During data analysis, the teacher-researcher engages in a systematic effort to search for patterns or trends in the data. There are many ways to accomplish this. Regardless of the particular technique employed, during the analysis phase, the researcher tries to systematically cut, sift, and sort the data into piles of like or similar objects. The key purpose of this systematic sorting and categorizing is to assist in answering the following two questions: What is the story told by my data? What might explain this story? These two questions help us to frame out what can be learned from the data analysis process. While you will not formally implement your proposal during this course, you need to consider how to work with the answers that your data offers. Asking these kinds of questions and exploring the themes that can arise from the work can direct your interpretations. Once the researcher believes the process has resulted from inadequate answers to those two questions, it is time for the researcher to take a critical look at the initial AR goal and ask how it may need to be revised based upon the analysis of the data (Sagor, 2002, p. 8-16). Using the triangulation matrix that you created on Wednesday as a base, brainstorm some ideas for how you think you would analyze the data that results from your collection methods. Be conscious of the approach that your data suggests (qualitative, quantitative, mixed methods) and make appropriate selections. Share your ideas for the analysis strategies. Be sure to include 2-5 possible themes that you expect to emerge from the data that you would collect. Remember that these are thoughts about where you might end up at the end of the work based on the experiences of others and your familiarity with your context and professional experiences.
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