combines quantitative and qualitative methods in a two-phase approach. It uses qualitative data to explain quantitative findings, providing a comprehensive understanding of complex communication phenomena through statistical analysis and in-depth exploration.
This approach addresses limitations of single-method research, enhancing explanatory power by combining statistical trends with contextual insights. It facilitates deeper understanding of unexpected or contradictory quantitative results, making it valuable for communication research.
Overview of explanatory sequential design
Combines quantitative and methods in a two-phase approach within Advanced Communication Research Methods
Allows researchers to use qualitative data to explain and interpret quantitative findings
Provides a comprehensive understanding of complex communication phenomena through integration of statistical analysis and in-depth exploration
Purpose and rationale
Addresses limitations of single-method approaches in communication research
Enhances explanatory power by combining statistical trends with contextual insights
Facilitates deeper understanding of unexpected or contradictory quantitative results
Strengths of explanatory approach
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Provides clear, distinct stages for implementation and analysis
Allows for in-depth exploration of quantitative findings
Enhances credibility of results through methodological
Facilitates communication of findings to diverse audiences (academics, practitioners)
Limitations of explanatory approach
Time-consuming process due to sequential nature
Requires expertise in both quantitative and qualitative methods
Potential for disconnect between quantitative and qualitative phases
May be challenging to integrate divergent findings
Key characteristics
Two-phase design with distinct quantitative and qualitative stages
Emphasis on explaining quantitative results through qualitative inquiry
Integration of methods occurs primarily during interpretation phase
Quantitative priority
Greater emphasis placed on quantitative data and analysis
Quantitative results guide the focus of subsequent qualitative phase
Statistical findings form the foundation for qualitative exploration
Allows for generalization of results to broader populations
Sequential timing
Quantitative phase conducted first, followed by qualitative phase
Clear temporal separation between and analysis stages
Allows for careful planning and refinement of qualitative protocols
Provides opportunity to address unexpected quantitative findings
Integration points
Initial integration occurs during development of qualitative protocols
Major integration takes place during interpretation of combined results
Quantitative results inform participant selection for qualitative phase
Final integration synthesizes statistical trends with qualitative themes
Phases of implementation
Follows a structured, linear process with distinct stages
Allows for careful planning and execution of each research phase
Facilitates clear communication of research process to stakeholders
Quantitative data collection
Utilizes , , or content analysis techniques
Employs probability sampling methods for generalizability
Focuses on measuring variables and testing hypotheses
Gathers numerical data to identify trends and relationships