I was reminded recently about the 1992 AEA meeting in Seattle, WA.  That seems like so long ago.  The hot topic of that meeting was whether qualitative data or quantitative data were best.  At the time I was a nascent evaluator having been in the field less that 10 years and absorbed debates like this as a dry sponge does water.  It was interesting; stimulating; exciting.  It felt cutting edge.

Now 20+ years later, I wonder what all the hype was about.  Now, there can be rigor in what ever data are collected, regardless of type (numbers or words); language has been developed to look at that rigor.   (Rigor can also escape the investigator regardless of the data collected; another post, another day.)  Words are important for telling stories (and there is a wealth of information on how story can be rigorous) and numbers are important for counting (and numbers have a long history of use–Thanks Don Campbell).  Using both (that is, mixed methods) makes really good sense when conducting an evaluation in community environments, work that I’ve done for most of my career (community-based work).

I was reading another evaluation blog (ACET) and found the following bit of information that I thought I’d share as it is relevant to looking at data.  This particular post (July, 2012) was a reflection of the author. (I quote from that blog).

  • § Utilizing both quantitative and qualitative data. Many of ACET’s evaluations utilize both quantitative (e.g., numerical survey items) and qualitative (e.g., open-ended survey items or interviews) data to measure outcomes. Using both types of data helps triangulate evaluation findings. I learned that when close-ended survey findings are intertwined with open-ended responses, a clearer picture of program effectiveness occurs. Using both types of data also helps to further explain the findings. For example, if 80% of group A “Strongly agreed” to question 1, their open-ended responses to question 2 may explain why they “Strongly agreed” to question 1.

Triangulation was a new (to me at least) concept in 1981 when a whole chapter was devoted to the topic in a volume dedicated to Donald Campbell, titled Scientific Inquiry and the Social Sciences. scientific inquiry and the social sciences   I have no doubt that this concept was not new; Crano, the author of this chapter titled “Triangulation and Cross-Cultural Research”, has three and one half pages of references listed that support the premise put forth in the chapter.  Mainly, that using data from multiple different sources may increase the understanding of the phenomena under investigation.  That is what triangulation is all about–looking at a question from multiple points of view; bringing together the words and the numbers and then offering a defensible explanation.

I’m afraid that many beginning evaluators forget that words can support numbers and numbers can support words.

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One thought on “Triangulation (or another way to look at data)

  1. Correct me if I’m wrong Quantitative methods are the ones that concentrate on numbers and frequencies rather than on meaning and experience.

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