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Read, compare and interpret.
Read: What is going
on in the data? (tagging, labelling and coding)
Compare: What is
different about the data? (similarity and difference)
Interpretation:
What does the data mean? uncovering meaning in the data.

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Read, compare, interpret

You read via content analysis, thematic analysis or discourse analysis.

Compare via similarities and differences

interpret data by trying to see what you understand via excel sheets / word / pen & paper

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cyclical process – read multiple times to make sense of data
code, compare and interpret to test if hypothesis is correct

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Coding is a method to analyze data. Use tagging / labels to group data to understanding the data set. You may need to reshuffle the logic to glean a new angle.

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Qualitative data are complex and thus, the challenge when analysing qualitative data is not just the volume of the data but rather it is the depth of the data, eg details, context and subtext. Analysis involves summarising data and then pulling connections across it answer research question. Analyse by Read-Compare-Interpret the data.

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Analyzing data is reading, interpreting, comparing the data, that's been coded to find answers to our research questions. In the process the interpretation or the reading may create new hypotheses and thus the research may become iterative.

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3 approaches in analysing qualitative data:
1) Read the data
Need to understand the data through analysis of content, theme and discourse
2) Comparison of data
Compare the difference in the data collected across different people etc.
3) Interpretation of data
Uncover the meaning in data by looking at your codes and breaking data into blocks to build up an overall meaning

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Coding is method used to analyze data by identifying themes or codes that appear in our qualitative data and then assigning intersections of data to those codes.

Grounded theory 'emergent' coding
Start with a blank sheet of paper, completely open to how the data speaks to me, defining codes and themes as i read the data.

Framework analysis 'structured' coding
Start with a framework of codes and themes beforehand and match the data to the codes and themes as i go along reading the data.

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Qualitative data analysis involves systematically coding and categorizing data to identify patterns, themes, and insights. It requires iterative comparison, interpretation, and reporting to derive meaningful understanding from non-numerical information.

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Coding qualitative data is a process where themes or codes are identified in sources like interviews and documents, and relevant data sections are assigned to these codes. This aids in organizing and analyzing the data. Types of coding include descriptive, thematic, and in vivo coding.

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Purpose is to categorise the data. There are different types of coding:
Descriptive coding: Literal interpretation of the words in text

Thematic Coding: Also ‘descriptive’, Group codes into wider themes

Line-by-line Coding: A code to summarise each line in the text

In vivo-coding: Use participants own words to summarise/code data

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We need to be very familiar with the data we've collected and read, compare and interpret them. We are likely to use zoom in and zoom out strategies to read the data depending on our hypothesis. What struck me is to read not only the data sets but what is not revealed - the subtexts and nuance.

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A long and tedious process of analysing qualitative data, but the richness of the data would be very eye-opening and may give you surprises.

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Read, compare then interpret. Process is iterative and requires a lot of effort.

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Coding is just one way to understand complex qualitative data. There are various ways of coding: eg emergent, structured, descriptive, thematic, in-vivo. There is flexibility to try different ways of coding if one is stuck or does not work well. It is a reiterative cyclical process for different types of coding and different ways to interpret the coding.

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Codes can be amalgamated into themes which can help to refine the researchers' understanding of the issue.

Analysing the subtext and what is unsaid - would that skew the data?

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Read the data over and over and over again to gain further and deeper insights.
Compare the data and interpret it thoroughly.

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Read the data --> Compare the data --> Interpret the data

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Three stages: reading, comparison, interpretation.

reading data essential.

Iterative process, requires skills, deep understanding.

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There are many approaches in coding, the purpose of coding is helping to organise data collected into groups/theme.

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Coding is like tagging, labelling, categorizing data according to themes, making it easier to analyze the data and thus draw some conclusions.

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Assimilation of information to analyse data

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Qualitative coding can identify themes and codes in our qualitative data. It helps to code your data by categorising them. It is also an iterative cyclical process where you will need to re-read your data multiple times.

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Read, compare & interpret. It's time consuming yet very meaningful to obtain rich data. I hope to understand more about what the software can do to ease this process.

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Coding is about sorting information/data into themes or different categories for ease of quoting and referencing to answer a research question. It is helpful but may or may not be necessary? It is one of the many other ways to do Qualitative analysis.

