After the class, I
have a deeper understanding of how different research purpose could affect
tools select. Unlike other computer assisted qualitative research tools, NVivo
needs to have pre-defined coding schemes that are hierarchical. This feature
tends to exclude codes that are emergent from the data, which refers to codes
that come out from data. This features will exclude studies that are
explorative and without pre-defined codes.
Then in the class, we discussed the risk nature of having
pre-defined codes. Rebecca raised the point that it might be risky to have
codes pre-defined since the data would have different pattern than the codes. I
would not be bothered much by this. Coding is an interpretive and trial-and
–error process. I agree that coding should be several rounds based, which means
the second round of coding should complement what didn’t achieve on the first
round. I also think the importance of having pre-defined coding scheme means
having a clear theoretical framework ready before conducting the study.
From the small group discussion, I found different fields
hold different research method. In learning sciences, most of the work do
coding for quantifying qualitative data. There are some qualitative studies
that do coding for interpretive purposes. We also talked the necessity of
having mixed methods of doing research.
Indeed, there are times when pre-defined categories will be the approach we take up. There are other times when we will engage in a more "flat" and "emergent" coding process. This certainly relates to our methodology and more specifically the analytical approach we take up. Nonetheless, packages like NVivo, while designed with a more hierarchical, pre-defined coding structure, can be flexibly applied!
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