Blended Learning

Friday, 24 January 2025

Qualitative Data Analysis (Qualitative Research)




Source: 4.3 Qualitative Research Methodologies – An Introduction to Research Methods for Undergraduate Health Profession Students



Renata Tesch's book "Qualitative Research: Analysis Types and Software Tools" is a foundational text that explores various qualitative research methodologies and the software tools available to assist researchers.

Key Analysis Types:

  1. Ethnography: Immersive research to understand cultures and communities.

  2. Phenomenology: Exploring individuals' lived experiences.

  3. Grounded Theory: Generating theory from data.

  4. Case Study: In-depth examination of a single case or a few cases.

  5. Narrative Research: Analyzing personal stories.

  6. Content Analysis: Systematic coding and categorizing of textual or visual data.

  7. Discourse Analysis: Examining language in social contexts.

  8. Action Research: Collaborative problem-solving with participants.

Software Tools:

  1. NVivo: For organizing, coding, and visualizing qualitative data.

  2. MAXQDA: For comprehensive data analysis and visualization.

  3. ATLAS.ti:  For analyzing complex qualitative data.

  4. Dedoose: Web-based tool for mixed-methods research.

  5. Quirkos: User-friendly tool for visual coding and analysis.

These tools and approaches provide researchers with robust frameworks and techniques for conducting in-depth qualitative studies.

Qualitative Data Analysis (QDA)

Qualitative Data Analysis (QDA) is a method used in social sciences and humanities to analyze non-numerical data. This type of data is typically gathered from interviews, focus groups, observations, and text analysis. QDA allows researchers to understand themes, patterns, and meanings within the data, providing insights into people's behaviors, experiences, and interactions.

Here are some key steps in qualitative data analysis:

  1. Data Collection: Gather data through various methods such as interviews, observations, and document analysis.

  2. Data Transcription: Convert audio or video recordings into written form to facilitate detailed examination.

  3. Data Coding: Identify and label important sections of the data, creating categories or themes.

  4. Theme Development: Group similar codes together to develop overarching themes that capture the essence of the data.

  5. Interpretation: Analyze the themes to understand the underlying meanings and patterns, and relate them to the research questions.

  6. Reporting: Present the findings in a structured manner, often with supporting quotes from the data to illustrate key points.

QDA is a powerful tool for exploring complex social phenomena, providing rich, in-depth insights that quantitative methods may overlook. 

1. Introduction to Qualitative Research

2. Approaches to Qualitative Research

3. Qualitative Data Analysis Process & Steps

4. Tips for Conducting Effective Qualitative Data Analysis

5. Issues and Challenges in Conducting Effective Qualitative Data Analysis

6. Online Tools for Qualitative Data Analysis

7. Books and Sources on Qualitative Research

7A. Qualitative Research: Essence, Types, and Advantages

    Qualitative Research: Essence, Types, and Advantages (pdf)

8. Qualitative Research Methodologies (James Cook University, Australia)

9. Qualitative Data Analysis (James Cook University, Australia)

10. Qualitative Research (Creswell)

11. Educational Research: Innovative Ways of Researching

12. 14 Review Types

13. Qualitative Data Analysis (101 Tutorials) - 6 Analysis Methods

14. Assessments

a) Learn to Learn Competency

b) Language Proficiency Self Assessment

c) Self Evaluate Your Language Skills

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