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Qualitative Data Analysis Method for Phenomenological Research

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Qualitative Data Analysis Method for Phenomenological Research

A phenomenological research design serves as an effective means of exploring students’ lived experiences. This is particularly so when the focus is on students with disabilities and school disciplinary practices. The selection of an appropriate data analysis method constitutes an important aspect of this research design: Qualitative Data Analysis Method for Phenomenological Research.

This article will investigate the methodology utilized in the data analysis of a phenomenological study and show an applied coding example of it. Besides, it will also look at the comparative advantages of doing it manually as opposed to software.

Proposed Data Analysis Method and Alignment with Research Design

Braun and Clarke’s Reflexive Thematic Analysis (RTA) is the most appropriate analysis for this phenomenological study. The designer adopts a modern-day approach that aligns well with the aim of the research design. The research design aims to uncover the essence of students with disabilities’ lived experiences about disciplinary practices. Reflexive TA techniques utilize subjectivity as a research resource while denouncing positivist notions of researcher “bias” and recognizing that qualitative analysis is always interpretative by nature (Braun & Clarke, 2022).

The six-phase procedure of reflexive thematic analysis consists of (1) becoming familiar with the data, (2) generating initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) writing the report (Braun & Clarke, 2006). The method emphasizes researcher reflexivity, meaning essentially that the meaning in the data is not fixed but is constructed through the researcher’s inferential engagement (Naeem et al., 2023). RTA is often used in health studies and education to develop themes from qualitative data. It allows researchers to investigate complex experiential phenomena while being methodologically rigorous (Braun & Clarke, 2024).

This analytical approach has various benefits for the proposed study. It sticks with the idea of using subjective experiences to understand why they seem to offset each other. Additionally, the reflexive nature of the approach acknowledges the role of the researcher in the making of meaning, which is particularly important in the case of the sensitive topic of disciplinary experiences.

In addition, focusing on the depth of the interpretation rather than counting the frequency conforms to the phenomenological principle with respect to the emphasis on the meaning and not measure. In addition, a flexible theoretical positioning in reflexive TA allows researchers to work on their data from differing epistemologies with analytical consistency.

However, challenges can be associated with undertaking this reflexive thematic analysis. The interpretative nature of the research process calls for thoughtful attention to methodological coherence. Researchers must ensure that theories, analytical techniques, and quality criteria align with one another.

In addition, focusing on researcher reflexivity requires a continuous questioning of assumptions and positioning—a challenge, especially when studying the experiences of marginalized people. The method requires significant time for extensive data engagement, especially in educational research projects it may present practical limitations.

Coding Example: Application to Conversational Data

To show how RTA works in practice, the following example shows the coding process using a fictitious participant reflection from the proposed study.

“When I got suspended for three days, I felt like everyone was staring at me when I came back. The teacher didn’t even ask why I was upset in class—she just sent me to the office. It made me feel like my disability doesn’t matter, like they see me as just a troublemaker.

I started thinking maybe I don’t belong in regular classes. Now I’m always worried about getting in trouble again, even when I’m just trying to participate.”

Phase 1: Familiarization with Data

The initial reading shows themes of social stigma, institutional misunderstanding of disability-related behavior, trouble with identity, and ongoing anxiety about future education participation.

Phase 2: Generating Initial Codes

Phase 3: Searching for Themes

These codes cluster around broader thematic areas: experiences of social alienation following disciplinary action, institutional failure to recognize disability-related needs, negative identity construction through disciplinary encounters, and the creation of ongoing educational anxiety.

Phase 4: Reviewing Themes

The identified approaches are coherent and distinct, and they capture the complexity of the experience. The themes show how ways of disciplining mix with a disability identity to create different educative marginalizations.

This illustration indicates how RTA moves systematically from data collection to meanings with an ongoing connection back to participants’ lived experiences and the researcher’s active and involved role in the construction of themes.

Manual Coding versus Software-Assisted Analysis

The comparison between manual coding and software-assisted analysis using NVivo reveals both similarities and distinctions that influence methodological decision-making in RTA. Both types of thematic analysis require researchers to systematically engage with data, follow a particular methodology framework, and interpret participants’ meanings (Braun & Clarke, 2022).

