Learning analytics

Learning analytics

Good day!

Today, let's talk a bit about learning analytics. Actually, this topic has been brought up during our interview with the Director of Centre of Teaching & Learning, few weeks before. It is interesting topic be discussed as e-learning has become more common as a medium in learning process. Now, what is learning analytics?

Let's take a look at wiki definition:

"Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs."

There are 4 importance thing here, which are:

-What you need to see

-Which data to be used

-What method/analysis/analytic tools you use

-What you need to do after see the result

The last part is where the process of "understanding and optimising learning and the environment".

An article (http://www.theguardian.com/education/2014/mar/26/learning-analytics-student-progress) share on how an institution, Purdue University even has tools which will give their students warning about their learning performance through colour. The instructors, after told by tool will tell the student to improve when the student got 'red colour' if in high risk such as isolated or not participate at all in online activities. This show the advantage of learning analytics as it tell you what happened (the result) and what you can do. Other benefits, it is true that not only learning analytics help students improve learning performance but also other skills such as team networking or leadership skills, as there are many activities online are in group.

Nowadays there is a lot of tools provided for this purpose. Whether embedded in the e-learning (learning management system) or stand-alone tools. The instructor has wide choice in other to analyse student's performance and then do what is necessary to improve them. However, in other to give useful result, the provider of the analytics tools itself need to consider several things:

-Provide accurate result (involve correct measurement, algorithm and etc)   

-Not all user are tech geek, so the tools must user friendly

-The result patterns or visual graph need to be easily understand (as those result are usually for decision making)

To get the concept clearer, I want to share one example through this video (which I learned from: http://glassclassroom.blogspot.com/2012/12/the-glass-classroom-big-data.html). 

The glass is just the medium and technology which still far beyond achieve, but what need to be focused is how the information needed (result after data being analysed) can appear just in few seconds (yeah, that easy!) and the user can use for their own needs-mobile control, class attendance, energy control, patients status, etc.

If doing analytic by own is uneasy or not enough time, why not establish a department in institution which specialize in providing analyses results required by instructors through phone call or email or one click? (Anyway, this is just bizarre idea)

So, let's use learning analytic tools to learn more effectively and efficiently!