One of the most common questions in VR training is what to include.

What features do we need?
How much detail is required?
How closely should it match the real world?

A more useful question often comes later - sometimes too late:

What can we leave out without harming the learning?

In immersive learning, subtraction is not a compromise. It is often where clarity comes from.

VR training does not need to show everything

VR training simulations make it technically possible to include almost anything.

Every tool.
Every object.
Every possible scenario.

The problem is that learning does not improve in proportion to detail. At a certain point, additional information stops helping and starts competing for attention.

Effective VR training focuses on what matters in the moment. It reflects how people operate in the real world, where attention is selective and decisions are made under constraints.

If everything is present, nothing stands out.

Accuracy is not the same as usefulness

There is often pressure for virtual reality training to be completely accurate.

From a technical or compliance perspective, that makes sense. From a learning perspective, it can be misleading.

Accuracy describes how closely something matches reality. Usefulness describes whether it helps someone act differently.

A perfectly accurate environment that draws attention to irrelevant detail can be less effective than a simplified one that highlights the right cues.

This is where realism needs to be handled with intent. The aim is not to recreate reality in full, but to create a situation that feels believable enough to support learning.

That balance is explored further in [Internal link - When realism gets in the way of learning].

Leave out information that does not influence decisions

One practical way to decide what to remove from a VR training simulation is to look at decisions.

Ask:

• What decisions is the learner expected to make?

• What information do they need in order to make those decisions well?

Anything that does not support those decisions is a candidate for removal, abstraction, or background treatment.

This does not mean hiding complexity. It means organising it so that the learner’s attention is not pulled away from the judgement you want them to practise.

This principle sits at the heart of decision-led immersive learning, explored further in [Internal link - Designing VR training around decisions, not steps].

Not every real-world variation needs to be included

Real-world environments are messy. Conditions vary. People improvise.

It can be tempting to mirror all of that variability in VR training, adding multiple edge cases and branching paths to cover every possibility.

In practice, this often reduces learning depth. Learners skim across scenarios rather than engaging meaningfully with any of them.

Effective VR learning design usually focuses on a small number of representative situations and allows learners to explore consequences within those constraints.

Breadth can always be added later. Clarity is harder to recover once it is lost.

Prompts, overlays, and explanations

Another category worth scrutinising is instructional overlay.

Text prompts, highlights, arrows, and explanations can be useful, especially early on. But when they dominate the experience, they often signal that the environment itself is not doing enough work.

If learners need to be told where to look or what to notice at every step, the simulation may be over-designed.

Where possible, it is worth asking whether a cue can be made visible through the environment, sound, or outcome of an action rather than an explicit instruction.

This is part of a broader approach to designing effective VR training experiences, discussed in [Internal link - How to design effective VR training experiences].

Fewer scenarios, clearer learning

There is a natural desire to maximise value by including lots of scenarios in a single VR training experience.

More scenarios can feel like more coverage. In reality, they often dilute learning.

Learners benefit more from spending time understanding why a decision matters than from briefly touching lots of situations without reflection.

Leaving out lower-value scenarios can create space for deeper engagement with the ones that matter most.

A useful rule of thumb

A simple way to test whether something belongs in a VR training simulation is to ask:

If this element were removed, would the learner still be able to practise the judgement we care about?

If the answer is yes, it may not need to be there.

This is not about minimalism for its own sake. It is about intentional design.

Less content, more confidence

The most effective immersive learning experiences are rarely the most complex.

They are the ones that help learners recognise what matters, make decisions with confidence, and understand the consequences of their actions.

Leaving things out is not a failure of ambition. It is often a sign that the learning goal is clear.