Similarities between Approaches

Coding, whether done manually or with the help of software, requires knowledge about the data, a consistent application of the procedures, and an ongoing reflexive engagement with the interpretations. Also, both strategies involve a close adherence to methodological concordance and transparency in analysis. The software can allow the researcher to be more creative thanks to efficient data management, thus relieving the researcher of the mechanical support found in regular manual analysis systems.

Distinctions and Advantages

There are many other benefits of NVivo over manual analysis, including better organization of data and easy retrieval. The software helps manage many sources of data and allows for complex queries and visualization tools that show patterns that humans may miss. In addition, the systematic management of data on NVivo guarantees the accuracy of qualitative research and a transparent audit trail (Kiger & Varpio, 2020). When triangulating on interviews and reflective journals, it is useful to have multiple data in one project and have it coded in one software program.

Moreover, not all software packages are conducive to reflexive thematic analysis. Some criticize that using features like automated queries can create a distance between the researcher and the context of the data. This can affect the quality of phenomenological research. Furthermore, too much reliance on software functions may lead to mechanical coding approaches that counter reflexive principles of thematic analysis today.

Preference and Justification

For this phenomenological study, the use of a hybrid approach with the first manual engagement and the second computer engagement is most appropriate. To begin the analytical process, I would undertake manual reading and initial coding in order to become intimately familiar with the lived experiences of participants and to remain phenomenologically sensitive to the contexts of lived experiences. According to NVivo, this would enhance organization, facilitate systematic comparisons across participants, and allow data merging from the triangulation approach.

This preference is due to the awareness that RTA requires both interpretive depth and systematic rigor. Making contact manually ensures that researchers’ interactions with participant voices are primary and reflexive, while software support provides the organizational infrastructure requisite for credible analysis of complex educational data involving vulnerable populations. Building on the interpretive sensitivity necessary for phenomenological research, this approach employs technology to improve analytical transparency and methodological coherence.

Conclusion

Braun and Clarke’s reflexive thematic analysis is ideal for exploring how students with disabilities experience school discipline because it is theoretically underpinned and has systematic yet flexible analytic procedures. The focus of the method on the reflexivity of the researcher and interpretive engagement fits with phenomenology’s commitments and offers methodological rigor. The proposed hybrid method of coding provides the interpretative depth necessary for an understanding of lived experience, along with the organizational benefits of contemporary software for qualitative data analysis, thus satisfying the philosophical demands of phenomenological research and the practical requirements of qualitative research.

References

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE.

Braun, V., & Clarke, V. (2024). Supporting best practice in reflexive thematic analysis reporting in palliative medicine: A review of published research and introduction to the Reflexive Thematic Analysis Reporting Guidelines (RTARG). Palliative Medicine, 38(6), 608–616. https://doi.org/10.1177/02692163241234800

Kiger, M. E., & Varpio, L. (2020). Thematic analysis of qualitative data: AMEE Guide no. 131. Medical Teacher, 42(8), 846–854. https://www.tandfonline.com/doi/abs/10.1080/0142159X.2020.1755030

Naeem, M., Ozuem, W., Howell, K. E., & Ranfagni, S. (2023). A step-by-step process of thematic analysis to develop a conceptual model in qualitative research. International Journal of Qualitative Methods, 22(1), 1–18. Sagepub. https://doi.org/10.1177/16094069231205789

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Question 

Rashonda Straite

National University

EDR 8400: Qualitative Research

Assignment 4: Determine a Method to Analyze Qualitative Data

In the Spotlight on Skills section of this lesson you are provided with an explanation of how to structure a presentation. Remember, slides are visual aids to support what you would say during a presentation. This resource will help you to compose your slides in a way that effectively balances visuals and text.

You have covered a lot of material these past 4 lessons.  Now, you have an opportunity to demonstrate your knowledge of qualitative methodology and designs.

For this lesson’s assignment, you will consider a data analysis method that aligns with the qualitative research design for a potential study that you proposed in Lesson 2. Address each of the following three prompts as an essay or presentation:

Length: If you choose to write an essay, this assignment will be at least 2 pages.

Resources:

Required Resources

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