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CHAPTER 5: RESEARCH DESIGN - Coggle Diagram
CHAPTER 5: RESEARCH DESIGN
MAJOR RESEARCH DESIGNS
Experimental Studies
•Test cause-and-effect relationships
•Laboratory experiment: high control, strong internal validity
•Field experiment: real-world setting, stronger external validity
•True experiment: random assignment
•Quasi-experiment: no random assignment
Surveys
• Cross-sectional: single point in time
• Longitudinal: over time
• Strong external validity, weaker causal inference
Secondary Data Analysis
•Uses existing data
•Lower cost
•May not perfectly fit the research question
Case Research
•In-depth study of one or more cases
•Uses interviews, observations, documents
•Multiple cases can improve generalizability•
Focus Groups
•6–10 participants
•Exploratory research
Action Research
•Solves real-world problems
•Builds theory through intervention and observation
Ethnography
•Cultural immersion
•Rich contextual understanding
•Limited generalizability
RESEARCH APPROACHES
Interpretive Research
• Theory building
• Deductive reasoning
• Often quantitative data
• Common methods: experiments, surveys, secondary data
Quantitative Data
• Numeric measures
• Statistical analysis
• Common in positivist research
Qualitative Data
• Interviews, observations, documents
• Rich, detailed information
• Common in interpretive research
Positivist Research
• Theory testing
• Deductive reasoning
• Often quantitative data
• Common methods: experiments, surveys, secondary data
Mixed-Mode Designs
•Combines quantitative and qualitative data
•Provides insights unavailable from either alone
•Useful for complex research questions
VALIDITY
Internal Validity (Causality)
•Determines if the independent variable causes the dependent variable
•Requires: covariation, temporal precedence, and no plausible alternative explanation
•Strengthened by: random assignment, control groups, manipulation
External Validity (Generalizability)
•Extent results can be applied to other settings, people, or time
•Includes: population validity and ecological validity
•Strengthened by: random selection, field experiments, longitudinal studies
Construct Validity
•Measures what it is intended to measure
•Accurate representation of the concept
Statistical Conclusion Validity
•Uses correct statistical procedures
•Appropriate test, adequate sample size, and meets assumptions
Cone of Validity
•Balances internal and external validity
•Examples: field experiments, longitudinal field surveys, multiple case studies
SELECTING RESEARCH DESIGN
Exploratory Research
•Problem is unclear
•Best fit: focus group or case study
Descriptive Research
•Describe characteristics or conditions
•Best fit: survey or case study
Explanatory Research
•Test relationships or causes
•Best fit: experiment, survey, or secondary data
Theory Building
•Usually uses interpretive designs
•Examples: case research, ethnography, action research
Theory Testing
•Usually uses positivist designs
•Examples: experiments, surveys, secondary data
Design Choice Depends On
•Nature of the problem
•Research purpose
•Desired validity
•Available resources
•Researcher competence
•Ethical considerations
IMPROVING VALIDITY
Manipulation
•Researcher changes the independent variable
•Compare treatment and control groups
Elimination
•Remove extraneous variables
Inclusion
•Include extraneous variables in the design
•Separately estimate their effects
Statistical Control
•Measure outside variables
•Control for them statistically
Randomization
•Reduces systematic bias
Random Selection
•Helps external validity
•Improves generalizability
Random Assignment
•Helps internal validity
•Supports causal inference