Nt1310 Unit 4

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Initially, all transcripts were reviewed by the researcher to begin to organize the data for themes, ideas, and feelings. By following the advice of Creswell (2013), the researcher began looking at the interview data for ideas, by taking notes, writing down words that stood out to her, identifying themes, and then classifying codes into categories.
Structural and in vivo coding was used to interpret the data. After the researcher read through the transcripts, she began to categorize and label the data according to the guidelines of structural coding. Using this method and NVivo, the researcher categorized the participant’s responses as they related to the interview questions. Structural coding helped the researcher identify the different participant’s answers to the interview questions on school connectedness, but as the researcher focused on identifying themes, she was concerned her personal biases towards the topic were evident and decided to go back and
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Utilizing the word cloud function of the NVivo software, the researcher created a Word Cloud (see Appendix A) to determine the codes that emerged from the interviews: connect, involved, people, school, friends, parents, together, and pride. This software package allowed the researcher to query and investigate the data using functions such as a cluster analysis of high-frequency words. Following the queries, the researcher went through a second iteration of the initial codes and categorized the code list into three main themes: family influence, school influence, and influence on self. After the codes were categorized, there were a few remaining codes that did not fit into any theme. These codes included why students do not get involved with schools. Even though the researcher thought this was relevant information, she was unsure how to code it into the established