week 1 Introduction to Qualitative Research Methods

Introduction to Qualitative Research Methods

• Definition: Involves the collection of non-numerical data to understand concepts, experiences, or perceptions.

Quantitative Study

• Definition: Research that uses numbers as data and statistical analysis to measure relationships or differences between variables.
• Characteristics:
  • Objective data (e.g., scores, frequencies, percentages).
  • Large sample sizes (30 participants and above).
  • Structured methodology (surveys/control experiments).
  • Data analysis using statistical methods.
• Example Question: "How often do students use AI weekly?"

Qualitative Study

• Definition: Research involving the collection of data (words, observations) to understand context, experiences, or perceptions.
• Characteristics:
  • Subjective data (e.g., interviews, field notes).
  • Small sample sizes (10-20 participants).
  • Flexible approach (open-ended questions).
  • Analysis of words to understand meaning.
• Example Question: "How do rural students describe their first experience with AI?"

Quantitative Research Steps

1. Identify Topic
2. Read Literature Review
3. Build Hypothesis
4. Conduct Survey/Experiment
5. Test Hypothesis
6. Write Report

Qualitative Research Steps

1. Identify Topic
2. Build Research Questions
3. Conduct Interviews
4. Analyze Data (Identify themes)
5. Read Literature Review
6. Write Report

Theoretical Considerations

• Strengths and Weaknesses of Approaches:
  • Quantitative:
  • Strengths: Suitable for testing theories, structured and systematic.
  • Weaknesses: Limited to existing theories, less flexible in study approach.
  • Qualitative:
  • Strengths: More flexible, can generate new theories/assumptions.
  • Weaknesses: Less systematic, harder to prove theories.

Exploratory Research

• Definition: Research aiming to gain initial understanding and identify real issues for further research.
• Characteristics:
  • Conducted on new, poorly understood topics with little previous study.

Descriptive Research

• Purpose: Answers questions such as “what,” “who,” “when,” “where,” and “how,” but not “why.”
• Characteristics:
  • Flexible, open structure without strict guidelines.
  • Does not require hypothesis testing.
  • Often involves qualitative data collection methods (e.g., in-depth interviews, focus groups).
  • Inductive approach to understand new phenomena.

Explanatory Research

• Definition: Aimed at identifying causes, relationships, or effects between two or more variables.
• Characteristics:
  • Focuses on "why" and "how" phenomena occur.
  • Tests hypotheses based on empirical data.
  • Systematic design to reduce bias, typically using quantitative methods.
  • Deductive approach building from existing theory.

Comparative Research Approaches to AI Use Among Rural Students

• Exploratory Research:

  • Investigates awareness of AI among rural students.
  • Example Question: "Are rural students aware of ChatGPT?"
  • Flexible design, no initial hypothesis.

• Descriptive Research:

  • Analyzes the extent and frequency of AI use.
  • Example Question: "How often do rural students use AI for school work?"
  • Structured surveys or observations.

• Explanatory Research:

  • Investigates reasons for low AI usage (e.g., internet access, awareness).
  • Example Question: "Does lack of internet access hinder AI use?"
  • Employs experiments or statistical analysis and interviews with students/teachers.

Advantages of Qualitative Research

• In-depth Understanding: Allows researchers to gain insights into perceptions and experiences.
• Flexibility: Researchers can adjust questions during data collection without strict structure.
• Participant Voice: Enables participants to share their perspectives, often overlooked in quantitative studies.
• Exploration of Complex Phenomena: Ideal for topics that are underexplored or existing theories are inadequate.
• Rich Narrative Data: Provides thorough and deep understanding of "why" and "how" phenomena occur, rather than just "what".