At EI Design, we offer a unique framework to predict/measure learnability, or learning effectiveness, of online courses. With an Analytics plug-in, you can validate predictive learnability with users real-time. In this article, I will outline how you can validate the learnability of online courses.
As we know, there is a direct impact of learnability on creating a positive ROI on your training budgets. While the Instructional Design process lays the foundation to create the required learning impact, this approach hinges on several assumptions. Unless validated by the users, we cannot be certain of the learning effectiveness. However, the challenge does not end here. Once we have the user feedback, there needs to be an easy to implement methodology through which the required changes/enhancements/remediation/reinforcements can be applied to the course till we obtain the required learnability. Currently, there are not many frameworks that enable you to validate how the course fared with your users and share the feedback in a manner that you can use to amend your existing learning design.
EI Design’s framework offers precisely this. You can use it to predict, measure, and validate the learnability of online courses.
At EI Design, we have been offering custom learning and performance solutions for nearly 15 years now. With a strong core of Instructional Design, our learning methodologies not only meet learners’ expectations but also create the required behavioral change that the business requires.
In Jan’15, we set up a task force to work with a mandate to create a framework that can predict, measure, and validate the learnability of online courses.
A product of our Innovation Lab, our unique framework is now ready. This enables you to:
Through two of my previous articles, I had provided an overview of our framework and a case study showcasing how you can evaluate the learnability of your online courses. Do refer to my previous articles:
This article focuses on how you can use our Analytics plug-in to validate your predictive learnability.
I share a case study that showcases:
As we know, learning analytics should not be concerned only with gathering data. It should be provided in a manner that you can plan further action. The required action could range from:
This is precisely what we have accomplished. We have an Analytics plug-in to capture data from users. More significantly, it helps you analyze data and take suitable action on the reporting.
The Analytics plug-in extends the core capability of our framework to meet your needs to:
Our Analytics component has been designed to create a robust framework to constantly improve learning, performance, and ROI for the business. It has a data driven approach to address user experience related issues in learning. Specifically, it:
Objectives of the exercise: The selected course is part of our Suite of 10 online courses for generic Compliance. The course was designed in CY’14 with inputs from Subject Matter Experts so the predictive learnability was in place.
Through the current exercise, we set out to:
Activities undertaken in the exercise:
Parameters of the learnability validation exercise and the reports (outcome): Here’s a short video that showcases some of the parameters (that were used to validate our assumptions) and a report that highlights where the existing level of the learning effectiveness of our course stands. The video also highlights how you can apply the user feedback to easily update your approach and enhance the learnability further.
This framework will help you:
While we have done extensive testing of our framework and the methodology, we are very keen to partner with organizations in this mandate. Do contact me if you are interested in signing up to measure, predict, or validate the learnability of your online courses.
This article is one of the three articles on how to predict, measure, evaluate, and validate the learnability of online courses. Do refer to my two previous articles to get the complete perspective:
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