AR & VR Learning: Data Requirements for Effective L&D Reporting

So how do you decide what data is important and what’s just noise? And how do you get that data out into your learning analytics platform. This post explores the eLearning data requirements for AR/VR experiences and suggests some of the data questions you could discuss with your vendor.

What are virtual reality (VR) and augmented reality (AR)? 

Virtual reality (VR) is an immersive virtual experience that uses technology to make the user feel like what they are seeing is real. VR uses a head-mounted display to project a slightly different image to each eye, so the picture appears three-dimensional.

It also uses head tracking so the user can look around and navigate a virtual world. For example, Jaguar Land Rover use VR to design and develop their vehicles.

Augmented reality (AR) overlays virtual objects in the real world. You can achieve this by using a head-mounted display similar to those used for VR, but with a transparent screen, so you can see the real world behind images.

You also can achieve this by using the camera and screen of a mobile device to overlay images onto a live video of the real world. For example, Amazon uses AR so customers can preview furniture in their homes before purchasing.

You can use VR and AR in learning to create practical experiences for where:

• real-world practice is prohibitively dangerous or expensive (e.g. medical practice, aircraft piloting, train driving, or military operations),
• travel to a training site is costly or prohibitive, or
• emotional engagement with a realistic experience is an important aspect of the training.

For instance, some auto manufacturers use VR to train car salespeople on new car models and features. Since 3D models of the vehicles already exist as part of the design and manufacturing process, you significantly reduce the costs of producing a VR tour of automobiles.

Furthermore, the immersive nature of the VR training experience helps salespeople become engaged with the content, explore the vehicle, and practice their sales pitch before the new model arrives in the showroom.

AR/VR data requirements and what to ask your vendor

Think about what questions you want to ask of your VR/AR data and design your data capture to answer those questions. For instance, you may want to track specific decision points, tasks, events, or milestones.

It’s also helpful to capture when each point occurred. Knowing when something happened means you can develop chronologies and patterns. And finding these patterns can help you predict behaviors based on different circumstances and ensure you have training and resources to support them.

And while you want meaningful data, you don’t want too much. In other words, don’t try to capture everything.

You can use data about learner interactions within a VR experience to inform you about:

• The Learner: How far did the learner get through the experience? What did they get right and wrong? Are they ready to practice their skills in real life?
• The Task: What parts of the task do learners find easier or more difficult? What are common mistakes that may require further training?
• The VR Experience: Are there any issues with the simulation that block progress or affect the learning? How much is the VR experience being used, and by whom?

MedStar Health used L&D reports like this to identify common mistakes made by learners interacting with their Zoll simulation. Of course, Zoll is not an AR/VR simulation, but you can collect the same kinds of data from any simulation.

Many VR learning experiences are custom built, which is why you should consider tracking requirements as part of the design so you can build them into the project.

Work with the vendor to identify what data you need to capture to answer your reporting questions and ensure the project scope includes testing that tracking with your learning analytics platform (LAP).

If the VR/AR vendor does not have experience with xAPI:

• send them our How to Implement xAPI eGuide as a starting point,
• make sure the data they generate will conform to your xAPI governance policies and processes, and
• be sure to introduce them to your LAP vendor as well.

Not all VR experiences are custom built, however. For example, CenarioVR is a VR learning authoring tool that creates rapid-author VR experiences. You can use this tool to rapidly generate basic VR experiences using 360° videos or images, which you can overlay with e-learning style questions and interactions.

These interactions are tracked via xAPI, so you’re capturing data about the critical decision points in the VR experience by default.

For existing custom-built AR/VR experiences, retrofitting xAPI tracking will mean asking the developer to do more work. It’s likely that this will be more costly than including the tracking in the first place.

The experience may have a mechanism for providing data via CSV—but because of the need to carefully identify the correct tracking data in the VR experience, it is unlikely that any CSV extracts will give the data you need. That’s why you should discuss your requirements with the original developer of the experience and go from there.

For facilitated AR/VR experiences with a trainer where it’s not cost-effective to retrofit tracking, you may be able to use the same tools for tracking a real-world activity. For example, have the trainer use a checklist app to record learner progress, success, and errors as they observe the training in the virtual environment.

AR/VR and your learning ecosystem

AR and VR experiences require specialist equipment. This can be from a simple Google Cardboard-style viewer transforming a smartphone into a head-mounted display to a sophisticated VR headset connected to a powerful computer.

As a result, most AR/VR experiences will not launch from an LMS or LXP. Instead, they will stand separately from the learning ecosystem. This also means AR/VR activities are unlikely to be affected by any changes to the ecosystem.

As the VR/AR experience will likely be accessed using shared equipment—rather than via an LMS or LXP—it is critical that you capture the correct learner identifier for each user and that the identifier matches or can be mapped to identifiers used in other systems. Talk to your VR vendor about how learners can be logged in and authenticated to ensure this is the case.

Like ILT/vILT learning experiences, an AR/VR experience will likely form part of a blended learning experience. For instance, informational content is delivered via video or e-learning course prior to the AR/VR experience to prepare the learner.

And after the experience, learners can take assessments to determine its effectiveness in preparing the learner for the real world. You also can use a checklist app to capture data relating to these assessments.

Combining these datasets enables you to answer questions, such as:

• To what extent does watching the explainer video prepare the learner to do well in the VR experience?
• How effective is the AR/VR experience at preparing the learner for the real world? Do learners who perform better in AR/VR go on to also perform better in reality?

Answering these questions can inform the design of improvements to each element of the blended learning program. This includes content before and after the AR/VR experience as well as the experience itself.

The Role of AR/VR in Skills and Compliance

When AR/VR is used to deliver compliance training, AR/VR forms a critical data source for compliance reporting.

Not only will the data show that learners completed the required training—but because learner interactions within the virtual world are tracked, the data can also be used to measure engagement with the training.

You can use AR/VR data for skills reporting to illustrate which skills learners are spending time developing. This data also can help capture data about learners’ skill levels as learners practice them in the virtual environment before being put to the test in real life.

Up Next: What are data requirements for other L&D tools?

This blog series has covered many of the key learning technologies in your ecosystem. As the series draws to a close, there are a few technologies we haven’t explored yet.

So, to make sure we’ve got you covered, the next post offers an overview of everything you’ve been waiting for—including data requirements for eLearning courses, intranets, assessment tools, games, and custom learning experiences. For each category, we’ll look at the kinds of data you should capture and the questions to discuss with your vendors.