What is data triangulation in mixed-methods?

What is data triangulation in mixed-methods?

• A. Data triangulation uses a single data source or method.
• B. Data triangulation is a form of data-entry error.
• C. Data triangulation uses multiple data sources or methods to corroborate findings.
• D. Data triangulation is not used in mixed-methods.

Answer: (C)

Data triangulation means using multiple data sources or methods to corroborate findings. In mixed-methods research, this approach helps validate results by checking that qualitative and quantitative data tell a consistent, convergent story. By comparing different angles or measurements, researchers gain greater confidence that the results aren’t driven by a single source or method. Using a single data source or method would not provide the cross-check that triangulation aims for. Treating data-entry errors as triangulation would be mistaken, since triangulation is about methodological cross-validation, not errors. And triangulation is indeed common in mixed-methods, where integrating multiple data types strengthens the overall inferences.

Data triangulation means using multiple data sources or methods to corroborate findings. In mixed-methods research, this approach helps validate results by checking that qualitative and quantitative data tell a consistent, convergent story. By comparing different angles or measurements, researchers gain greater confidence that the results aren’t driven by a single source or method.

Using a single data source or method would not provide the cross-check that triangulation aims for. Treating data-entry errors as triangulation would be mistaken, since triangulation is about methodological cross-validation, not errors. And triangulation is indeed common in mixed-methods, where integrating multiple data types strengthens the overall inferences.