Qualitative Coding Tutorial: How To Code Qualitative Data For Analysis (4 Steps + Examples)

Summary

This video script offers a comprehensive guide to qualitative coding, a fundamental step in qualitative analysis. It explains the concept, differentiates between deductive and inductive coding approaches, and outlines the coding process, including initial coding and line-by-line coding. The script also introduces various coding methods and emphasizes the importance of aligning coding with research aims and questions, ultimately leading to a more systematic and transparent analysis.

Takeaways

• 📚 Qualitative coding is essential for dissertations, theses, and research projects, aiding in categorizing data extracts for later analysis.
• 🔍 Qualitative coding involves creating and assigning codes to describe data, making it easier to identify themes and patterns.
• 🧠 There are two main coding approaches: deductive (using pre-established codes) and inductive (creating codes based on the data).
• 🔄 A hybrid coding approach combines both deductive and inductive methods, starting with pre-established codes and adding new ones from the data.
• 📝 Initial coding involves getting a general overview of the data and assigning broad, rough codes.
• 📄 Line-by-line coding delves deeper into the data, refining and expanding codes to capture more detail and richness.
• 🔑 Five common coding methods are in vivo coding (using participants' own words), process coding (action-based codes), descriptive coding (summarizing with single words), structural coding (labeling data structure), and values coding (coding based on participants' worldviews).
• 🗂️ After coding, categorizing codes into groups helps organize data and identify themes for analysis.
• 🧩 Moving from coding to analysis involves code categorization and theme identification, essential for drawing meaningful insights from the data.
• 💡 Tips for effective coding include planning your steps, using a detailed codebook, keeping track of code meanings, staying aligned with research aims and questions, and ensuring consistency among multiple coders.

Q & A

What is qualitative coding?

Qualitative coding is the process of creating and assigning codes to categorize data extracts, which helps in deriving themes and patterns for qualitative analysis.

Why is coding important in qualitative research?

Coding is important because it ensures that the data analysis is systematic and transparent, which validates the research process and makes the findings reviewable by other researchers.

What are the two main approaches to qualitative coding?

The two main approaches are deductive coding, which uses pre-established codes, and inductive coding, which creates codes based on the data itself.

Can you combine deductive and inductive coding approaches?

Yes, you can combine both approaches in a hybrid coding method, starting with a set of predetermined codes and adding new codes as they emerge from the data.

What is the initial coding stage?

The initial coding stage involves getting a general overview of the data, developing an initial set of codes, and assigning broad codes to data extracts.

What are some common methods used in initial coding?

Common methods include in vivo coding, process coding, descriptive coding, structural coding, and value coding.

What is line-by-line coding?

Line-by-line coding involves reviewing data line by line, refining and expanding codes to capture as much richness from the data as possible.

Why should you avoid automated coding software?

Automated coding software cannot understand the subtleties of language and context, making human-based coding necessary for accurate analysis.

What is the purpose of code categorization?

Code categorization involves reviewing all the codes and creating categories to help organize the data, making it easier to identify connections and themes.

What should you consider when choosing a coding method?

When choosing a coding method, consider your research aims and questions, as they will guide the approach and ensure alignment with your overall research objectives.

Outlines

00:00

📚 Introduction to Qualitative Coding

This paragraph introduces the topic of qualitative coding, its importance for dissertation, thesis, or research projects, and the different approaches and methods used in coding data. Emma from Grad Coach TV welcomes viewers, explaining the value of qualitative coding in research and promoting related services offered by Grad Coach, such as one-on-one coaching and professional coding services.

05:02

🔍 Understanding Codes and Coding

This paragraph provides a basic definition of a code, explaining that it is a label describing a piece of content. It details how qualitative coding involves creating and assigning codes to categorize data extracts, which later help in deriving themes and patterns for qualitative analysis. The importance of systematic coding for ensuring data validity and transparency in research is highlighted.

10:06

🔄 Approaches to Coding: Deductive and Inductive

This paragraph discusses the two main coding approaches: deductive and inductive. Deductive coding uses pre-established codes based on research questions or previous studies, while inductive coding creates codes based on the data itself. The advantages and limitations of both approaches are explained, along with the possibility of using a hybrid approach combining both methods.

