“The most meaningful thing technology can do in healthcare education is remove the noise — so students can focus on becoming great clinicians, and educators can focus on teaching”
1. Can you tell us a little about your background and how you got into the field of IT development and technology projects?
I started out as a developer, so technology has been my entry point from the beginning. Over time, working closely with organisations in the healthcare education space, I naturally moved into a business analyst role as well — because I found that understanding the why behind a system makes you a much better builder of it. Being embedded in an environment like IHNA, where the regulatory requirements are complex and the stakes around student outcomes are real, pushed me to think beyond just the technical execution. Now I sit across both sides — I analyse the business need and I build the solution — and I think that combination is what makes the work genuinely interesting.
2. You have experience in development and IT support. How have those positions helped inform your understanding of how digital platforms are built?
Being on the ground in IT support changes how you think about building things. You see firsthand what breaks, what confuses people, and what gets ignored entirely. That experience made me much more practical when I moved into development. When I’m designing a system now — whether it’s a compliance platform or a student-facing portal — I’m always thinking about the person who’s going to use it at 8am when something’s gone wrong and they need answers quickly. I think a lot of platforms fail not because the technology is bad but because the people building them never had to support them in real life.
3. As a business analyst in technology projects, what do you find most interesting about your work in relation to digital platforms?
For me, the most interesting part is translating messy, complex organisational processes into something that actually works cleanly in a digital environment. In healthcare education specifically, the processes are incredibly layered — regulatory frameworks, clinical placement requirements, student progression rules — and turning all of that into a coherent platform that people actually want to use is genuinely challenging. Right now I’m working across several platforms simultaneously — an AI-powered education pathway tool, a governance and compliance system, HR management, simulation inventory — and what I find fascinating is how each one forces you to think differently about data, workflows, and user behaviour.
4. In simple terms, what are AI-enabled platforms, and how might they be used to improve healthcare education?
An AI-enabled platform is basically a digital system that can learn from data and make intelligent decisions, rather than just following fixed rules. In healthcare education, that could mean a lot of things. One of the projects I’m working on — EduPath.ai — is a good example. It’s designed to help students understand their education and career pathways in a personalised way, rather than giving everyone the same generic information. AI can look at a student’s background, their goals, the qualifications they need, and map out a relevant path for them. That kind of personalisation at scale just wasn’t possible before. Beyond career guidance, AI can help with adaptive learning, identifying students who are struggling before they fall behind, and even simulating clinical scenarios for practice.
5. From a technology standpoint, what are the most important features to include when developing digital platforms for healthcare education?
A few things stand out from my experience. First, the platform has to handle complexity without exposing that complexity to the user — healthcare education involves multiple regulatory frameworks, clinical hours, registration requirements, and the user shouldn’t have to navigate all of that manually. Second, data integrity is non-negotiable. In an environment like nursing education where student records connect to AHPRA registration and clinical placements, errors have real consequences. Third, accessibility and usability — students come in with very different levels of digital literacy. And finally, integration — these platforms can’t sit in isolation. They need to connect with existing student management systems, regulators, and placement providers. That interoperability piece is often underestimated and usually the hardest to get right.
6. How might artificial intelligence improve the interactivity, personalization, or efficiency of learning platforms for students and educators?
From what I’ve been building, the efficiency gains for educators are probably the most immediately impactful. A lot of educator time in healthcare training goes into things like tracking clinical hours, chasing compliance documentation, and answering the same pathway questions over and over. AI can automate a lot of that and free educators to focus on actual teaching. For students, personalisation is the big win. Every nursing student comes in with different prior knowledge, different learning styles, different career goals. An AI-powered platform can adapt — suggest relevant resources, flag gaps, track progress in a way that feels individual rather than generic. Interactivity is the next frontier — using simulation and scenario-based learning that responds dynamically to student decisions rather than following a fixed script.
7. In your experience, how important is the userfriendly design and usability of digital platforms for healthcare students?
It’s everything, honestly. I’ve seen really well-intentioned platforms fail completely because students found them confusing or intimidating. Healthcare students are time-poor — they’re juggling clinical placements, assessments, and personal commitments. If a platform takes more than a few seconds to give them what they need, they disengage. When I’m developing, I spend a lot of time thinking about friction — where does the user have to stop and think? Where do they have to click more than they should? Even the visual design matters because it signals to the user whether the platform respects their time or not. A clean, intuitive interface isn’t just nice to have — it directly affects whether the tool gets used and whether it achieves its purpose.
8. In your opinion, how might AI technology impact how healthcare professionals learn and develop their skills in the future?
I think the shift is going to be from scheduled, static learning to continuous, embedded learning. Right now, professional development tends to happen in discrete blocks — a workshop here, a mandatory module there. AI will make it possible for learning to happen in context, in the flow of work. A healthcare professional dealing with a complex case could have an AI layer that surfaces relevant evidence, flags considerations they might not have thought of, and logs that interaction as a development moment. The simulation side is also going to be transformative — particularly for high-stakes, low-frequency events where clinical staff can’t get enough real-world practice. We’re still in early days, but the trajectory is clear. The platforms being built now are going to form the foundation for something quite different from how healthcare education looks today.