If you are a researcher or a student seeking help on how to code qualitative data, this article will be of benefit to you. Coding is the process of organizing the collected data into segments of text before bringing meaning to the information. A code is, therefore, a word or phrase that symbolically assigns a meaning to textual or visual data. Coding qualitative data can be done manually or using computerized software programs such as Nvivo, Atlas, Maxqda, and Hyper RESEARCH, among others. Computerized programs are, however, more efficient than hand-coding in storing and locating qualitative data and are also effective when comparing different codes.

 

In a qualitative database, several code types are considered, including; setting and context codes, perspectives held by subjects, subjects’ ways of thinking, process codes, activity codes, strategy codes, relationship and social structure codes, and lifestyles and pre-assigned coding schemes. The process of developing codes could be emergent from information collected from participants, predetermined to only fit in data to them, or a combination of the emerging and predetermined codes. When using predetermined codes, you may develop a qualitative codebook.

 

A qualitative codebook is a record containing a list of predetermined codes that researchers use for coding data. In the codebook, you could include names of codes in one column, a definition of those codes in another column, and the specific instances in which the code is found in the transcripts in another column. Our company has the best academic writers who are equipped with knowledge and coding skills to help you meet your needs in coding qualitative data. We ensure to deliver our services with the utmost level of professionalism. If you face any challenges while coding your qualitative data, remember we have qualified data analysts who will be glad to assist you. Most graduate and Phd/doctoral students seek our help in coding data for their qualitative dissertations/theses.

 

Necessary Preparations Before Coding

The general procedure of coding textual data involves, reading all the transcriptions while jotting down ideas as they come to mind. You then pick the shortest document from your interviews and go through it to answer the question about what the interview is about. Write the thoughts of the underlying meaning of the information in the margin. Repeat the above step for several interviews and make a list of all the topics. Cluster the similar topics and form them into columns with sub-headings.

 

Once you have formulated the list, abbreviate the topics as codes while writing them next to the appropriate segments of the text in the collected data. Find descriptive wording for the topics to turn them into categories and reduce the total list of categories by grouping topics that are related. Then, make a final decision on the abbreviation for each category and assign alphabets to these categories. You should then gather the data material belonging to each category to perform a preliminary analysis and finally recode your data if need be. The categories are important in formatting data for computer-assisted qualitative data analysis software (CAQDAS) programs.

 

Writing Analytical Memos

An analytic memo is a site of written reflection and conversation with yourself about your data. The purpose of writing an analytic memo is to document and reflect on your coding process and the choices of your codes. It also documents how the process is taking shape, the emerging patterns, categories and subcategories, the themes, and concepts in your data, leading towards theory.

 

• The codes you write in the margins of your hardcopy data and listed in a CAQDAS file are just labels until they are analyzed. When writing analytic memos, you first reflect on your relation to the participants or phenomenon you are studying.
• Consider your study research questions, goals, and your purposes for the research study.
• Reflect, and write about your code choices and their definitions in operation.
• Fourthly, review and write on the patterns, themes, categories, and concepts that emerge;
• Note the possible networks among the codes, patterns, themes, categories, and concepts using drafted diagrams, among others.
• Reflect on emergent or related existing theory. You also reflect on any problems with the study and any personal or ethical issues with the research study, the future directions for the research study, and the analytic memos you have generated periodically through the analysis. Besides, it is important to reflect and write on the final report for the research study.

Making your Textual Data Manageable

This is the first step when beginning an analysis of your data before actual coding. In this step, you filter the parts of your text that you will include in your analysis and the parts you will not. To achieve this, you first state your research concern and the theoretical framework of your research study.

 

Stating the research concern of study helps you to focus on what you want to study and the reason you want to study it, hence, becoming a blueprint for making coding decisions. Research concerns should be relevant and related to your specific research study. Important information that could be omitted in this stage of stating your research concerns could come up in later stages of coding and be selected as the coding process proceeds.

 

To safeguard against missing important information that could be unexpected, have each transcript coded by more than one person and probably have a consultant, who is a member of the population you are studying to code the transcripts independently and then compare the data with your data.

