Data redundancy for triangulation

A topic in research methodology

Triangulation refers to approaching the same research question using several sources of evidence. There are different kinds of triangulation.

Triangulation requires redundancy in the information available – that is that there are several slices of data that can be interrogated to help answer the same research question.

"Although consistent interpretations of several 'slices of data'…do not ensure the researcher has made a good job of making sense of the data, the effective use of triangulation gives the reader more confidence that the researcher has produced a trustworthy and authentic account."

Taber, 2013, p.179

In the hypothetical schematic example below, there is sufficient data to triangulate for two of the three research questions.

Triangulation is only possible where there are several different sources of data that can be interrogated to help answer the same RQ

Key:

RQ: research questions

Shapes represent different types of data sources, perhaps:

  • Squares: classroom observations
  • Circles: teacher interviews
  • Ellipses: documents (e.g., school policy documents, etc.)

Colours represent different participants/groups, perhaps:

  • Green, blue, orange – different classes
  • Red: Governing body.

Judging redundancy with compound questions.

Some research questions may be compound: meaning they can only be answered by, in effect, first answering two or more subsidiary questions. Care must be taken in judging if there is redundancy in data sources when working with compound research questions as data sources are needed to addres each subsidiary question.


Work cited:

My introduction to educational research:

Taber, K. S. (2013). Classroom-based Research and Evidence-based Practice: An introduction (2nd ed.). London: Sage.