I sent out the last batch of emails encouraging people to participate in research. As always, I get replies, some saying they do not have BYOD or no longer have BYOD as they have gone 1:1. I didn't think anything of it except in terms of whether they were able to participate in the research, then... Well, I also get bounces - bad emails, old emails of people no longer there, etc. Since I figure the school associated with that address has BYOD, I look for an alternate address. So there I am digging around in a school's website for an address and find their BYOD information sheet for parents. It's apparent from reading the sheet that the school, and independent school, had a BYOL program where students brought their own laptops. However, they are no longer doing that - only students who are currently doing BYOL may continue, and if they want to replace their laptop and continue BYOL, they can. But with conditions. Those conditions are:
they have to buy one of three specified models;
they have allow the school to re-image the hard drive with the school's software and operating system and,
students and parents will not have admin access to the computer.
Now that's a fascinating approach - that moves firmly from BYOD to a standard 1:1 program, except they don't have a 1:1 program. They do allow students to bring small devices and use them with the teacher's permission. This is just a fascinating scenario to me.
On the data front, I've created one set of codes, and naturally have way too many. That's where I found a couple of issues with NVivo - naturally it doesn't spit out the data exactly like I want it. I do love the fact that I can look at a code (node in NVivo-speak) and see the text I coded, which makes it easy to check for consistency in coding. But getting all the nodes and the associated text in printable form so I could sort and group was not so easy. I've somewhat managed to condense the codes and now I'm making a pass over a second interview, then I'll go back to the first. I also am checking the codes against the survey organization. After all, the goal is to triangulate.
I've started looking at the survey data. I only have a couple of open-ended questions, and people only write one or two sentences, so coding those will not be overwhelming. I also intend to code all the surveys since I will have no more than ten. The difficulty is that the interview is semi-structured. Every person's story is different so the path we take through the interview is also different, even with the questions as checkpoints.
I also started investigating various stats packages to see about saving a buck. Wikipedia has a comparison page, as well as just a list. Of course, every package requires a more detailed look. PSPP is free, but I'm not sure it does MANOVA. R has high ratings, and a very steep learning curve. SOFA looks simple, but it doesn't seem that powerful. So, it looks like I will be spending quality time with SPSS.