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!
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