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A unit of measure











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“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts, advanced to the stage of science.” ~William Thomson, Lord Kelvin (1894)

This week, our thoughts have shifted from the specifics of evaluation and research to data collection. But what is data? How is it measured? To me, as a scientist, this point is of vital significance. How we measure what we observe will impact how we draw conclusions from our observations. The Weiss reading was detailed in the examination of data and sampling methods, and critical of how data collection can skew results and reduce significance of research findings. I am finding that as I read both the course text and the supplemental instructional materials for this course, I am being constantly challenged in my previous understanding of research and evaluation. If you had asked me before this class to define the differences between research and evaluation, I would have told you that they were very nearly one in the same. Based upon the Boulmetis and Dutwin text, they are distinctly different. One of our chapter questions this week was to define the differences between research and evaluation. The book makes it very clear; research occurs under a controlled setting to seek an understanding of cause-effect relationships, evaluation seeks to offer insight into a program for a benefit of a particular group of vested individuals. However, the water begins to get murky when talking about using the scientific method in research and evaluation. It would seem from the book that evaluations would not use an empirical approach…but why not? If the scientific method is the gold standard, why not use it whenever applicable. And if for some reason it is not applicable, can you realistically draw any significant conclusions? Maybe this comes from my own lack of understanding of complex methods of research. I want to look at ordinal data. Nominal data has very little interest to me, especially when it is based upon self-reporting and subjective observations. I guess my question boils down to this…if someone is going to perform an evaluation, why bother if it cannot be accomplished empirically?


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