What does data triangulation involve in research?

Data triangulation involves utilizing multiple data sources or methods to enhance the credibility and reliability of research findings. By integrating different perspectives and approaches, researchers can cross-verify results, leading to a more comprehensive understanding of the research problem. This multiplicity allows for the identification of patterns and discrepancies that may not be evident when relying on a single source or method.

The use of multiple data sources or methods helps mitigate bias and strengthens the overall validity of the study. For instance, combining interviews, surveys, and observational data can provide a more nuanced view of the phenomenon being studied. This practice is crucial in research that seeks to explore complex issues where findings can vary significantly depending on the methods used.