Data Analysis Data analysis.Use your interview transcript to begin practicing data analysis. First, using manual coding, read through the transcript and code it for themes. Specific guidelines and steps will be discussed in class and provided here (see below). If you are using a specific research method/design, try (if you would like to do so, not required) to follow that approach in data analysis (e.g. Grounded Theory coding levels, CQR categories, Listening Guide sequential readings, etc.). Use the Wertz et al. (2011) in addition to other course readings and texts as a guide; consider readings focused on data analysis and interpretation. Optional computer software analysis: Then,if you would like, choose a qualitative research software package that fits your computer platform (Mac or PC). You may download a free copy (typically granted for 30 days) of NVivo, Atlas.ti, HyperResearch, MAXQDA or an alternative that you prefer. You do not need to purchase it. Note: It takes a bit of time to become familiar with the software. You do not need to master it, but need to develop a basic working knowledge to form an opinion about strengths and weaknesses. This is optional for this assignment. NVivo free download:http://www.qsrinternational.com/products_free-trial-software.aspx Atlas.ti Free Download:http://atlasti.com/free-trial-version/ MAXQDA: https://www.maxqda.com/trial This is due after the second weekend to provide class time to practice analysis as a group. You may write a draft before the second weekend to revise before turning it in or you may wait to write this up until after the course weekend. Write approximately 3-4 pages that provides a snapshot of the analysis, with a few examples, and then discuss the issues, concerns, problems and questions that arose along with any general themes or tentative interpretations observed. If you tried computer coding (optional), discuss the differences for you in manual vs. computer coding and analysis. Integrate course readings on analysis.Include 1-2 pages of coded transcripts with your paper. Data Analysis Information Manual Analysis Goal: Practice data analysis steps - extracting main themes from your data. Refer to readings as needed. If you want to practice a particular kind of data analysis like Voice-centered Method/Listening Guide or CQR (Consensual Qualitative Research) or Grounded Theory, use the description for that specific method and try it out. Description:In this part of the assignment you will manually analyze the interview data youve collected in in your interview assignment, and will demonstrate how you arrived at a list ofthemescommon across your interviews, and themeaningyou have made from this assignment. The following are some useful guidelines for conducting your manual data analysis. STEP A (Preparation) Make a copy of your transcript for coding. You only need to do data analysis on 2-3 pages of transcript (although you can do it all if you want); find a good, meaty part of the interview. Review the readings on data analysis. STEP B (Open Coding): In this step, you identify textual material within your transcript that you think is significant for the context of your research question, then create concepts (codes) for this material. 1. Read/skim through your transcript; identify and annotate significant textual material (i.e., phrase(s), sentence(s) or paragraph(s) that describe important events, objects, explanations, circumstances, evaluations, etc.) 2. Skim through the annotated textual material and create concepts (i.e., codes) using mnemonics (i.e., meaningful names that can be comprehended by other readers and that make sense in the context of your research) for each of these textual units. 3. Associate the concepts (codes) you have created with the textual data.Each textual unit might be associated with multiple concepts (codes). During coding, you will notice that you are reusing concepts that you have already created, and eventually no new concepts will emerge, meaning you can move to the next step of axial coding. STEP C (Axial Coding). Categorize the concepts (codes) you created in the open coding step by assigning them to higher-level categories, if possible.This categorization produces a more abstract model of the concepts (codes). Take them up to the next level of descriptive codes. STEP D (Selective Coding): In this step, you develop the big picture, by creating a category-network, in which you relate concepts (codes) and categories and translate these relationships into short themes. (NOTE: The relations you look for are not necessarily causal relations you are not trying to establish causality or build a theory).Review your category-network by comparing and contrasting the various categories. During this process, you may perceive some textual material differently from before (i.e., fitting better into an alternative category or belonging to an additional category). Perform any desired changes if called for. STEP E: (repeat STEPs B, C, D for additional transcript material if you like). STEP F: Check to see if there are categories that seem to fit together - if so they may form a major theme in your research. You may also color code the categories using a different color for each category and its associated textual data in the transcript. This will help in reviewing the transcripts at a later stage. Go back to the original copies of the transcripts and search for textual material that was not highlighted to see if belongs to any theme or category and handle it. Considerations in your data analysis paper

1. Introduction paragraph (e.g., description of the interview transcript that you are using for this assignment).
2. Descriptionof your manual analysis: (process, sample of codes along with their associated text from transcript, list of categories, list of relations between categories, list of final themes).
3. Reflection on the process of data analysis how long did it take, what did you like, what was fun, challenging or frustrating? What did you find surprising?
4. Computer coding: If you tried computer coding, comment on how that process differed from manual coding and any implications from this approach.
5. Analysis & Interpretation: What did you learn from your interviewee and observations? What can you say about the themes and the meaning you have made? What is going on here? How do you interpret your findings? How does this inform what you now know about your original research problem/question? Are your new learnings consistent with what you have read about your topic in the literature? Have you identified some new directions to explore? Have you noticed any contradictions or surprises between your interview data and themes, and what the literature has suggested? Howtrustworthyare your interpretations? What are thelimitationsto what you can know?
6. How might you sharpen your research problem and question based on what you have learned from this assignment? What might be some implications for your work?
7. Provide a 1-2 page example from your coding process (in addition to the 3-4 page paper) to illustrate your steps in the data analysis process. Put this into an appendix to your paper.

Attachments:

data-analysis....docx