Data analysis
Mood:  a-ok
Now Playing: I like the way (Tommy James and the Shondells)
Topic: Data Analysis
Well, the data analysis is a bit tricky! I have a fair idea how I'll do the approaches to inventory and the ASI.

Well first up, I'm going to get overall scores for lecturers on the beliefs and intentions scales, and check to see if these differ from discipline. Then check and see if there is any difference on the knowledge transmission and learning facilitation scales. I do however realise I have no data to check if there is change to contextual factors such as age, gender, time in teaching - but, we'll see if it still holds across disciplines - and it gives impetus for further research perhaps.

As I said before one of the problems is in determining which discipline fits in where. Now Lueddeke (2003) looked at soft and hard disciplines whilst Lindblom-Ylanne et al (2005)looked at the four categories of soft, hard, and its pure and applied forms. Now, I wish to compare with these results, so, I think it will be best to select these headings for comparison rather than engineering, business and mathematics ... since, I may have a mixture of different disciplines. I think depending on the courses I should classified them rather than the discipline they belong too ... for example, something with a course name such as "Operations Research" - that should be classified hard ... but if applied or pure - not sure ... well ... it might do the 'pure' work of operations research and should be 'hard pure'. I reckon if its 'operations research' and based in business I might think it is 'pure applied' but that doesn't make sense - since business is soft .. isn't it? Maybe should stick to where the course is based on and their target students.

But you know what I'm thinking - I'm looking at the comparison of the UWI courses engineering management (for the pure mech eng. students) and the operations research course for the industrial engineering students. Now the engineering management, I'll have to call that soft applied - I'm sorry - it seems more like a course in the business school ... whilst the operations research course seemed more like a hard pure course - so, I'm afraid of the conflicts that might come about if I did the disciplines, since both these courses would have been assigned as hard applied because they were in the engineering faculty ... this is getting difficult to decipher - so, I have to make a framework for establishing where each course goes. I think what I might do - is first compare across soft, hard disciplines and then compare across the courses which I think are hard or pure.

It might be difficult to explain this and make sure that this doesn't get too confusing to the reader - so, got to make the explanation and the headings very clear as to why I have chosen to compare this way - well, might be very well that I don't find anything - so might just ignore the reason for classifying like this (but then all that post-hoc analysis problems comes i.e. searching for results and hence increasing your Type II errors - never mind that!).

Well, not sure how much I can get out of the ASI, but might decide to check and see what their overall ASI scores, I've only got 5 lecturers so not much to do any comparison unless they are all in different disciplines it might make more sense. Well, let's see we got one engineering, two computing and two maths. This is interesting. Well, they are all pure in that sense, so best I can do, is check and see if there is any relationship between them and their teachers - not sure how much that'll tell me - can divide into hard pure and hard applied - it is the best I can do at this point. I'm guessing that statistics won't be sufficient to explain any relationship so, will have to use almost inductive explanations and looking for relationships - this is terrible work - terrible - wish I had more lecturers and students. Doubt we can do much factor analysis with this kind of data - but we shall see ... all, I can conclude if I do the factor analysis is say that this gives an indication but no conclusive remarks can be made unless there is a larger study.