Ongoing Data Analysis
I am immediately struck by the distinction between data analysis during the research project and final data interpretation after the study is completed. This is a distinction that I have not considered before and I generally assumed that while you might "peek" at your data as you gathered it, analyzing it would not be beneficial until you completed the length of your study. The chapter goes on to outline important terms and techniques for research data.
Analysis : Breaking down data into smaller pieces. A dissection to look at each part.
Synthesis: Putting all of the parts together to observe the data as a whole. Looking for what the big picture is telling us from our data.
Deconstruction: Taking apart our methods and looking to see where we might be influencing data or making assumptions about the data.
Contextualization: This is a meta process of viewing how we view data. Understanding who we are as observers. Understanding the culture, location, historical influences, social influences, etc. that may be skewing our view of the data.
We have been given the task to start an observation protocol and I am finding it difficult to perfectly locate my targets, however chapter 5 suggests being open to ongoing data analysis that changes, adapts, and evolves as the study progresses. I know that I will need to do this with my critical question. Ultimately, chapter 5 is urging us to be mindful of the data that is coming in, journal our thoughts, make notes on what is working and what is not, be open to the possibility that our focus could shift as the data reveals new information, and to deeply analyze where we could be missing something or making mistakes based on our contextual views.
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