How to Track VR Training Data with Learning Analytics

Virtual reality training in the real world

If you’re like most of us, you’ve delved into the world of virtual reality—exploring cities on Google Earth, playing games with friends, or viewing works of art at the Louvre. But VR can also play a valuable role in your training programs.

VR training is particularly useful for dangerous environments, such as caves or construction sites, or for tasks that are difficult or expensive to practice in real life, such as medical interventions or controlling expensive machinery.

Swimming in a virtual reality data lake sea

Incorporating VR learning experiences into overall corporate training is becoming more mainstream. And organizations implementing VR are moving beyond prototypes and starting to ask how they can track the use of VR to measure its effectiveness and their learners’ performance.

While xAPI is an ideal way to track VR experiences, what exactly should you track? Unlike many experiences where data can be difficult to obtain or access, VR presents the opposite challenge.

There’s a sea of data about the exact position and orientation of a learner’s head and controllers every fraction of a second. So, how do you pull out the most useful details to create meaningful analytics?

What types of VR training data can I track?

You can collect several types of L&D data during VR training, each offering unique insights into the learning process. The solution is to identify and track specific key points in your VR learning experience. For example, these key points might include the following:

• Decision points. Choosing between certain options (e.g., which button to press on a dashboard).
• Tasks. Completing a defined task, such as putting out a fire with an extinguisher.
• Milestones. Reaching a precise point in the experience.
• Events. Significant instances when a learner is expected to respond to particular situations.
• Other actions. Looking at or interacting with other parts of the experience that may not be part of a learner’s core task list.

Think about additional training data capture and decision points for each of these. For example, you’d want to know what decision a learner made and the options the learner has to choose from.

For tasks, it would be helpful to have some measurement of success. So using the example of a fire simulation, you can measure success in how quickly a learner extinguishes a fire while using the correct steps or how efficiently the learner helps evacuate the floor if the fire is too large to contain.

In all cases, it is helpful to know when each key point occurred—capturing when something happened enables you to develop chronologies and patterns. And identifying these patterns can help you predict behaviors based on different circumstances and ensure you have training and resources to support them.

Blended learning realities for comprehensive VR training and reporting

Good virtual reality training is supported by a combination of blended learning resources to prepare for and build on the VR experience.

A combination of blended learning resources supports good virtual reality training to prepare for and build on the VR experience. As you consider what data you want to capture from the experience, also think about how that data will fit with data about the other learning around the VR experience.

The kinds of questions you might ask of your data are:

• Did people who completed more preparatory reading perform better in VR tasks?
• Do people who read the instructions before the experience successfully complete that experience faster?
• Do people who perform better in VR training make fewer mistakes in real life?

How to report on VR training metrics with learning analytics

Finally, when choosing what training experiences to track, think about how you will report on the data. For instance:

1. Which stakeholders will be interested in seeing data from the VR experience, and what information would they like to see?
2. How will you us`make reports and visualizations available to those stakeholders?
3. How will you tie that data into overall learning programs and/or organizational goals?

The future of VR training and learning analytics

As VR training continues to grow in popularity, so will the use of learning analytics to measure and improve learning outcomes. The ability to capture detailed, immersive data from VR training will enable organizations to make data-informed decisions, personalize instruction, and provide targeted interventions.

With the right tools and strategies, VR training and learning analytics can deliver significant benefits—including improved learning outcomes, enhanced learner engagement, and a greater return on training investment.

Don't have any goals or KPIs?

If you don't have a learning program objective or business goal to tie in with your L&D data, then you probably don't need reporting because you don't need virtual reality in your training.

In other words, just because something seems cool doesn’t mean you need it.

So if you don't have a reason to use virtual reality in your training programs, well, don’t.

Your time and resources are probably better spent elsewhere.