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10 ECTS project - Contribution 1
Hi,
What exactly is expected to be in the first contribution?
I updated the project slides on StudOn for this question.
We expect you to show some progress, that is, intermediate results.
Over the deliverables, you’ll be rewriting the different sections as you deepen your insight/work.
The process I’m about to describe applies to confirmatory research. For exploratory research please make use of the resources I’ve given you about grounded theory and/or case studies.
After writing the related work section, you should have some idea of what the answer to your research question might be. This is then written as one or more hypotheses. Each hypothesis should be a discrete, testable statement. For instance, here is an example which I’ve paraphrased from a student thesis. In this example I haven’t put it in the style you would normally use, because I want to show the underlying logical structure more clearly.
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- Self-study is the least effective method of learning (Grundmann, 2011).
- Free and open source software developers feel that workshops and other formal training courses are the least effective ways of acquiring software development skills (Glott & Ghosh, 2005).
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Therefore, I think there is a difference between the learning techniques favoured by free and open source software developers and the general population, with free and open source software developers favouring informal training methods.
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[color=blue] - Knowledge in self-organizing and self-learning communities such as free and open source software projects is usually acquired through “learning by doing” (Glott, Meiszner & Sowe, 2007).
- In a similar type of community (Wikipedia), the key contributors appeared different from casual contributors from the onset (Panciera, Halfaker & Terveen, 2009).
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Therefore, I think that any difference in learning techniques favoured by free and open source software developers and the general population can be attributed to fundamental differences between free and open source software developers and the general population, not self-reporting bias or other factors.
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Rewriting the first conclusion as a hypothesis, I might arrive at: H1: Free and open source software developers are more likely than the general population to prefer informal training methods.
The next step would be to set about trying to prove the null hypothesis - the opposite of my hypothesis. If my research shows that there is no substantial difference between the general population and free and open source software developers in terms of the training methods they prefer, or if it shows that there is a difference but that free and open source software developers are less likely to prefer informal methods, my original hypothesis is rejected. If the null hypothesis is rejected, my original hypothesis is validated.
Results, expected or not, usually give you food for thought and help you refine your research. “I didn’t see any difference between the free and open source software developers, but my sample might not be representative of free and open source software developers. I should see if there are any differences between my sample and the public FLOSS 2014 data set.” (Admittedly this example question is something you probably would have considered earlier, but hopefully it gives the general idea. You shouldn’t of course ignore your results and look around for ways to get the answer you want, but you should try to explain them.)