How I approach learning design — and what it's like to work together.
I start by understanding the learner, the context, and the performance problem — not by choosing tools.
Cognitive science and evidence-based instructional design guide how I create experiences that support real learning.
Learning is more than completing a course or passing a quiz.
I design meaningful practice and relevant feedback so learners can apply new skills — and move toward independent action.
I use AI to make learning more personalized, responsive, and accessible.
From realistic conversation practice to adaptive feedback, the focus is what learners can achieve — not the technology itself.
Every learning experience starts with a clear problem and a measurable goal. If an activity doesn't support learning or performance, it doesn't belong in the design.
I connect theory with practice, drawing on learner research, cognitive load principles, scaffolding, adult learning, and human-centered design to make intentional choices.
I think beyond individual lessons. I consider the entire learner journey, from identifying needs to creating, testing, and improving solutions that can scale.
I use learner feedback, performance data, and evaluation to understand what's working and what needs to change. Good design isn't a one-time deliverable — it evolves.
I believe technology should remove barriers, not create them. I'm especially interested in using AI to expand access to meaningful learning opportunities for multilingual and underserved communities.
I believe the best learning experiences don't just explain concepts. They help people practice, make decisions, overcome challenges, and apply their skills where it matters.
That's the kind of learning I design.
Explore my projects