Hello! You’ve changed the format of the blogs, haven’t you? Yes, we like to mix it up a bit. We thought this might be fun, and not at all derivative.
What are these bonus findings then? Well, it all stems from the fact that this time round we have been given students’ final grades as a percentage, rather than a class. Continuous rather than categorical data. This opens up a whole new world of possibilities in terms of identifying a relationship between usage and grades.
Wait, didn’t you already prove that in Phase 1? We certainly did.
So why are you doing it again? Well, to not-quite-quote a famous mountaineer – because we can. It’s important to be clear that we’re not trying to ‘prove’ or ‘disprove’ results from the previous phase. Those stand alone. We’re simply taking advantage of the possibilities offered by the new data.
And those possibilities are…? Remember Spearman’s correlation coefficient from the last post? Well, we can use that again. As you’ll remember from earlier posts, it’s best to keep continuous data continuous if you can. The first round of the project gave librarians with percentage grades – continuous data – a methodology which required them to convert said grades into classes – categorical data. So we’re outlining this technique for their benefit – it’ll save time AND it’s better!
But if you’ve only got the class-based data… Not a problem! Use the old technique, which is designed for class-based data. This is just about giving people options so that they can choose whatever fits their data best.
Right. Got it. So, what did you find? This might be where you have to take a bit of a back seat, my inquisitive friend.
In fact, we found absolutely nothing to surprise us. The findings echo everything we established in the first phase, and the additional work we’ve done with extra variables in this phase. Figure 1 shows the effect sizes and significance levels for each variable.
As usual, I’ve only reported the statistically significant ones, and they are exactly the same as the ones that were statistically significant in our previous tests. You can see that, again, we’ve found a slight negative correlation between the percentage of e-resource use which happens overnight and the final grade. Once again, I’m inclined to dismiss this as a funny fluke within the data, rather than an indication that overnight usage will improve your grade.
So nothing new to report? Not really. Just a new method (outlined in the toolkit) for those librarians who want to take advantage of their continuous datasets.