I don't have a clever title: #IVMOOC Week 6: Networks03 Mar 2015
I’m in Boston, in the middle of training for marking of the Critical Thinking Assessment Test. The training is good, and their process is solid. Put that on top of a decent reliable and valid instrument and you’ve got something. I’ll need to see the results and the data to draw more conclusions, but so far I like it.
Anyways. #IVMOOC. After the midterm frustration, I encountered more on the self-assessment quizzes. Less about the actual quizzes, but more about the discrepancies between the content in the online course, and the content presented in the book. Having these two contradictory resources isn’t a good thing, and confuses students and makes assessments inaccurate. Am I wrong because I didn’t get the concept, or am I wrong because I was taught the incorrect information. When I did the quiz, I checked my answers by recreating the network in SCI2 and running the Network Analysis tool. The answers given by the tool were incorrect. So, I could be doing it wrong, using incorrect theory, or misapplying the tool. I really don’t know which one is true. I think it’s a bit of all 3. Either way, the instructors should take note of this and make sure that these errors are addressed in future versions.
The assignment was a different flavour of network, which holds a lot of implications for future use. I fully intend to keep pursuing these techniques with different data sources, as it is a unique way to show the collaboration and impacts of scholarly work. I really think using this in the context of an institution or a historical view of a conference is very useful and informative for many stakeholders. My co-occurence network involved Carl Wieman and the NSF database, shown below:
I’m really looking forward to the projects. The comic book fan mail database really appeals to me, from my love of comic books and some ideas that I have about the utility and potential impact of visualizations. If anyone wants to team up, let me know!