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Four ways Big Data is driving e-Learning design

Four ways Big Data is driving eLearning design

Want to learn to be more mindful? Interested in improving your Spanish? Want to pick up digital marketing to supplement your income? There is a course for that!

Online courses offered by universities, eLearning providers, and employers have made the idea of virtual classrooms popular. Some organisations incentivise their employees to learn - by linking appraisals to the certificates they earn. And learners across age groups have begun to invest in themselves by enrolling in online courses, irrespective of where they live.

Not surprisingly, course designers and faculty responsible for structuring these programs are very interested in improving every aspect of eLearning. With sophisticated authoring tools and LMS (Learning Management Systems) becoming available, eLearning providers are invested in understanding what is working and what is not.

What aspects can they change to improve student engagement and knowledge transfer? This is where Big Data comes into play.

How Big Data lives up to its hype
Big Data has become a buzzword today; its effective use has many implications for eLearning. Let us define Big Data in the context of online learning. Course providers have the opportunity to collect a lot of information about their students with every interaction. For instance, the demographic data (age, sex, geographic location, educational and professional background) for each course taker is available. You also have information about how he/she came to hear of the eLearning program - via ads, social media threads, websites, a referral program, etc. - and you can figure out which device they used to log on, and what browser or OS has been installed.

While the course is underway, information about each student’s progress is gathered. For instance, a course provider can figure out the modules that register highest student engagement, the assignments that cause many to drop out, and the videos or lectures that they watch through to the end, without skipping. Students are also asked to provide feedback at the end of the course. All this adds up to a whole lot of information of different types, gleaned through various interactions, and is together called Big Data.

Now, the real challenge lies in making sense of this mountain of data to create actionable intelligence. How does one go about mining Big Data to generate real insight? We tell you.

1. Choose the Right Learning Management System for your course
On a macro level, rationalising and parsing Big Data may lead you to conclude that you need a new Learning Management System to publish your course. Running analytics can tell you which courses are most popular and do well among your audience. This information can inspire the design of new courses or modules - in related fields.

2. Tweak Course Material and Delivery Mechanisms
Course structure can also be reviewed and tweaked for better engagement. For instance, if you decide to offer a foundational course in your field, and you can ask for it to be a prerequisite, if you find that a large number of all students drop off as the modules tackle more advanced concepts. You may learn that videos that are under 6 minutes in length, and those that end with an interactive questionnaire, do way better than videos that are longer and more unidirectional in their communication. Or you may conclude that using social media platforms, as opposed to your corporate learning website is a better strategy, to teach a particular part of the course.

3. Build New Features and Tweak Existing Ones
You can also gain valuable insights about which technology platforms work best. Are 78% of your students accessing the course on an Android-based platform, on their phones? You may then want to optimise content specifically for mobile-reading. You can take a look at the features that are most-commonly accessed by students. For instance, is the group chat option a favourite with your eLearners? Do they like to bookmark articles or download them for future use? Looking at user behaviour carefully can help you develop features that tackle roadblocks and build new functionalities, specifically for your audience.

4. Be Agile and Responsive
The beauty of Big Data is that the information you need is constantly being collected, and is available immediately. You can therefore put into place mechanisms that continually mine the latest data sets to incorporate learnings and tweak your eLearning programs, to be agile and responsive.

But it is important to know the key parameters you will use to drive these decisions, beforehand. It is therefore critical that you prioritise your goals, put into place robust metrics, use the right third-party or inbuilt analytic tools, and safeguard the data you collect, to gain the most out of Big Data in the context of eLearning.

Contact us at Gaja Digital to guide some of these decisions, and let us help you develop the right eLearning course for your organisation or educational institution.

Preeti Prakash | Journalist

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