You realize from the stated concerns that there will be repeating ideas which you then present to the participants of the research study to confirm if your understanding of their stories is correct. Presenting the repeating ideas to the participants helps you improve your understanding of the data.

In addition to the research concerns, you should state your theoretical framework in an organized and detailed manner. The theoretical framework helps you determine your biases and to remain objective as you read your textual data. You will have many ideas in the process of coding,  which you ought to record, for example, in a research journal or computer file.

 

Selecting Relevant Text for Further Analysis

All your transcripts should be filed on your computer. Read the raw data as you highlight the relevant ideas for your research study with the guidance of your research concern. If you are using hard copies of transcripts, the same process of reading through your textual data while highlighting relevant ideas still applies. Copy the highlighted texts into separate files, one for each individual or focus group, and save the files in a larger project folder. You then create a separate file for each transcript. Make a header, including the project, the group, the date you created the file, and the person who did the selection of the relevant ideas. You should record any analytic memos with the texts, including the speaker and the transcript page number. These detailed records of the transcripts help you coordinate input from stakeholders.

 

Organizing Relevant Texts to Repeating Ideas

When selecting relevant texts,  you realize that different research participants express the same idea using the same or similar words. These ideas expressed in similar words are referred to as repeating ideas and build the biases for a theoretical narrative. In this step, you reread your selected relevant texts to identify the repeating ideas in each transcript. Also, identify orphan texts, ideas that are too narrow, ideas that are too broad, or even if you have second thoughts about the relevant text you selected, and make necessary changes to obtain reasonable repeating ideas that are important for your study.

 

You then combine the repeating ideas from all the transcripts into a list for the whole research study sample. The ideas you come up with should be workable, usually between forty and eighty, depending on your cognitive style. Afterward, name your repeating ideas using short wordings that express the repeating idea.

 

The next step involves organizing repeating ideas into groups called themes. The repeating ideas are grouped according to their similarities, which provide the basis for the theme. Read through your repeating ideas as you assign each of them to themes. Change any list of repeating ideas that could be orphaned by including them into a theme or reorganizing your themes. You then identify the number of themes you have, usually recommended to be between ten and twenty, and name them. You may discuss the themes with a team before checking with a consultant who is not involved in the project.

 

Developing Theoretical Constructs

Theoretical constructs are groupings of organized themes that develop the analysis from the description of participants in repeating ideas and themes to a more abstract and theoretical view. To develop theoretical constructs, read through the themes as you group them into larger groups which form the theoretical constructs and name them. Verify with consultants and make changes from the feedback you receive.

 

Finally, you create a theoretical narrative using the theoretical constructs to describe the participants' experiences in a story that is real and vivid. The theoretical narrative begins by describing your research concerns. You then describe your first theoretical construct,  considering the research participants. The constructs are then broken down into themes using the language of the repeating ideas to make the participants experience real. You then present the narrative in the participants' words. Put the repeating ideas in quotes since they represent the participants' own words.

 

You then repeat the same for the other theme constructs to develop a theoretical narrative and finally present it in the third person. It is important for you to also test your findings for reliability, validity, and credibility. You can get high-quality qualitative data coding services from our experts; just join our live chat and we will guide you on how to proceed.

 

Summary

Coding is an important process for any qualitative analysis of a research study. It helps to organize textual research data into meaningful information that can be interpreted in the participants’ language. It involves stating your research concerns and theoretical framework, then selecting the relevant text for further analysis by reading and rereading through the raw textual data. Related relevant texts are then grouped to form repeating ideas. The repeating ideas are organized into themes (categories), which are then developed into theoretical constructs based on the theoretical framework. These theoretical constructs then form a theoretical narrative in the participants' original language.

 

Codes used for qualitative analysis could be emergent from the research data collected, predetermined, or a combination of both. In the case of predetermined codes, a qualitative codebook could be developed to provide the predetermined codes that researchers use for coding research data.

 

Coding can be done both manually or using computerized programs such as Nvivo, Atlas, and Maxqda, among others and it is important to test your findings after coding for reliability, validity, and credibility. If you are looking for a professional to help you with data coding, we will help you promptly.