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Qualitative data analysis is a process of reading and analyzing data in close detail in order to understand it. There are many different ways to do this, and the most basic is simply reading the data and identifying what's being said. Other methods include content analysis, which focuses on what is being said, and discourse analysis, which looks at how people are saying things. Once the data has been analyzed, it is often written up and presented in a report.

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Basically you're breaking data into meaningful parts, making sense of data, systematic search for meaning.

Read again again again, in close detail.

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Analysing qualitative data is a multifaceted process that requires a systematic approach. The 3 steps being Reading, Comparing and Interpreting. To facilitate further, qualitative analysis software can serve in aiding in coding the data and offering tools to track and organise our observations.

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Coding is like reading with intent and multiple rounds of coding can help to paint a story to support the research question.

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Some descriptions of the qualitative analysis techniques mentioned:

Content analysis is a method for analyzing the content of text data. It involves systematically coding and categorizing the text to identify patterns and themes. Content analysis can be used to analyze a variety of text data, such as news articles, social media posts, or interview transcripts.

Thematic analysis is a method for identifying recurring themes in qualitative data. It is a more flexible method than content analysis and can be used to analyze smaller amounts of data. Thematic analysis involves reading through the data carefully and identifying patterns and themes. The themes are then defined and named, and the data is coded accordingly.

Discourse analysis is a method for analyzing the use of language in social interaction. It is often used to analyze transcripts of conversations or public speeches. Discourse analysis involves examining the way that language is used to construct meaning and to create social relation

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There are many different approaches to analyse qualitative data. No one right way to do it.

Use the data to answer your research questions.

Read, Compare & Interpret

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the process of creating and assigning codes to categorise data extracts

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Read it carefully, then code it and read it again, analyzing what they have said, and what was the hidden messages that they didn't mention in the feedback.

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As the data collected is often unstructured and messy, coding helps us make meaningful connections so that we can identify relationships and themes. it is likely that we will use different coding approaches and online programmes can help.

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The challenge with qualitative data is not the volume, but the depth of the data, as it involves analyzing and interpreting what is said

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Coding – a way of organising qualitative data

identify recurring themes or patterns to examine data in systematic way
requires interpretation

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Organising the large chunks of data into categories for easy reference and analysis...crafting effective questions is crucial to obtaining rich and meaningful insights into the participants' inner thoughts and feelings.

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Is being a Sherlock Holmes holding a magnifying glass looking through what people say. Categorising by themes etc and go through with an eye for details.

" You know my methods, Watson. There was not one of them which I did not apply to the inquiry. And it ended by my discovering traces, but very different ones from those which I had expected."

The Memoirs of Sherlock Holmes (1893)

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The basics of coding qualitative data, which involves analyzing and assigning labels or tags to identify common themes that emerge in qualitative data.

There are various methods of coding qualitative data, including line-by-line coding, thematic coding, interpreted phenomenological analysis (IPA), and in vivo coding.

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An iterative process of RCI:
- Read to understand
- Compare across groups to find patterns
- Interpret the patterns to answer the research question

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Coding is like sorting clothes in a wardrobe, you need to categorize them according to your preferences for easier retrieve.

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breaking up long and detailed data into common themes or codes, allowing for easier comparison and analysis of different perspectives on specific issues or topics.

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Challenge of analysing qual data: depth and complex due to unstructured data

Typical approach to analyse qual data:
1) Read and familiarise
2) Make comparisons - across different people, categories, time
3) Interpret - what does the data mean?

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3 key stages in analysing qualitative data
(a) Read: Iterative process of seeking clarify of key focus and approach to study (Content/Thematic/Discourse Analysis)
(b) Make comparison and complete write-up
(c) Interpretation (Does not solely focus on what is being said, but also what are the ideas that are missing)

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Analysing coding is to infer meanings from the data collected to make meanings for the research.
Question:
Different researchers come in with different experiences and expectations. How are we to ensure that the data obtained is interpreted correctly? Different people may interpret the same data differently

Must we record and listen to the qualitative data collected via interviews etc instead of just reading it from a transcript? The tone used in the speech during the interview is important as different tones can carry different meanings though the same words may be uttered.

