What is Data Analysis in Qualitative Research?

Data analysis in qualitative research is an iterative and complex process of systematically searching and arranging data to increase understanding of a phenomenon.

Data Analysis
Data Analysis

Data Analysis in Qualitative Research

Qualitative research is the research that is concerned with the opinions, ideas, events, and perceptions formed by a group of individuals, using several tools such as: (observation and interview) in order to reveal the reality and then analyze and interpret the data.

The qualitative researcher considers that the facts are multiple and not fixed and that knowledge is not independent of the human being, and therefore the research is affected by the researcher’s background from the beginning of the research until its end.

Qualitative Data Analysis Process

When the researcher conducts qualitative research, there are several important procedures that should be mentioned, which contribute to the quality of qualitative research, including clarifying how to analyze data and formulate results.

The analysis process is one of the most difficult stages in qualitative research, especially for the novice researcher, due to the presence of a large amount of data and the lack of fixed and specific models that are easy to refer to.

The process of analyzing qualitative data shows the researcher's creativity in interpreting the data, his ability to think critically, and his understanding of the subject of the study.

There is no single way to analyze qualitative data because the analysis process is affected by the researcher's perspective and his scientific and cultural background.

The analysis shows the researcher's ability to think and extract meaning from the data through critical reading and informing the researcher of theories and research on the problem being studied.

During the analysis process, one must immerse himself in reading so that the researcher becomes close to data that requires the ability to analyze with an open practical mindset. Because the results are not visible, but the researcher is the one who extracts them and then links them to the relevant theoretical concepts.

It is clear that the process of analysis in qualitative research is an organized process based on creativity and innovation.

What are the Steps of Qualitative Data Analysis?

Qualitative research goes through several steps and organized procedures that are linked to each other, including:

Organizing the data: where the researcher reads the texts and immerses himself in the details and tries to reach the essence of the data, using the written texts and field notes, and then examining them in order to build a meaning for the data.

Description and classification of codes: The essence of qualitative data lies here and researchers build a detailed description and then compose codes and present ideas. The researcher encodes the texts collected from interviews and observations.

Developing and evaluating explanations: The process of interpretation requires creativity and the ability to criticize and make judgments in order to extract what is behind the coding, and then develop it and organize the ideas. This is the most important step in the analysis of qualitative data, as it is possible to obtain feedback from colleagues about the initial data that has been interpreted, which helps in writing a final report for the research.

Data presentation: by using tables, figures or images, it contains texts and not numbers, so the type of data is chosen based on what answers the research questions, and then displays the quotations and interpretations of the researcher, whether using manual analysis or with the help of computer programs.

Principles of Qualitative Data Analysis

Language-based analysis: All qualitative data is converted into texts like transcripts of interviews. Being qualitative research based on words makes it a language-based analysis.

The iterative process: analysis in qualitative research is not an analysis that goes through a linear process, but rather depends on iteration and continuity between data collection, analysis, and interpretation.

It is possible to refer to data collected during the analysis process and to copy the original data during the encoding process.

A novice researcher should not collect a lot of data initially; So that he does not ignore some details during the analysis process because the most important thing is saturation, meaning that collecting other data does not add new information.

Stages of Qualitative Data Analysis

Data organization stage: It is the stage in which the researcher returns with a set of audio recordings, field notes, and many pages.

This stage requires the planning process and then organizing the data, which facilitates the analysis process.

It is necessary to deal in an orderly manner with the data and to ensure the information and the names of the participants in the research and the specific dates.

After that, the data is classified according to the participants in the study, tables are prepared, and aliases are given to the participants.

Transcript of the audio recordings of the interview: into paper and electronic files on a computer to facilitate handling.

Open coding: It is for the researcher to encode the initial data (interviews, field notes, etc..), which is the process of reading the data to search for specific topics. It is possible to encode a word, sentence, or part of large texts without being restricted to a specific theoretical point of view.

Classification of Codes: After the open coding stage, a long list of codes that need classification is produced. This stage needs to reduce the number of symbols, as the interconnected symbols that are related to the subject of the study are collected and the data is read repeatedly, and then the convergent symbols are collected and focus on the study goal during classification.

Axial coding: After classifying the symbols, the analysis process does not end because the pivot coding is based on finding relationships between the categories and then identifying the phenomena in the data and making it an axis with which the subcategories of symbols are linked.

Selective coding: It is the final stage and it is called selective because the codes chosen by the researcher answer the questions of the study where he puts what he deems appropriate in groups with a focus on what achieves the objectives of the study, and the researcher explains this in a logical manner in the study report.

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