Data Triangulation
Using multiple data sources, times, or settings to examine the same phenomenon, so findings do not depend on a single vantage point.
Data triangulation strengthens a study by drawing on more than one source of data about the same question, for example interviewing both managers and staff, comparing survey responses with documents, or collecting data at different times and sites. It is one form of a broader triangulation family that also includes using multiple methods, multiple analysts, or multiple theories. When independent sources converge, confidence in a finding grows; when they diverge, the discrepancy itself becomes informative and pushes the analysis toward a fuller explanation.
In a thesis, triangulation is a practical way to demonstrate rigor, especially in qualitative and mixed methods designs where statistical generalization is not the goal. Be specific about what you triangulated and how you compared the sources, and discuss disagreements openly instead of smoothing them over. Examiners value evidence that your conclusions survived being tested from more than one angle.
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