Virtual reality

The Houston chapter of the Association for Talent Development (ATD) had a technology conference in 2018, and Faccini was one of the speakers. He shared the ways virtual reality (VR) is being used today in various organizations. These are my notes from that presentation as well as a report he co-authored on the same topic.

Faccini, M. (2018) ‘VR in the Enterprise: What Works and What Doesn’t’, presentation at ATD Houston Technology Conference 2018. Houston, April 26.

Seaton, H., Faccini, M., and Hallock, S. (2018) VR Learning: A Primer for Learning & Development [Online]. Available at

Outline (of report)

  1. Introduction
    1. Six VR learning scenarios
    2. Six ways VR learning is unique
  2. The basics
    1. What is VR?
    2. What about augmented and mixed reality?
    3. How does VR work?
    4. Creating content
    5. Authoring
    6. Content analytics
  3. VR for learning
    1. Competencies and learning: A first framework
    2. VR benefits
    3. xAPI and analytics
    4. State of the market now
    5. What can L&D professionals do to get familiar with VR/AR now?
    6. Deeper look: Why VR learning works
    7. Assessing VR learning: Second framework
  4. Cases


Faccini is associated with several companies, including Immerse Learning (a British company that created a multi-user VR platform) and AquinasVR (which create VR for corporate training).


Faccini started his talk with a video showing a VR simulation for a pill press machine, which is used by GlaxoSmithKline to train their workers. Was this simulation expensive? Yes and no — I believe Faccini said it cost about £85,000 to make, which is a lot but it is less than what they were doing before (which was flying workers in to train on their spare pill press machine).

He then showed videos of other examples of how their VR platform is being used (some to support learning, others not):

Immerse Learning has a YouTube channel  that shows some examples, although not all that were shown in the conference. Here’s one of their demo videos that shows learners in their real (physical) environment and the virtual environment:

Good candidates for VR, and early entry points

VR can be expensive, but it doesn’t have to be. Evaluate the type of learning and the uniqueness of the skill or behavior to be learned.

Learning physical skills: Learning how to use equipment or other physical skills requires body movement and so in these cases the VR must support interactivity. Thus, the VR should have rendered scenarios. This means the VR experiences are rendered with a gaming engine such as Unity  or Unreal Engine  . This requires a software developer and can be expensive.

VR is notably good for learning physical skills because you can practice the skill many times, and can try out scenarios that would be unsafe in the real world.

Learning behavioral skills: Learning behavioral and soft skills requires seeing faces, gestures, and non-verbal cues; in these cases, the VR may only require simulations (without interactivity). Simulations can be done by filming 360° or even 180° videos, such as you see today on YouTube’s Virtual Reality channel  . These are filmed with cameras such as the Samsung Gear360  . You can’t have interactions with these videos, but they offer realistic video at a lower cost. To have 360° virtual reality videos, you need to use a camera that records two perspectives.

VR is notably good for learning some behavioral skills because it engages emotions. Additionally, due to the Proteus effect (in which a person’s behavior changes due to characteristics of their avatar in a virtual world or VR) people can “put themselves in another’s shoes”.

Other inexpensive options:

Selling the idea

VR experiences have some important benefits.

Presence increases engagement: The learner remains engaged because they are at the center of it. The VR experience is shown from the learner’s point of view and ideally requires them to do things instead of simply watch. Note that to increase presence even more, you should include sound in the VR because it can support the illusion and also drown out sounds of the real world. You should also be mindful that the level of immersion is (in part) dictated by the type of equipment you use. For example, a tethered headset (like Oculus) can provide better graphics but being tethered can limit mobility, while mobile VR (like Google Cardboard) usually have lower quality graphics and don’t usually support hand movements.

Repeatable practice: The learner can practice the same experience over and over again, which helps them learn patterns.

Data: You can assess learning more accurately with VR, because you are assessing real actions instead of answers to multiple-choice questions. You also can collect other data to feed into learning analytics. I felt this was a weaker area of the report: It mentions collecting lots of data in ways that were not possible with SCORM-compliant LMSs, introduces the idea of VR generating xAPI activity statements, and then gives an example of collecting completion data! However, the report points to a webinar about VR and xAPI which may provide more details. There was, though, this intriguing comment:

‘VR learning will increasingly incorporate AI-enabled capabilities like voice analysis to see how learners are performing, gesture analysis, and heartrate analysis to see if, when and how often learners are nervous as they progress through training, and an infinite array of not-yet-discovered measures that will help our people become their best. SCORM was not built to capture this kind of data, which is why the VR Learning community are so excited about xAPI’ (Seaton et al., 2018, pp. 15-16).


See also

The Fourth Transformation: How augmented reality and artificial intelligence will change everything by Robert Scoble and Shel Israel, published in 2017.


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