Analytics | Read Write Collect

Replied to Delight 19: Data – Ideas and Thoughts (ideasandthoughts.org)

I guess I’m a numbers guy. I like data and yes, I find delight in data. My phone is full of data. Maybe the key is that I find delight in it but I don’t find all the answers it in. Delight has a bit of a whimsical feel that can sometimes place things in their proper perspective.

Dean, I have actually found myself moving away from reflecting excessively reflecting upon data and analytics. I kind of fear being something of a slave to the data, that I lose sight of my why. For example, there was a time when I looked at how many clicks I got on a post or retweets etc. Like danah boyd, I had become somewhat addicted to stats:

I believe there is a limit to what data can tell us or inform our practice, especially in regards to context and creativity.

In regards to Cricket, I read an interesting reflection from Andre Borovec recently. Although we have a multitude of data at our fingertips, we also need to be mindful how this is utilised.

I think it is like connecting the dots, sometimes this can be positive and productive, however sometimes it can lead to conspiracy theories.

As a side note, I have enjoyed dipping into bits of the Data Smart Schools project. Also have Tim Harford’s The Data Detective on my list of books to read. However, the quote that has left me thinking the most about data recently has been this from Nassim Nicholas Taleb:

Bookmarked Tell Me, Learning Analytics… (Reflecting Allowed)

Learning analytics give us data on student behaviors, but they do not provide explanations for these behaviors, so they do not tell the whole story of the human being, what motivates them, what barriers/obstacles stand in their way. They do not get to the root of lack of engagement.

Maha Bali discusses the limitations of learning analytics and what information is left silent.

Marginalia

Learning analytics focus on observable and quantifiable behaviors that are easy for the LMS to collect. When someone logged in, how long they stayed, which tool they used. We don’t know for sure that if analytics tell me someone watched the same video 4 times… if this means they literally sat and watched it 4 times from beginning to end (though some systems do tell how many mins were watched) but we don’t know if they tried again because their internet connection was bad, or because they were distracted by something happening at home, or something else they were doing on their computer at the same time… we just don’t know. We can know that someone has not submitted their last two assignments. But we don’t know why they didn’t submit them, what kind of barriers they were facing, and how to motivate them in future?