DALMOOC – Catching up!

I have joined a new MOOC, but this is not the best start for me. When I heard about the course a week ago it had already started. And I did not get around to work seriously with it until this week end. But here I am, a student of «Data, Analytics, and Learning» offered by UT Arlington. The catch up has started!

The course invites the participants to interact on many platforms inside and outside of EdX, and to be fairly independent of a syllabus and instead base themselves on social/peer learning. That is very exciting, but another reason why catching up does not make all that much sense in this course. All the more reason to get through the introductory lectures and assessments fast, to get to where everyone else is. I guess that is where the social learning takes place.

Actually the first competency was a bit of a challenge for me. I am supposed to identify tools online that are commonly used in Learning Analytics. This field is so new to me that I am not even quite sure of what it is yet. Of course I see analytical tools in use all around me. For example, earlier today I logged my workout from this morning in an online Crossfit log service. Besides me using it for my own purposes this data is being «mined» for insights that the company uses to write blog posts about the best work out practices. As a teacher I have also seen how performance data from my students can be a good corrective that helps me help them in their learning. But that can hardly be regarded «big data», and my use of those data is all but automated.

In my searching for analytical tools online, i came accross one that looked promising to me: Scrapy is a tool for extracting data from websites. I guess we could call it datamining? I also found NodeXL: a free, open-source template for MicrosoftExcel, that helps to build and explore network graphs.

However, the natural focus for me now, would be on the tool that we will use for the first couple of weeks in this mooc: Tableau. And by doing that experience more of the whats and hows of Learning Analytics.


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