15:08

📝 The Coding Process: Initial and Line-by-Line Coding

This paragraph outlines the stages of the coding process: initial coding and line-by-line coding. Initial coding involves getting a general overview of the data and developing an initial set of codes. Line-by-line coding delves deeper into the data, refining and expanding the codes. It emphasizes the iterative nature of coding and the importance of meticulous work to ensure high-quality codes.

20:11

🧩 Methods of Initial Coding

This paragraph describes five common methods used in the initial coding stage: in vivo coding, process coding, descriptive coding, structural coding, and values coding. Each method is explained in detail, highlighting their specific uses and benefits in different research contexts. The importance of choosing the right method based on research aims and questions is stressed.

25:13

🧠 Moving from Coding to Analysis

This paragraph explains the transition from coding to qualitative analysis. It covers the initial steps of code categorization and theme identification, providing practical examples. The importance of asking analytical questions to gain insights from the data and the relevance of research aims and questions in guiding the analysis process is emphasized.

💡 General Tips for Successful Coding

This paragraph offers general tips for optimizing the coding process, such as planning steps, using detailed codebooks, tracking code meanings, avoiding directional drift, and ensuring consistency in research teams. It highlights the importance of aligning coding approaches with research aims and questions to achieve effective and systematic qualitative coding.

🎓 Conclusion and Additional Resources

This paragraph concludes the video, summarizing the importance of qualitative coding in research projects. It reiterates the influence of research aims and questions on coding approaches and methods. Viewers are encouraged to like, comment, and subscribe for more research-related content and are reminded of Grad Coach's private coaching services for personalized research assistance.

Keywords

💡Qualitative Coding

Qualitative coding is the foundational process in qualitative research that involves creating and assigning labels or codes to categorize data extracts. It is essential for systematically analyzing data and identifying themes and patterns. In the video, it is presented as the primary focus, with explanations of different coding approaches and methods provided to guide viewers through their research projects.

💡Deductive Coding

Deductive coding is one of the main coding approaches where researchers start with a set of pre-established codes based on their research questions or literature review. It allows for a focused analysis but may limit the discovery of new insights. The script uses the example of coding interview transcripts with predetermined codes like 'sushi', 'pizza', and 'burgers' to illustrate this approach.

💡Inductive Coding

Inductive coding is the opposite of deductive coding, where researchers begin without predetermined codes and develop them directly from the data. It is useful for exploring new ideas and creating new theories. The script mentions that in inductive coding, codes emerge from the data, such as when analyzing open-ended interview responses where the direction of the conversation is not predetermined.

💡Hybrid Approach

A hybrid approach in coding combines both deductive and inductive methods, allowing researchers to start with a priori codes and add new ones as they analyze the data. This approach is highlighted in the script as a flexible method that provides the benefits of both deductive and inductive coding, ensuring a thorough and rich analysis of qualitative data.

💡Initial Coding

Initial coding is the first stage of the coding process where researchers get a general overview of the data and develop an initial set of codes. The script explains that this stage can involve broad codes that are later refined during line-by-line coding, emphasizing the importance of understanding the data before categorizing it.

💡Line-by-Line Coding

Line-by-line coding is the second stage of the coding process where researchers delve deeper into the data, refining and expanding upon their codes. The script describes this as a meticulous process where each line of data is carefully reviewed to ensure a detailed and thorough understanding, which is crucial for high-quality analysis.

💡In Vivo Coding

In vivo coding is a method where researchers use the participants' own words as codes, avoiding interpretation and staying close to the original data. The script explains its usefulness, especially in cross-cultural research, with an example of how different cultures perceive time, illustrating the importance of in vivo coding in maintaining the authenticity of the data.

💡Process Coding

Process coding involves using action-based codes that indicate movement or procedure, often represented by gerunds. The script describes its utility in identifying non-verbal actions that are important for understanding the text's meaning, such as coding actions like 'describing a panda' or 'arguing with a relative'.

