The 3 “S” of Data Analysis

On the 15th week, we started our class with reading the different interview transcriptions that were printed out previously for us to read. This was the first time we looked at the transcribed data and began our initial identifying themes and coding data.  At first, we took about first 40-50 minutes of in-class time to read the transcripts. We were reading and also taking notes while marking up places in the transcripts that give rise to intriguing ideas that can eventually lead up to a theme or something. In other words, we were potentially looking for themes in the data for coding and categorizations.
After we read the transcripts, we were paired with the person next to us to share our findings if you will. Most of us had not been able to get beyond the first two transcripts we laid out hands on. From the transcripts we read, we all marked interesting information that were indicative of participants’ communication style, preference and methods. For example, my group-mate and I discussed the theme of “switch”, more like “rhetorical switch” that happens for interview participants in academic and non-academic setting in terms of communication styles. By “style”, I mean the stylistic choices that they make in terms of diction. For example, we both noticed that  the participants choose to use simpler words in communicating with their inner-circle people such as friends and family. However, when it comes to communicating with outer-circle people, such as colleagues they tend to use more formal English. Switching of stylistic choice is then a conscious rhetorical decision they make depending on the places and spaces of communication.








   Image 1: our reading notes on the board.

The rhetorical switch also happens on a conceptual level too as we both pointed out. For example, one of the participants mentioned he can talk about Foucault with his professional colleagues but not with family members. Other groups also shared their observations with the class. For example, one group mentioned the theme of self-monitoring that is part of language practices especially for the people with multilingual background. Another group mentioned the point about language-based persona—something our participants indicated to. Both these resonated with my personal languaging experiences being one with multilingual background. Other trends that we discussed were “self-perceptions” of language users and also labeling identity. Another trend in the data was “authenticity” of communication depending on people our participants interact with. For example, with inner circle people like family the communication tend to be more authentic whereas, with outer circle people, it may lack authenticity in some contexts. A few examples that we examined  reminded me of Geisler's point on “context-appropriate vernacular or code”. To determine the integrity of interpretation,  “Not all language data need to be analyzed as language. There are times when we need only concern ourselves with what language says rather than what it does.” (240).
After the discussion part, we all wrote some keywords that came up through our discussion. It was followed by class discussion of the trends we are noticing in our accumulated data. After that we took break for few minutes. When we came back, we went back to reading more transcripts to find out trends in the data. We looked the three main research questions to see how our current findings align with those questions for our project. At this stage we talked about coding and categorization of data—both of which are significant parts of research process. We also talked about data triangulation. Rachel, our professor made a nice visualization of data triangle on the white board:
                                                                     Interviews

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                                                 Artifacts                      Fieldnotes
                              Image 2: Visualization of Data Triangulation

She pointed out that we need to think about these three sources of data that we have in order to triangulate our findings. We all agreed that this is just the beginning of “data-surfing”—we did not use this exact term in particular. But I think that’s where we are at the moment. We also briefly discussed our to-dos for next week—writing rough analysis of the data. In next couple of weeks, one letter out of English alphabet is going to be important for our research methods class—"S”—with a lot of surfing (also scanning), sifting (of data) and solidifying our findings.