires the coder to remember or be able to find all of the relevant codes; the
more codes we have, the harder it is to find the ones we need, no matter how organized your
codebook is.
Make accuracy a priority
Remember

31. Let’s Revise

32. • Here are 6 final takeaways for manually coding our qualitative data:
• Coding is the process of labeling and organizing our qualitative data to identify themes. After we
code our qualitative data, we can analyze it just like numerical data.
• Inductive coding (without a predefined code frame) is more difficult, but less prone to bias, than
deductive coding.
• Code frames can be flat (easier and faster to use) or hierarchical (more powerful and organized).
• Our code frames need to be flexible enough that we can make the most of our results and use them
in different contexts.
• When creating codes, make sure they cover several responses, contrast one another, and strike a
balance between too much and too little information.
• Consistent coding = accuracy. Establish coding procedures and guidelines and keep an eye out for
definitional drift in your qualitative data analysis.
Conclusion:

33. Softwares for Qualitative Data Analysis

34. Saldana, J. (2013). The coding manual for qualitative researchers. London: Sage
Creswell, J. W. (2013). Qualitative Inquiry and Research Design: Choosing Among , Five Approaches
(3rd). Thousand Oaks, CA: Sage.
Glaser, Barney G. & Holton, Judith (2004) Remodeling Grounded Theory, Forum: Qualitative Social
Research, 5(2), Article 4.
https://science-education-research.com/EdResMethod/Coding.html
https://getthematic.com/insights/coding-qualitative-data/
References

35. Thank You