💡Descriptive Coding

Descriptive coding is a method that uses single words to summarize the general idea of the data extracts. The script mentions its effectiveness in quickly referring to content, especially useful for non-text data forms like videos or images, and for organizing large datasets by topic areas.

💡Structural Coding

Structural coding involves labeling and describing the structural attributes of the data, such as 'who', 'what', 'where', and 'how'. The script explains its utility in quickly accessing segments of data, particularly useful for large datasets like collections of dissertations or open-ended survey questions.

💡Values Coding

Values coding focuses on coding excerpts that relate to participants' worldviews, values, attitudes, and beliefs. The script illustrates its application by highlighting instances where participants express personal sentiments, such as 'I feel' or 'I think', which provide insight into their values and are crucial for research aiming to explore cultural values and interpersonal experiences.

Highlights

Introduction to qualitative coding as an essential first step in qualitative analysis.

Explanation of qualitative coding as the process of creating and assigning codes to categorize data extracts.

The importance of coding for ensuring data validity and analysis transparency in research.

Differentiation between deductive and inductive coding approaches.

Description of deductive coding using pre-established codes based on research questions or literature review.

Inductive coding as starting with a blank canvas and creating codes based on the data itself.

The hybrid approach to coding, combining both deductive and inductive methods.

Initial coding stage involving getting an overview of data and developing initial codes for inductive approaches.

Line-by-line coding for a deeper analysis and formalization of codes.

Avoidance of automated coding software in favor of human-based coding for understanding subtleties of language and context.

Introduction of five common coding methods: in vivo, process, descriptive, structural, and values coding.

In vivo coding using participants' own words to avoid interpretation errors.

Process coding with action-based codes to indicate movement or procedure within the data.

Descriptive coding to summarize data extracts with a single word or phrase.

Structural coding for labeling specific structural attributes of the data.

Values coding to focus on participants' worldviews, values, attitudes, and beliefs.

Combining coding methods for a comprehensive initial coding stage.

The iterative nature of coding and the importance of refining codes during line-by-line coding.

Transitioning from coding to qualitative analysis with steps including code categorization and theme identification.

General tips for optimizing the coding process, including planning, consistency, and teamwork.

Transcripts

In this video, we are going to dive into the  topic of qualitative coding which you will  

need to understand if you plan to undertake  qualitative analysis for any dissertation,  

thesis or research project. We will  explain what exactly qualitative coding is,  

the different coding approaches and methods and  how to go about coding your data step by step. So,  

go ahead, grab a cup of coffee, grab a cup of tea  or whatever works for you and let us jump into it.

Hey, welcome to Grad Coach TV where we demystify  and simplify the oftentimes intimidating world of  

academic research. My name is Emma, and today  we are going to explore qualitative coding,  

an essential first step in qualitative analysis.  If you would like to learn more about qualitative  

analysis or research methodology in general we  have also got videos covering those topics so  

be sure to check them out. I will include the  links below. if you are new to Grad Coach TV  

hit that subscribe button for more videos covering  all things research-related. Also, if you are  

looking for hands-on help with your qualitative  coding check out our one on one coaching services  

where we hold your hand through the coding  process step by step. Alternatively,  

if you are looking to fast track your coding  we also offer a professional coding service  

where our seasoned qualitative experts code  your data for you ensuring high-quality  

initial coding. If that sounds interesting  to you, you can learn more and book a free  

consultation at gradcoach.com. All right,  with that out of the way let us get into it.

To kick things off let us start by understanding  what a code is. At the simplest level, a code is  

a label that describes a piece of content. For  example, in the sentence pigeons attacked me  

and stole my sandwich you could use pigeons as  a code. This code would simply describe that the  

sentence involves pigeons. Of course, there are  many ways you could code this and this is just  

one approach. We will explore the different ways  in which you can code later in this video. So,  

qualitative coding is simply the process of  creating and assigning codes to categorize  

data extracts. You will then use these codes  later down the road to derive themes and  

patterns for your actual qualitative analysis. For  example, thematic analysis or content analysis.  