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iterative and cyclical process - read, interpret and analyse

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Using coding/tags to classify data for easy integration and deeper analysis, and then draw accurate conclusions from there.

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Analysing qual data is through reading and familiarising oneself with the data. Coding is used to understand the qual data. Through reading, analysing and comparing the data set, it will help the researchers to identify trends, patterns and discover findings in the data.

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Coding is a long and tedious process. It is iterative so a lot of going back and forth in order to chunk them into categories and themes. There are 2 types of theory - the Grounded and the Framework theories. We can use the two theories together,

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By coding, it transforms raw data into meaningful insights and patterns. Various coding techniques offer distinct approaches. Grounded theory encourages the data to communicate organically and allow themes to take shape through iterative coding. Framework analysis employs a structured framework for coding in systematic organization and categorization. Discourse analysis takes a broader perspective in examining the language patterns, social constructs.

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Read your data...again and again and again...
Familiar yourself with the nuance of your data.

Challenge of qualitative data is the depth and not the volume.

3 step approach:
- Read
- Compare
- Interpret

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Read ... Understand......Compare

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Qual Coding - arrange data into different categories

1) Grounded theory

2) Framework analysis

or Both

Can group into themes, using own words, IPA, line by line,

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Coding is essentially identifying what is of interest in the data and categorizing information. The coding process involves breaking up long qualitative data into common themes for comparison across different sources.

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This is what AI is for. Unfortunately if you do your own labelling you will get more intimate with the data... so no AI is going to help you become KNOWLEDGEABLE of the samples that you have collected

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Read, summarise, use content/thematic/discourse analysis and compare, interpret by checking to see if it matches the hypothesis.

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Read-Compare-Interpret 3-step approach.
Read is an iterative cyclical process.
Compare what's different and similar across data.
Interpret what the data means, uncovering meanings in the data

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categorising texts into groups (= lego blocks) for subsequent analysis of the bigger meaning (= building lego blocks)

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Read the data, go through it, code it and read it again. Thematic coding is one way of doing coding.

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Haha! Book report! You have no choice but to reaaly dig into your data by reading, re-reading and doing alll again - to get essence and nuance of opinions and perspective...

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Qualitative data analysis is a process of reading and analyzing data in close detail in order to understand it.

There are many different ways to do this:

1.  reading the data and identifying what's being said.
2. content analysis which focuses on what is being said
3. discourse analysis which looks at how people are saying things, and more importantly, what is not being said.

Once the data has been analyzed, it is often written up and presented in a report.

Three stages of analysis of qualitative data:
reading , comparing and interpreting.

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It's like writing a book report - it's shorter than the book itself but will give the reader a better idea of what the book is about + an analysis of the story

Read, compare, interpret

Analysis --> uncovers patterns in data
Interpretation --> uncovers meanings

www.quirkos.com

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Quick to learn, flexible to use

Quirkos is easy to master, with just the essential tools you need to help you focus on the richness of your small qualitative data sets.

Organise your sources, canvas and codes in any way, and finely categorise and filter your data. Our flexible design is agnostic, so you can use grounded theory, thematic analysis, or IPA as you prefer.

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Quirkos - Qualitative Data Analysis Software made simple

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Quirkos makes qualitative data analysis software that's simple to learn and use, and affordable.

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Coding of qualitative data is about categorising the information to gain a more in depth understanding and make more meaning out of what has been collected from the subjects.
Question:
1) How do we know which is the most effective way of coding our data?

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Look out for common themes (tags/labels) and compare by using line by line coding or in vivo coding for further interpretation.

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As qualitative data explores complex and detailed topics with various contexts and subtexts, the challenge lies not just in the volume of data but in its depth.

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Putting things into categories. A way to manage data will make it easier for report writing later on.

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Knowing your data very well --> reading it over and over again/ analysing it in very close detail

Coding --> to uncover patterns and meaning in the data

Coding is useful to help
- find quotes which support your arguments & answer your research questions
- look for the interesting sections (line by line/ IPA /in vivo coding)

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Coding is organising data into categories and identifying patterns.

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Qual Coding is a systematic way to categorise and identify patterns of data with recurring themes. Its overall aim is to provide a comprehensive and meaningful interpretation of qualitative data.

