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The Top Reasons Why Analytics Is Important For eLearning

In the latest instalment in our eLearning series, we sit down with Summit’s Managing Director – Matthew Lambert about his take on the top reasons why analytics is crucial for eLearning best practice.

How can learning-specific analytics improve design and development in eLearning?

Understanding the behaviour and development of your learners is an extremely important aspect of instructional design. It allows us to create beneficial eLearning experiences in order to equip learners with the best possible framework in which to achieve their goals and objectives. Without analytics, we will struggle to adequately determine what works and what doesn’t – it therefore allows us to adapt and evolve more readily.

What are some of the basic tenants of learning analytics?

Essentially, learning analytics are collections of data sets that’s gathered while learners are engaged in any eLearning experience. Key metrics that we measure are scores achieved on a particular test or exam, how quickly learners worked through the content, how many times they logged in and participation on discussion boards, to name a few. Some key insights also come from the amount of time learners visit a specific piece of content , for instance where we see a high volume of viewership on a specific piece of content and a low assessment score we know this is a concept that learners battle with. This allows our facilitators a birds-eye view of areas which they may need to focus more on in order to help a learner progress and the data can also be used to make educational predictions and analysis to ascertain what learning materials are best-suited.

Why are learning analytics so vital for continuous improvement in eLearning?

If I had to distill the importance of analytics in successful eLearning programmes, I’d have to point to the following:

  • It helps us to predict a learner’s performance which further aids us to develop very bespoke and highly engaging eLearning programmes in future, based on past performances which the metrics will show us.
  • We can personalize the learning experience since the data shows us meticulous detail about each learner, their understanding of the material and engagement thereof. No two learners are alike and we find that we get the best results from learners when the material is adapted for them.
  • It helps to improve future learning programmes which is invaluable in terms of time and resources, especially in tough economic climates. Furthermore, we can offer our customers a better service because we’re able to understand and mitigate potential risks which invariably saves them time and money.
  • Boost in cost efficiency, as I’ve already alluded to – the more informed we are and the more factual we get in terms of basing business decisions on analytics, the better able we are to save costs which benefits us a service provider and our customers.

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