It is worth noting that coding and analysis can  take place simultaneously. In fact, it is pretty  

much expected that you will notice some themes  emerge while you code. That said, it is important  

to note that coding does not necessarily involve  identifying themes instead it refers to the  

process of labelling and grouping similar types of  data which in turn will make generating themes and  

analysing the data more manageable. You might be  wondering then why should I bother with coding at  

all why not just look for themes from the outset?  Well, coding is a way of making sure your data  

is valid. In other words, it helps ensure that  your analysis is undertaken systematically and  

that other researchers can review it. In the world  of research, we call this transparency. In other  

words, coding is the foundation of high-quality  analysis which makes it an essential first step.

Right, now that we have got a plain language  definition of coding on the table the next step  

is to understand what types of coding exist.  Let us start with the two main approaches,  

deductive and inductive coding. With deductive  coding, you as the researcher begin with a set of  

pre-established codes and apply them to your data  set. For example, a set of interview transcripts.  

Inductive coding on the other hand works in  reverse as you start with a blank canvas and  

create your set of codes based on the data itself.  In other words, the codes emerge from the data.  

Let us take a closer look at both of  these approaches. With deductive coding,  

you will make use of predetermined codes also  called a priori codes which are developed  

before you interact with the present  data. This usually involves drawing up  

a set of codes based on a research question or  previous research from your literature review.  

You could also use an existing code set from  the codebook of a previous study. For example,  

if you were studying the eating habits of college  students you might have a research question along  

the lines of what foods do college students eat  the most? As a result of this research question,  

you might develop a code set that includes  codes such as sushi, pizza and burgers.  

You would then code your data set using only  these codes regardless of what you find in the  

data. On the upside the deductive approach  allows you to undertake your analysis with  

a very tightly focused lens and quickly identify  relevant data, avoiding distractions and detours.  

The downside of course is that you could  miss out on some very valuable insights as  

a result of this tight predetermined focus.  Now, let us look at the opposite approach,  

inductive coding. As I mentioned earlier this  type of coding involves jumping right into the  

data without predetermined codes and developing  the codes based on what you find within the data.  

For example, if you were to analyse a set of  open-ended interview question responses you  

would not necessarily know which direction  the conversation would flow. If a conversation  

begins with a discussion of cats it might go on to  include other animals too. And so, you would add  

these codes as you progress with your analysis.  Simply put with inductive coding you go with the  

flow of the data. Inductive coding is great when  you are researching something that is not yet well  

understood because the coding derived from the  data helps you explore the subject. Therefore  

this approach to coding is usually adopted when  researchers want to investigate new ideas or  

concepts or when they want to create new theories.  So, as you can see the inductive and deductive  

approaches represents two ends of a spectrum  but this does not mean that they are mutually  

exclusive. You can also take a hybrid approach  where you utilize a mix of both. For example,  

if you have got a set of codes you have derived  from a literature review or a previous study,  

in other words, a deductive approach but you still  do not have a rich enough code set to capture the  

depth of your qualitative data you can combine  deductive and inductive approaches which  

we call a hybrid approach. To adopt a hybrid  approach you will begin your analysis with a  

set of a priori codes, in other words, a deductive  approach and then add new codes, in other words,  

an inductive approach as you work your way through  the data. Essentially, the hybrid coding approach  

provides the best of both worlds which is why  it is pretty common to see this in research.  

All right, now that we have covered what  qualitative coding is and the overarching  

approaches let us dive into the actual coding  process and look at how to undertake the coding.

So, let us take a look at the actual coding  process step by step. Whether you adopt an  

inductive or deductive approach your coding will  consist of two stages, initial coding and line  

by line coding. In the initial coding stage the  objective is to get a general overview of the  

data by reading through and understanding  it. If you are using an inductive approach  

this is also where you will develop an initial set  of codes. Then in the second stage line-by-line  

coding you will delve deeper into the data and  organize it into a formalized set of codes.  

Let us take a look at these stages  of qualitative coding in more detail.

