Evolutions

When I first started this course, I was a little apprehensive. While I am able to pick up technology skills fairly easily, I'm still in the very early stages of my doctoral program. I have an idea for my dissertation topic, and I know that technology will play an important role in that -- both in content and in analysis of the data. But I haven't really collected any data yet. I was skeptical of my ability to learn the tools without having my own research already complete, and I was jealous of some of my colleagues who are deeper into the process (and closer to writing the dissertation) because they had more data to work with. 

The more I learn about CAQDAS technologies, however, the happier I am that I'm getting exposure to all of these tools now -- in the early stages. I feel certain it will save me countless hours down the road because I'll be better organized and prepared to use the tools, and I won't feel overwhelmed to dive into them. I think the Bazeley & Jackson (2013) text said it best:

"Starting early, if you are still learning software, will give you a gentle introduction to it and a chance to gradually develop your skills as your project builds up. This is better than desperately trying to cope with learning technical skills in a rush as you become overwhelmed with data and the deadline for completion is looming." (p. 26).

It's nice to know that I'll be able to use the same tools throughout the process, and I can slowly learn more features as they're needed.

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The evolution and use of CAQDAS tools fascinates me. I had no idea coming into this semester how interested I would be in this area, but I suppose it makes sense given that it's a great intersection of my research and technology interests. I was talking about QDAS with my husband recently, and it occurred to me that he uses some similar technologies for his job. My husband is an attorney who works in complex business litigation, and one of the things he frequently has to do is review documents. For example, he might have to read 10,000+ emails downloaded from a client's inbox, code them for content, and look for segments that may support or refute a particular argument. We were talking about the software he uses and how that process compares to the work I may ultimately do in ATLAS.ti, and he mentioned that the new trend in the legal field is to move toward predictive coding software. He doesn't have it at his firm yet, but he said that it's supposed to learn some of your coding habits and conduct some of the document analysis for you based on parameters you set. 

I immediately started thinking about that in terms of qualitative research, and I wonder if something like that will ever be used or accepted in our research community. I would need to know more about how it works to really form an opinion on it, but I can see potential advantages and disadvantages with it. If it really is a learning software that learns how I code and applies that knowledge to my projects, then I think it could be a huge time-saver. But it could also distance me from my data, and I would really want to scrutinize the process that it uses. It's like outsourcing -- there are some things (like housekeeping!) that I'm happy to outsource to others, but there are other things that just aren't worth outsourcing. Coding might be one of those things. I guess we'll see as the software continues to evolve. 

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I'm excited to learn more about Dedoose. I like ATLAS.ti so far, but I'm a fan of cloud computing, and I'm curious about how it might handle my mixed methods research. Two questions that came up as I was looking through the website:

1) Compatibility: It says in the video that it can pull in data from the software programs like NVIVO and ATLAS.ti, but is that relationship bi-directional? Can you import and export data with Dedoose? 

2) Pricing: I know Dedoose charges a monthly fee. Do you only pay for the months that you use it (e.g., sign in)? If you have a project uploaded in Dedoose that you don't touch for a month or two, do you have to pay the monthly fee because they're still housed on the platform?