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code = tags
theme = larger ideas/ concepts

e.g.,
code = cereal
theme = healthy eating

There are many different coding approaches.

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Coding is the process of managing your data, putting them into categories.

Grounded theory “emergent” coding – a blank sheet, no preconceptions of what you're going to find in the data

Framework analysis “structured” coding -  you got your codes and theme beforehand and what you're trying to do is match the data to the codes that you’ve already identified

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Coding is nearly always an iterative cyclical process - going through the data and analysing them over and over again.

Coding your coding - grouping up the codes/themes into categories.

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Analyzing qualitative data is a lot about interrogating the data, summarizing it and putting connections across it.

Aim:
Use the data to answer your research questions

How:
3-step Approach: Read, Compare and Interpret the data

Read: An iterative and cyclical process where we read the data again and again and familiarize ourselves with it. (Almost as if we can even read it backwards)

Content Analysis

Thematic Analysis

Discourse Analysis

Coding: Line by Line, IPA, In Vivo

Compare: What are people saying, why are they different, different data given across different questions, different people, whay are some people saying some things and why are some people NOT saying some things.

Interpret: Going back again to read and analyze the analysis. "It involves uncovering patterns in data and interpretation involves uncovering meaning ..., messy, multiple meanings..."
Does this data match what we are going to say? Can that support how we interpret our data?

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Coding is a iterative process where we need to go back and forth to look at it allows us to continuously refine our understanding of the data and to identify new patterns and themes. As we code the data, we may be seeing connections between different codes or we may need to create new codes to capture the meaning of the data.

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Qual coding is only one of the many ways to support meaning making and analysis of qualitative data needs to be a iterative process. The use of technology could also be useful in the process. The 2 kinds of coding could be based on the emergent theory or 'structured' coding approach.

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2 types of coding: Grounded and structured

1. Grounded Coding:  codes and categories emerge directly from the data. Involves closely reading and analyzing the data, identifying key concepts, and assigning codes to represent those concepts.

2. Structured Coding: codes and categories are predetermined based on existing theories or prior knowledge. Involves applying these codes to the data and organizing the data into predetermined categories.

Approaches are not mutually exclusive and may use a combination of both in their analysis.

Coding is an iterative cyclical process, and you go back and do it over and over again and reading it through multiple times to try to put the codes and themes into different groups.

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Coding is an iterative cyclical process to sort and organise data, to get to know your data. When a coding approach does not work for us, we can go back and try another approach from a different viewpoint. It requires interpretation to make the analysis complete.

Ways of Coding Data:
Descriptive
Thematic
Line-by-line
Interpretive phenomenological analysis (IPA) - participant's conceptual understanding of the world
In-vivo - using own words to summarise
Discourse analysis

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look for codes or common threads and put into categories for easier data mgt

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Coding is categorizing and sorting data for ease of reference and analysis.

Braun and Clarke (2006)
Codes: "Pithy labels identifying what is of interest in the data"

Themes: "A common, recurring pattern across dataset, clustered around a central organising concept"

Coding is not a must. It's just one way to understand and explore complex qualitative data.

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Coding is like putting things into categories e.g. finding out what different ppl have said about a particular topic so that you can manage your data

2 types of coding
- grounded theory (on the fly)
- framework analysis (already have list of codes before starting)

but usually a combination of both

Coding is an iterative process, get to know your data better (it's not a must but it's just easier) :)

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READ , read , read , read until we understand
(said and not said)
COMPARE find coding
INTERPRET - does it support or not, themes / blocks
what is relevant to us

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Coding qualitative data involves analyzing and assigning tags or labels to identify common themes that appear in qualitative data such as interviews or documents. Coding helps in breaking up long and detailed qualitative data into themes or categories to compare what people are saying about a particular topic.
The 2 kinds of coding are :

Grounded theory/emergent coding where one starts with a blank sheet and defines the codes and themes on-the-fly.

Framework analysis/structured coding where an individual has a list of codes and themes beforehand and tries to match the data to them.

Sometimes, researchers use a combination of both methods as they extract information from qualitative data.

Coding is an iterative process that requires multiple passes through the data and may involve multiple levels and types of coding.

While coding is an important step in the process, it is not an end itself and must be followed by further interpretation and analysis.