Stage one, initial coding. The first step of the  coding process is to identify the essence of the  

text and code it accordingly. While there are many  qualitative analysis software options available  

you can just as easily code text-based data using  Microsoft Word's comments feature. In fact, if it  

is your first time coding it is oftentimes best  to just stick with Word as this eliminates the  

additional need to learn new software. Importantly  you should avoid the temptation of any sort of  

automated coding software or service. No matter  what promises they make automated software simply  

cannot compare to human-based coding as it cannot  understand the subtleties of language and context.  

Do not waste your time with this. In all  likelihood, you will just end up having to recode  

everything yourself anyway. Okay, so let us take a  look at a practical example of the coding process.  

Assume you had the following interview data  from two interviewees, in the initial stage  

of coding you could assign the code of pets or  animals. These are just initial fairly broad  

codes that you can and will develop and refine  later. In the initial stage broad rough codes  

are fine they are just a starting point which  you will build onto later when you undertake  

line by line coding. So, at this stage, you are  probably wondering how to decide what codes to use  

especially when there are so many ways to  read and interpret any given sentence. Well,  

there are a few different coding methods you can  adopt and the right method will depend on your  

research aims and research questions. In other  words, the way you code will depend on what you  

are trying to achieve with your research. Five  common methods utilized in the initial coding  

stage include in vivo coding, process coding,  descriptive coding, structural coding and  

value coding. These are not the only methods  available but they are a useful starting point.  

Let us take a look at each of them to understand  how and when each method could be useful.

Method number one in vivo coding. When you use  in vivo coding you make use of a participant's  

own words rather than your interpretation of the  data. In other words, you use direct quotes from  

participants as your codes. By doing this you will  avoid trying to infer meaning by staying as close  

to the original phrases and words as possible. In  vivo coding is particularly useful when your data  

are derived from participants who speak different  languages or come from different cultures.  

In cases like these, it is often difficult to  accurately infer meaning thanks to linguistic  

and or cultural differences. For example,  English speakers typically view the future  

as in front of them and the past as behind them  however this is not the same in all cultures.  

Speakers of Aymara view the past as in front  of them and the future as behind them. Why,  

because the future is unknown it must be out of  sight or behind them. They know what happened  

in the past so their perspective is that it  is positioned in front of them where they can  

see it. In a scenario like this one, it is not  possible to derive the reason for viewing the  

past as in front and the future as behind without  knowing the Aymara culture's perception of time.  

Therefore, in vivo coding is particularly  useful as it avoids interpretation errors.  

While this case is a unique one it illustrates  the point that different languages and cultures  

can view the same things very differently  which would have major impacts on your data.

Method number two, process coding. Next  up there is process coding which makes  

use of action-based codes. Action-based  codes are codes that indicate a movement  

or procedure. These actions are often indicated by  gerunds that are words ending in ing. For example,  

running, jumping or singing. Process coding  is useful as it allows you to code parts of  

data that are not necessarily spoken but that  are still important to understand the meaning  

of the texts. For example, you may have action  codes such as describing a panda, singing a song  

or arguing with a relative. Another example would  be if a participant were to say something like  

I have no idea where she is. A sentence like  this could be interpreted in many different ways  

depending on the context and movements of the  participant. The participant could for example  

shrug their shoulders which would indicate  that they genuinely do not know where the girl  

is. Alternatively, they could wink suggesting  that they do actually know where the girl is.  

Simply put, process coding is useful as it allows  you to in a concise manner identify occurrences in  

a set of data that are not necessarily spoken  and to provide a dynamic account of events.

Method number three, descriptive coding.  Descriptive coding is a popular coding method that  

aims to summarize extracts by using a single word  that encapsulates the general idea of the data.  

These words will typically describe the data in  a highly condensed manner which allows you as  

the researcher to quickly refer to the content.  For example, a descriptive code could be food  

when coding a video clip that involves a group  of people discussing what they ate throughout  

the day, or cooking, when coding an image showing  the steps of a recipe. Descriptive coding is very  

useful when dealing with data that appear in forms  other than text. For example, video clips, sound  

recordings or images. It is also particularly  useful when you want to organize a large data  

set by topic area. This makes descriptive coding  a popular choice for many research projects.

