About Me
My name is Owen Hayes
I'm a Learning Designer with more than 15 years of experience designing curriculum, assessment, online learning and professional development across schools, government, startups and large corporate organizations.
I co-design learning with SMEs and stakeholders to create practical, performance-based experiences that translate to real work. I’m comfortable working across authoring tools and LMS platforms (including Articulate, Moodle, Canvas and Coassemble).
I bring a mix of educational rigour and technical capability — including building interactive learning activities and simulations with AI tools, HTML, CSS and JavaScript — and I’m always looking for ways to improve clarity, consistency and learner outcomes.
How I Work
Start with the problem, not the solution
Most learning projects start with a solution already chosen. I push back on that. Before anything else, I want to understand what's actually causing the gap, and whether learning is even the right fix.
Design for transfer, not completion
A course that gets finished isn't a success. I design for what happens after: whether people can actually do the thing when they need to. That means realistic practice, relevant context, and less content than you think you need.
Build capability, not dependency
The goal is never a training library. It's a team that performs better. I work with stakeholders to get to the root problem, build the right thing, and make sure it sticks.
Tools & Technologies
Articulate Storyline
Articulate Rise
H5P
Camtasia
Synthesia
Adobe
Coassemble
Canva
Pendo
WalkMe
Canvas
OpenAI
Claude
Moodle
Markdown
HTML
CSS
JavaScript
GitHub
My Approach
The choice of learning experience is always driven by the specific performance outcome and the environment where the skill will be applied. It is common to feel pressure to rush into building courseware in response to external demands, but I believe in first evaluating if training is the best solution for the problem.
For instance, if a customer service team is struggling with a new policy, a 30-minute course might be less effective than a job aid such as a PDF flowchart.
My goal is to identify the most efficient tool for the job, so the final solution provides real value without adding unnecessary friction to the learner's day.
I view SMEs as essential partners, and I work to build a strong relationship so they feel supported rather than interrogated. That usually means bringing high emotional intelligence, clear communication and a structured process to the collaboration.
I guide our work using a methodology like Action Mapping or a Training Needs Analysis: we start by identifying the business problem or performance issue, then map the specific on-the-job behaviours that will solve it, and finally design targeted practice activities.
This approach helps us move beyond sharing information and instead distil expertise into actionable steps that result in measurable performance improvement.
I align evaluation to the original business goals by defining measurable outcomes before any content is designed. While the Kirkpatrick Model can provide a useful structure, I am careful not to over-rely on Level 1 reaction data, particularly end-of-course surveys, as evidence of real impact.
Instead, I prioritise measures that meaningfully predict and support transfer, drawing on research such as Will Thalheimer’s The Learning-Transfer Evaluation Model. This means looking beyond satisfaction toward evidence of remembering, decision-making, task performance, and intent to apply.
For example, I replace generic satisfaction questions with performance-focused prompts that assess confidence to perform critical tasks, clarity about next actions, and commitment to application.
The result is evaluation data that is actionable, strategically aligned, and clearly connected to workplace performance and business outcomes, not just learner sentiment.
Many learning projects fail because they become information dumps rather than genuine learning experiences. Organisations often optimise for content coverage instead of memory, practice and application.
To fix that, we have to shift the focus from what learners should know to what we need them to do on the job.
By designing for practice, feedback and realistic decision-making, learning sticks — and performance improves.
For me, engagement comes from research-backed practice and respect for the learner’s time. Tools and interactivity matter, but they should serve the learning goal — not distract from it.
I rely on established learning theory (for example Mayer’s Principles of Multimedia Learning and Julie Dirksen’s work) to keep experiences focused, clear and effective.
The aim is purposeful practice: learners spend as much time as possible doing authentic tasks rather than passively consuming content.
As an L&D professional with tech industry experience, I consider myself an advanced user of AI tools. While I am a fan of the technology’s potential, I believe it requires a "tight leash" and expert oversight to achieve a high-quality result. I integrate AI throughout my work, from initial strategy to coding bespoke interactive activities, to push the boundaries of what a learning experience can be.
Rather than just talking about these capabilities, I prefer to demonstrate them. This website and several of my portfolio examples were developed with AI assistance to showcase how these tools can be harnessed effectively. Because the landscape is evolving so rapidly, I am currently exploring the use of agentic AI to improve the quality and speed of my work while staying at the forefront of the latest trends. My goal is to ensure that while the tools are cutting-edge, the output remains purposeful, research-backed, and focused on authentic practice.