Review:
Triangulation (research)
overall review score: 4.2
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score is between 0 and 5
Triangulation in research refers to the methodological approach of using multiple data sources, methods, theories, or investigators to cross-verify and enhance the reliability and validity of study findings. It is a common strategy in qualitative and mixed-methods research to ensure comprehensive understanding and reduce biases.
Key Features
- Use of multiple data collection methods or sources
- Cross-verification of results to improve accuracy
- Application across qualitative, quantitative, or mixed-method studies
- Enhances credibility and validity of research findings
- Encourages diverse perspectives for comprehensive insights
Pros
- Improves reliability and robustness of research outcomes
- Reduces bias by integrating different viewpoints or data sources
- Provides a more comprehensive understanding of the research subject
- Widely accepted and valued in academic research methodology
Cons
- Can be time-consuming and resource-intensive
- Requires careful planning to effectively integrate multiple approaches
- Potential for conflicting data that may complicate analysis
- Less effective if not properly implemented or if sources are not truly independent