Method number four, structural coding. True to  its name structural coding involves labelling and  

describing specific structural attributes of the  data. Generally, it includes coding according to  

answers of the questions of who, what, where and  how rather than the actual topics expressed in the  

data. For example, if you were coding a collection  of dissertations which would be quite a large data  

set, structural coding might be useful as you  could code according to different sections within  

each of these documents. Coding what centric  labels such as hypotheses, literature review  

and methodology would help you to efficiently  refer to sections and navigate without having  

to work through sections of data all over again.  So, structural coding is useful when you want to  

access segments of data quickly and it can help  tremendously when you are dealing with large data  

sets. Structural coding can also be useful for  data from open-ended survey questions. This data  

may initially be difficult to code as they lack  the set structure of other forms of data such as  

an interview with a strict closed set of questions  to be answered. In this case, it would be useful  

to code sections of data that answer certain  questions such as who, what, where and how.

Method number five, values coding. Last  but not least values-based coding involves  

coding excerpts that relate to the participants'  worldviews. Typically this type of coding focuses  

on excerpts that provide insight regarding the  values, attitudes and beliefs of the participants.  

In practical terms this means you would be looking  for instances where your participants say things  

like I feel, I think that I need and it is  important that as these sorts of statements  

often provide insight into their values,  attitudes and beliefs. Values coding is therefore  

very useful when your research aims and research  questions seek to explore cultural values and  

interpersonal experiences and actions or when you  are looking to learn about the human experience.

All right, so we have looked at  five popular methods that can  

be used in the initial coding stage. As I  mentioned this is not a comprehensive list  

so if none of these sound relevant to your project  be sure to look up alternative coding methods  

to find the right fit for your research aims.  The five methods we have discussed allow you to  

arrange your data so that it is easier to navigate  during the next stage, line-by-line coding. While  

these methods can all be used individually it is  important to know that it is possible and quite  

often beneficial to combine them. For example,  when conducting initial coding with interview data  

you could begin by using structural coding to  indicate who speaks when. Then as a next step,  

you could apply descriptive coding so that you  can navigate to and between conversation topics  

easily. As with all design choices, the right  method or combination of methods depends on your  

research aims and research questions. So, think  carefully about what you are trying to achieve  

with your research then select the method  or methods that make sense in light of that.

So to recap, the aim of initial coding is to  understand and familiarize yourself with your data  

to develop an initial code set if  you are taking an inductive approach  

and to take the first shot at  coding your data. Once that is done  

you can move on to the next stage,  line by line coding. Let us do it.

Stage two, line by line coding. Line by line  coding is pretty much exactly what it sounds like  

reviewing your data line by line, digging deeper,  refining your codes and assigning additional  

codes to each line. With line-by-line coding, the  objective is to pay close attention to your data  

to refine and expand upon your coding especially  when adopting an inductive approach. For example,  

if you have a discussion of beverages and you  previously just coded this as beverages you could  

now go deeper and code more specifically, such  as coffee, tea and orange juice. The aim here is  

to scratch below the surface. This is the time to  get detailed and specific so that you can capture  

as much richness from the data as possible. In the  line-by-line coding process, it is useful to code  

as much data as possible even if you do not think  you are going to use it. As you go through this  

process your coding will become more thorough  and detailed and you will have a much better  

understanding of your data as a result of this.  This will be incredibly valuable in the analysis  

phase so do not cut corners here. Take your time  to work through your data line by line and apply  

your mind to see how you refine your coding as  much as possible. Keep in mind that coding is an  

iterative process which means that you will move  back and forth between interviews or documents  

to apply the codes consistently throughout your  data set. Be careful to clearly define each code  

and update previously coded excerpts if you  adjust or update the definition of any code  

or if you split any code into narrower codes.  Line by line coding takes time so do not rush it,  

be patient and work through your data meticulously  to ensure you develop a high-quality code set.

Stage three, moving from coding to analysis.  Once you have completed your initial and  

line by line coding the next step is to start  your actual qualitative analysis. Of course,  

the coding process itself will get you in  analysis mode and you will probably already have  

some insights and ideas as a result of it so you  should always keep notes of your thoughts as you  

work through the coding process. When it comes to  qualitative data analysis there are many different  

methods you can use including content analysis,  thematic analysis and discourse analysis. The  

analysis method you adopt will depend heavily  on your research aims and research questions.  

