From Graduate Coursework to Workforce Strategy: Exploring Mixed Reality in Mining

One of the things I valued most about completing my master’s degree was the opportunity to connect academic work to problems I was actually seeing in the workplace. Rather than treating assignments as purely theoretical exercises, I often tried to use them to explore questions that were relevant to my work in learning, technology and mining.

One of those questions was:

How do you give employees realistic practice when the workplace itself is too hazardous, expensive or operationally complex to use as a training environment?

That question eventually became the foundation for a graduate project exploring the use of augmented and mixed reality for workforce training in mining.

The challenge: practical learning in a high-risk environment

Mining creates an interesting learning challenge. Employees need hands-on experience to develop confidence and capability, but there are limits to how much authentic practice can safely occur in an operating mine. Production environments are active around the clock. Equipment is expensive. Interrupting operations for training has real cost implications. And some situations are simply too hazardous to recreate for learning purposes.

In the project, I identified several barriers facing mining organizations, including the rapid entry of new miners as experienced workers retire, limited opportunities for realistic hands-on practice, the cost of interrupting production and the complexity of delivering training in a 24/7 environment.

So the problem wasn't:

“How can we use virtual reality?”

It was:

“How can we create more opportunities for realistic practice without introducing unnecessary risk or disrupting operations?”

That difference mattered.

Starting with the problem instead of the technology

Emerging technologies can be exciting, particularly in learning. But there is always a risk of starting with a shiny new tool and then trying to find a reason to use it.

For this project, I wanted to do the opposite. I started with the workforce problem and evaluated whether augmented, virtual or mixed reality could meaningfully address it. Research reviewed for the project suggested that simulation technologies could offer advantages in areas such as training efficiency, safety, time and cost, particularly where realistic practice is otherwise difficult to provide. That made immersive learning worth exploring—but it didn't automatically make it the right solution.

Evaluating the technology in context

I used the SECTIONS framework by Bates & Poole to help evaluate potential technology choices. The recommendation that emerged was the Trimble XR10 with Microsoft HoloLens 2, a mixed-reality device integrated into a hard hat.

For a mining environment, some of the most important criteria weren't flashy technical features. They were practical questions such as:

• Can it fit within PPE requirements?

• Is it untethered?

• Can employees use it without creating additional hazards?

• Will it integrate with the organization's existing technology environment?

• Is there external expertise available to support it?

• Is it realistic for the conditions in which our workforce operates?

The project identified the integrated hard-hat design, untethered operation, compatibility with existing systems and support within the mining training ecosystem as important advantages. That was one of the most useful lessons from the exercise.

The best technology isn't necessarily the most technically impressive one. It is the one that fits the employee, the environment and the work.

A technology purchase isn't an implementation strategy

Another important part of the assignment was looking beyond the cost of the devices themselves.

It would have been easy to create a recommendation that said:

Buy five HoloLens units and start training.

But technology adoption doesn't work that way.

The business case considered three major areas of investment:

• Hardware. Multiple Trimble XR10/HoloLens units would be required to support practical training groups.

• Learning development. Immersive technology only creates value if there are worthwhile experiences for employees to use on it.

• Infrastructure. The physical training environment would need to support AR, MR and VR experiences.

The overall estimate was more than $300,000, including approximately $163,000 for device kits, $85,000–$125,000 for two initial learning modules and approximately $50,000 in training-centre upgrades.

Those numbers helped reinforce an idea that has followed me into much of my later work:

Buying technology is usually the easiest part of digital transformation.

The harder work is designing the ecosystem around it.

Thinking in terms of an enablement ecosystem

If this type of solution were implemented, the devices would only be one component.

Successful adoption would also require:

• useful learning experiences

• technology integration

• appropriate training spaces

• user support

• facilitator capability

• operational buy-in

• maintenance and governance

• measurement.

In other words, the real solution isn't “mixed reality.” The solution is the combination of technology, learning design, infrastructure and change required to make realistic practice possible. That is much closer to how I think about workforce enablement today.

What happened with the recommendation?

This was a graduate project and business-case exercise rather than an implemented technology initiative.

A pilot has not been conducted, the devices were not purchased, and I have not yet presented the business case formally to leadership or engaged Microsoft, NORCAT or another partner to pursue implementation.

And I actually think that is important to say. Not every valuable project needs to end with implementation. The value of this work was in learning how to take a workplace problem and evaluate a potential solution from multiple perspectives:

learner experience + safety + technology + operations + infrastructure + investment.

It gave me an opportunity to practice strategic thinking around emerging technology without assuming that innovation automatically equals adoption.

What graduate school gave me that I still use

Looking back, this is one of the reasons I found graduate study so valuable.

The strongest assignments weren't disconnected from my professional life.

They gave me structured opportunities to investigate questions I was already asking at work.

This project allowed me to combine:

• research — What does the evidence suggest?

• instructional design — What would employees actually need to practise?

• technology strategy — Which technology fits the use case?

• operations — What constraints exist in the real environment?

• business thinking — What would implementation actually cost?

Those perspectives don't always sit together in traditional L&D work, but they increasingly do in workforce enablement.

The bigger lesson wasn't about mixed reality

Mixed reality may or may not ultimately be the right solution for a particular workforce challenge. Technology will continue to change. The more durable lesson from this project was a process for evaluating it.

1. Start with the workforce problem.

2. Understand the environment.

3. Determine what people actually need to be able to do.

4. Evaluate technology against those requirements.

5. Consider the entire ecosystem required for adoption.

6. And then ask whether the expected value justifies the investment.

That mindset has become much more important to me than any particular device.

Because good workforce technology strategy shouldn't begin with:

“What can this technology do?”

It should begin with:

“What are we trying to enable people to do better?”