Understanding Research Methodology

Introduction

• Overview of topics to be covered:
  • Definition of research methodology
  • Different research methods: qualitative, quantitative, and mixed methods
  • Sampling, data collection methods, and data analysis
  • Choosing the right research methodology
• Host: Derek
• Guest: Karen, an experienced researcher with various publications and a Ph.D.

What is Research Methodology?

• Definition: The "how" of research, describing how research activities are conducted.
• Importance: Follows the introduction and literature review chapters, clarifying how the research question will be addressed.
• Key components:
  • What data was collected
  • Source of data
  • How data was collected
  • How data was analyzed
• Methodology should be replicable by others.

Qualitative, Quantitative, and Mixed Methods

• Qualitative: Focuses on words and ideas; explores meanings and experiences.
• Quantitative: Involves numerical data; focuses on measurement and statistics.
• Mixed Methods: Combines both qualitative and quantitative approaches.
• Research Philosophies:
  • Positivist: Tests hypotheses using quantitative data.
  • Interpretivist: Generates theories from qualitative data.

Sampling

• Population: The entire group of interest (e.g., all South Africans).
• Sample: A subset of the population for study.
• Importance of sampling methods:
  • Probability Sampling: Random selection; aims for representativeness.
  • Non-Probability Sampling: Based on convenience; may not be representative.
• Understanding limitations of sampling approaches is crucial for validity.

Data Collection Methods

• Common methods:
  • Qualitative: Interviews, focus groups, document analysis, observations.
  • Quantitative: Surveys, measurements, structured questionnaires.
• The choice of method should always tie back to the research question.
• Practical considerations: access to participants, tools available, etc.

Data Analysis

• Qualitative Analysis:
  • Content analysis: Identifying themes and patterns.
  • Discourse analysis: Understanding communication dynamics.
  • Narrative analysis: Exploring personal stories and meanings.
• Quantitative Analysis:
  • Descriptive statistics: Summary of data (means, medians, etc.).
  • Inferential statistics: Relationships and comparisons (e.g., regression, ANOVA).
• Importance of knowing your data's characteristics before analysis.

Choosing the Right Research Methodology

• Begin with a clear research question.
• Consider the nature of the research: exploratory vs. confirmatory.
• Practical aspects: access to participants, budget constraints, etc.
• Iteration between title, question, aims, and methodology is important for coherence.

Conclusion

• Recap of topics discussed.
• Encouragement to explore further resources from Grad Coach.
• Invitation for questions and comments.