We cover qualitative analysis methods on the  Grad Coach blog so we are not going to go down  

that rabbit hole here but we will discuss the  important first steps that build the bridge  

from qualitative coding to qualitative analysis.  So, how do you get started with your analysis?  

Well, each analysis will be different but it is  useful to ask yourself the following more general  

questions to get the wheels turning. What actions  and interactions are shown in the data, what are  

the aims of these interactions and excerpts,  how do participants interpret what is happening  

and how do they speak about it, what does their  language reveal, what are the assumptions made by  

the participants, what are the participants  doing, why do I want to learn about this,  

what am I trying to find out? As with initial  coding and line by line coding your qualitative  

analysis can follow certain steps. The first  two steps will typically be code categorization  

and theme identification. Let us look at these two  steps. Code categorization which is the first step  

is simply the process of reviewing everything you  have coded and then creating categories that can  

be used to guide your future analysis. In other  words, it is about bundling similar or related  

codes into categories to help organize your data  effectively. Let us look at a practical example.  

If you were discussing different types of animals  your codes may include dogs, llamas and lions. In  

the process of code categorization, you could  label in other words, categorize these three  

animals as mammals whereas you could categorize  flies, crickets and beetles as insects.  

By creating these code categories you will  be making your data more organized as well as  

enriching it so that you can see new connections  between different groups of codes. Once you have  

categorized your codes you can move on to the next  step which is to identify the themes in your data.  

So, let us look at the theme identification step.  From the coding and categorization processes,  

you will naturally start noticing themes  therefore the next logical step is to identify  

and clearly articulate the themes in your  data set. When you determine themes you will  

take what you have learned from the coding  and categorization stages and synthesize  

it to develop themes. This is the part of the  analysis process where you will begin to draw  

meaning from your data and produce a narrative.  The nature of this narrative will, of course,  

depend on your research aims, your research  questions and the analysis method you have chosen,  

for example, content analysis or thematic  analysis. So, keep these factors front of  

mind as you scan for themes as they will  help you stay aligned with the big picture.

All right, now that we have covered both  the what and the how of qualitative coding  

I want to quickly share some general tips and  suggestions to help you optimize your coding  

process. Let us rapid-fire. One, before you  begin coding plan out the steps you will take  

and the coding approach and method or methods you  will follow to avoid inconsistencies. Two, when  

adopting a deductive approach it is best to use a  codebook with detailed descriptions of each code  

right from the start of the coding  process. This will ensure that you apply  

codes consistently based on their descriptions  and will help you keep your work organized. Three,  

whether you adopt an inductive or deductive  approach keep track of the meanings of your  

codes and remember to revisit these as you go  along. Four, while coding keep your research aims,  

research questions, coding methods and analysis  method front of mind. This will help you to avoid  

directional drift which happens when coding is  not kept consistent. Five, if you are working in a  

research team with multiple coders make sure that  everyone has been trained and clearly understands  

how codes need to be assigned. If multiple coders  are pulling in even slightly different directions  

you will end up with a mess that needs  to be redone, you do not want that. So,  

keep these five tips in mind and you will  be on the fast track to coding success.

And there you have it qualitative coding in a  nutshell. Remember, as with every design choice  

in your dissertation, thesis or research project  your research aims and research questions will  

have a major influence on how you approach the  coding. So, keep these two elements front of mind  

every step of the way and make sure your  coding approach and methods align well.  

If you enjoyed the video hit the like button  and leave a comment if you have any questions.  

Also, be sure to subscribe to the channel for  more research-related content. If you need a  

helping hand with your qualitative coding or  any part of your research project remember  

to check out our private coaching service  where we work with you on a one-on-one basis,  

chapter by chapter to help you craft a winning  piece of research. If that sounds interesting  

to you book a free consultation with a friendly  coach at gradcoach.com. As always I will include  

a link below. That is all for this episode  of Grad Coach TV. Until next time, good luck.