February 25, 2009
I am struggling with interpreting data. I’m struggling with the basics of interpreting tables and graphs and trying to see the point that is being made in writing come through in mathematical form. Also, in class last Wednesday we viewed software that helps compute data. While certainly a helpful tool to plug in some numbers and be spit back an “answer,” I am at a loss as to what all the variables mean. The highest level of math I ever completed was Pre-Calculus and I barely skated by with a C. Math has never been my strong suit. Numbers and abstract representations do not get processed and instead get lost inside my head.
Even with these struggles I am enjoying reading about the benefits of a co-taught classroom. I have found higher test scores for both special education and general education children who are in a co-taught classroom. I have also found an improved quality of life for special education students, and I could argue general education students as well. I’m not sure if “quality of life” can be measured with mathematical terms. Therefore would one write two separate research papers one comparing co-teaching and test scores and one teaching co-teaching and quality of life? Or is it acceptable to include both sets of “data” even though they cross quantitative and qualitative boundaries?
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It is unfortunate that you don't feel comfortable with quantitative data. I wish we could spend more time learning quantitative techniques. But, after today, we will have to move on to qualitative methods. A survey course like this doesn't allow deeper focus on any one topic.
ReplyDeleteYou raise an interesting point about using different categories of data - quantitative and qualitative - to look at a common set of research questions. Actually, a mixture of both types of data is not uncommon in most research reports. In addition, there is a mixed-methods approach where the burden of linking evidence to claims is more or less equally shared by quantitative and qualitative data. So see for yourself where your group's research is headed, if your study is primarily quantitative, a bit of qualitative data will only help it look more persuasive, and vice versa.