But like much stand-alone software, QDAS is now having to face the challenge of Web 2.0. They are not the only ones (consider Microsoft Word up against Google Docs or Wiki's) and you get the idea. Suddenly the world is a lot wider; there are more possibilities; and potential gains and losses.
As with most things in our technologically fast-moving world, the horizon on this issue moved toward us very quickly. Silvana diGregorio and I published our book on QDAS in December 2008 (Qualitative Research Design for Software Users, which focused on a suite of well known software packages. Since that time, we've become increasingly aware of the fast-paced change out there as Web 2.0 moves forward with new tools for qualitative researchers...and QDAS developers are pushed by Web 2.0 innovations in new directions to meet user demands.
As a result of these changes, several issues arose for us:
1. What do you call this new stuff?
Currently, we have settled on QDAS 2.0, which stands for the hybrid situation that currently exists while the field uses a mixture of both QDAS and new Web 2.0 tools that do qualitative research types of things.
2. Who's Who is this area now?
Whereas QDAS developers used to be a cozy world unto themselves, the field is wide open now. In addition to QDAS developers you now need to keep track of:
- the big companies in Software and Web 2.0 development. (Google, MS Labs, IBM--and many more of the big, hardy group are conducting research and developing prototypes for tools that will do a lot of things qualitative researchers will like and want to use)
- Government funded research tools--pay attention in particular to the UK's Economic and Social Research Council activities (ESRC)
- Wild West of new independent developers who are developing web-based tools and new Apps. Take a look at Annotate, Ethnosnacker (where you can learn about the Everyday Lives application for the I-Phone).
I'll be writing a lot on the QDAS/QDAS 2.0 challenge in the upcoming months because it is so near and dear to my heart.
1 comment:
Typically descriptive statistics or descriptive analysis is the first level of analysis. It helps researchers summarize the data and find patterns.
Qualitative Analysis
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