As LAK11 starts to ramp up (for me at least, I”m a few days behind) I thought i would take a shot at being a useful helper/facilitator for the course. My hope during this six weeks is to give a tad more guidance than i normally would in an open course and provide a safe place for discussion from people who might not know much about learning analytics, who might be new to an open course, or who are just slackers like me.
A few words on being the ombudsman
While we were talking about the roles that each of the five facilitators could take up during this course, i suggested that a voice for newbies might be useful. A person who could respond to “uh… what the xxx are they all talking about” style questions, and who could feel frustrated and confused right along with you. The simple fact is that while i’ve dabbled with LA, I’m not exactly a luminary on the subject. I’m going to be learning along with everyone else… which is why i signed on.
So feel free to ping me on witter (@davecormier) or connect with me some other way if you’re wondering what you’re supposed to be doing in this course, what a ‘hunch’ is or to complain that you can’t quite figure out what George is talking about.
I’m thinking of providing a common list of cheater options for each week, an article to skim to get a vague idea of what’s going on, a description of what i did with one of the activities and maybe some other thoughts as the week goes on. we’ll see.
Week 1 – skimming
My skimming suggestion this week is the article by Tanya Elias http://learninganalytics.net/LearningAnalyticsDefinitionsProcessesPotential.pdf. It has awesome skim potential. It’s well layed out, with titles that identify whether or not you need to read that particular part of the article. It gives you a nice background of the bits and pieces that learning analytics has grown out of and also, the potential to skip right along to the page 4 section that describes analytics… culminating with this very nice quote by dawson (also computers page 11 and theory page 14)
Although it is now accepted that a student’s social network is central for facilitating the learning process, there has been limited investigation of how networks are developed, composed, maintained and abandoned. However, we are now better placed than our predecessors to use digital technologies for the purpose of making learner networking visible…. network- poor earlier in their candidature, it becomes possible for them to make timely and strategic interventions to address this issue. (p.738)
You might very well skim this article and then decide that it’s worth the full read. ’cause it is.
This week’s activity
Hunch is pretty painless. No excuse not to be a star this week and do the activity. It gives a little window into what analytics are all about and is kinda fun to boot. I recorded myself doing it. If you just want to hang back and cheat over someone’s shoulder… be my guest.
This week’s presentation – John Fritz
It is an introduction to learning analytics. The sound is nice and clear… which is always important. It’s a nice introduction to a part of the field. Something you could easily turn on and run on your desktop while you’re working on your assignments. http://www.learninganalytics.net/?page_id=71
- I found it really helpful.
- It’s focused on Learning(course) Management Systems
- If you’re an analytics ninja, you might want to go back to doing your weird code stuff.
- Includes a use case of ‘why learning analytics’
Bottom line? Wanna sound smart at your next meeting on this topic? Watch this presentation, take notes so you can refer to the articles he talks about.
Is this useful?
If I get some sense that this is useful, I’ll do one of these every week during the course. I’ll also take feedback collected from this blog post and bring it to the friday sessions if people like?
Need stuff added? Stuff here that isn’t useful? Let me know.