Description of Data Analysis

After observation and group discussion procedures, student video diaries were used to collect data, following Hutchison’s (2011) visual ethnographic method. Data collected from student generated videos allows for stronger participatory research, essential to critical ethnography as participant research provides more emancipatory data collection. Another aspect of student videos is that my presence as researcher is not required at the time of data collection, hence I was able to have less of a physical impact on the research site of this data

collection. Participants had the full control over their participatory journal, but I provided directions with possible prompts to use if they needed (appendix I). The prompts were worded the same as the interview questions used for individual and focus group interviews. Participants were given the opportunity to edit their film as they saw fit. To ensure ethical requirements of consent, participants could participant in some, none, or all of the data collection. All participants

participated in the observation(s), individual interview, and focus group interview.

Five out of eight participants submitted an audio or video participatory journal, with three participants declining to submit (this information is further detailed in the limitations section of the research conclusion chapter, chapter 6).

3.2.7 Description of Data Analysis

Aligning with an ethnographic approach, I provide detailed and thick description and use thematic data analysis in order to narrate inferences on conclusions I determine through the data (Creswell, 2012). First, I locate shared patterns of meaning (belief, behaviour, and/or language) amongst the data I collect (Creswell, 2012). The analysis of this information began during stage two,

the primary reconstructive analysis, of the data collection process. Low inferences were used to begin this analysis and low-level codes were employed. Low-level coding began with the primary record and primary field notes, and the coding process did finish until after the completion of stage three. Low-level codes remained as objective as possible from the beginning, and aimed to employ language that portrayed actions of participants, only. As the low-level coding continued through the observational stage, I placed more interpretation upon codes as was “supportable through horizon analysis” (Carspecken, 1996, p. 147).

After over one hundred codes were compiled I used member checks with

participants, who were asked to review how I interpreted meaning in primary field notes.

At the end of stage three, more abstraction was used to code data. Before abstraction and high-level codes were determined, however, I compiled a set of raw low-level codes, which intersected and showed redundancies (Carspecken, 1996). In order to create this set of codes, Carspecken (1996) suggests six steps:

locate word processing files that contain the original primary notes; create a blank secondary file electronically adjacent to the primary file; when anything from the primary notes is deem worthy of a possible code, paste it to the blank coding file with corresponding explicit detail as well as the file and page numbers from the original, primary record; continue coding primary records creating new codes and starting to create sub-codes where appropriate; and, lastly, use reconstructive analysis on sections from the primary record to which my attention has been drawn, and, from the results of this analysis, start to form high-level codes.

Carspecken (1996) indicates that one must go back through primary low-level coding to find codes that align with high-level codes to determine the viability of the high-level code. Said high-level codes are also based on “a horizon analysis of one possibility within a meaning field” (p. 150). As I conducted Carspecken’s (1996) coding processing, I used more current computer software, specifically Dedoose, in order to house this information and create coding hierarchies.

Dedoose maintains original text transcriptions and helps to create copies of coding excerpts that can continually be viewed in the context of the whole transcription. This program was helpful to both analyze codes and retain data collected in their original context.

As mentioned, codes were first listed as raw codes, which were then re-organized to create a hierarchical structure of codes in a “tight hierarchical scheme” (Carspecked, 1996, p. 150). This list also includes the file and page number of the primary note document for coding reference. Carspecken (1996) also suggests to tag low-level, high-level, and very high-level codes using the asterisk in order to differentiate which codes used low level inferencing and which codes used high level inferencing. For my research, I identified low-level codes by using no asterisk at all (as there were many more low-level codes than high-level codes). I labeled high-level codes with one asterisk, and I labeled very high-level codes with two asterisks. Labeling codes in this way helped me place interpretation on the data within the appropriate timing of Carspecken’s (1996) three stages of the data collection process. For example, when I constructed meaning fields, in stage two of the data collection process, I used only low-level

codes, which is what Carspecken’s (1996) guide suggests. To reiterate, low-level codes labeled behaviour or concepts in the most objective way, and I only aligned these codes with theoretical frameworks after the initial meaning fields had been constructed (during stage two) and the data collection had finished. Then, in the last stage of the data analysis, I included some high-level codes and few higher-level codes (Carspecken, 1996) that matched the horizon analysis and theoretical frames used for this research. The high-level and very high-level codes placed high inferencing on data, primarily according to the theories of Said (1994) and Bourdieu (1993; 2003). Any high-level or very high-level codes that did not align with the horizon analysis or any of the theoretical frames (discussed throughout this research) were not included in the data analysis as the high-inferencing of these codes was not supported by the final data analysis.

Carspecken (1996) also indicates that the hierarchical reorganizing of codes should not begin until stage three of the data collection is completed so that the dependability of code hierarchy would not be compromised before dialogical data was collected. The hierarchical organization of codes revealed key

categories, which are identified and further discussed in the findings chapter, chapter 4. How one determines the categories and emphasis of these categories should align with the theories to which the research aligned. I, therefore, went back to the literature and theories in order to assist with locating categorical emphasis for codes, and to rebuild the literature as required after analysis of the data.

According to Carspecken (1996), “good coding will almost deliver your final analysis, particularly when reaching the stage of code reorganization” (p.

153), and I found this to be the case for this research. In order to provide the analysis of findings and suggestions for future research, I depended on my thorough coding approach completed through reconstructive analysis. Detailed and thick description was provided with narrative analysis in order to give a well rounded depiction of the critical issues raised and to better understand the

importance of the advocate and further a plan for change (Creswell, 2012). I also placed data analysis within the context of the participants and research site and I articulate how the analysis is tied to the cultural context of the site. As mentioned, in the findings and call to future research chapters, chapters 4 and 5, I return to the literature to align my interpretation with the theoretical frameworks used for this research.

In previous sections of this chapter, chapter 3, I have provided a rationale for an ethnographic approach and determined that this approach was best-fit to exploring and providing more understanding for the nuances of the TCK experience negotiating cultures. I specified three stages of data collection procedures, and discussed the data analysis plan. In the next section, I briefly include the credibility of knowledge claims and discuss the extent to which the claims are generalizable to other contexts. Validity of research claims is more extensively discussed in chapter 6, the conclusion of this research.