How Predictive Analytics Improves L&D Decision in eLearning

16Sep

If only there was a crystal ball that could predict the future of the organizations, the business decisions taken would always hit the bull’s eye. The new age crystal ball in the world of technology is the predictive analytics that can help employers take strategic decisions such as company should hire which candidate; which sales employees deserve to become team leaders; if learners will engage with the simulation in eLearning or they should develop a serious learning game instead; if it is worth sending a manager to an MBA program and so on.

When organizations implement predictive analytics in LMS, it can do wonders. This statistical technique is capable of creating a new paradigm in the eLearning industry. If your Instructional Designer is measuring the ROI of your online training program, he must have warned you already of the ineffective learning. Following are some of the typical reasons for the ineffectiveness of your existing LMS –

  • The learning content is irrelevant to the training goals of your employees
  • There is no scope to apply innovative features to expand knowledge
  • Employees are not taking the required course to hone their skills
  • Lack of managerial support
  • No priorities are set to complete the course

Predictive analytics in eLeanring or Predictive Learning Analytics (PLA) can help organizations identify these issues and mitigate these learning gaps to make your online corporate learning programs more effective with regards to changing job behaviors. This advanced analytics can take your Learning Management System to the next level. This technology lets you understand what is likely to happen by predicting your learning audience’ future success.

Predictive analytics in eLearning leverages digital transformation technologies including data mining, predictive modeling, and machine learning to identify and measure patterns in learning data and theorize future behaviors of your employees. It also greatly helps them to avoid, for example, applying what they’ve learned based on past trends.

Unlike any other metrics, Predictive Learning Analytics is more effective as it focuses on the individual learner, rather than the LMS as a whole. This makes predictive analytics hugely influential in addressing the issues causing ineffective learning. It enables the managers to determine the progress made by the employees in their courses. This technology helps the company understand how well the employees have benefited from the eLearning courses and if they are going to implement the acquired knowledge in their jobs.

How to use predictive analytics in eLearning?

Predictive analytics in eLearning works best when each of the stakeholders including learners, instructors, managers, and course administrators are actively engaged. In this post, we offer you some of the surefire ways your organization can apply to transform your existing LMS by eliminating the ineffective eLearning strategies.

1. Keeping learners in-the-know

The basic way of avoiding failure of your eLearning program is by cautioning your employees when they’re at risk. Purdue University is using Course Signals in their LMS that uses symbolic traffic lights as an assessment mechanism to enable learners to know how they’re performing. The red light shows they are risk and green denotes they are on the track.

Empowering employees through predictive analytics in eLearning enables them to improvise their learning and develop positive habits that will carry over into their daily work tasks.

2. Early intervention for instructors

Instructors can be warned by leveraging dashboards that identify trends to enable early intervention. For instance, predictive analytics can empower applications that can notify instructors of at-risk learners and make recommendations for intervention. There are also tools which let you see how individual employees are performing as compared to their counterparts and monitor their progress accordingly.

3. Notifying managers

Managers should always be notified and aware of their employees’ online training progress. They need to know if any learner is displaying any signs of ineffective learning. With the help of predictive analytics tools, notifications can be sent to the managers so that when employees implement their acquired knowledge in their jobs, managers can monitor their work and check out if the learning isn’t being applied.

4. Developing eLearning courses

Predictive Learning Analytics can also help organizations drive corporate training strategies by helping the employers roll out a map for strategic eLearning course for the new hires and veteran employees alike. Using these analytics data, companies can develop an effective eLearning program that progressively empowers new employees with refresher modules or advanced training as they continue their work at the company.

Here is another excellent article on how to measure the ROI of your LMS

How to set up predictive analytics in LMS?

There are three basic steps you can adopt:

  1. Create an in-house eLearning solution that’s customized to fit your specific purposes for PLA.
    Bear in mind that developing your own tool requires a long-term commitment to maintenance, troubleshooting, and continual improvement. Be sure you’re able to invest the resources into this kind of project before you begin.
  2. Purchase an out-of-the-box solution.
    These tools are faster to implement than a custom solution, but costs can accumulate when you need to integrate with other applications. Customization is minimal, and security updates can be infrequent.
  3. Invest in a collaborative system.
    In some cases, several organizations work together to build a PLA system, but usually, this is limited to academic institutions rather than corporate organizations.

Once you’ve implemented your predictive learning analytics solution, you’ll need a way to intervene. An intervention is any action that is designed to improve outcomes for a learner. An intervention can be passive or proactive and can be automated or manual. In either case, it should have a specific goal and be measurable, so that you can evaluate its effectiveness.

If you are looking for the right eLearning solution that encompasses the fastest and easiest way to ensure your organization stays ahead of the curve, predictive analytics is the one you should not ignore. To know more about this you can contact us here.