ADDIE-Based Course for Medical Professionals
As part of my completed Professional Diploma in Digital Learning Design, I designed a course that applied the ADDIE framework end-to-end—from analysis to evaluation. The project is designed to help medical professionals understand and apply AI tools to improve diagnosis and personalize care. Using adult-onset allergies as a focused case, the course introduces foundational medical knowledge in adult-onset allergies while guiding learners in applying AI tools to real-world clinical scenarios. The submission itself received the highest level of marks (Distinction) and I’m continuing to develop it in collaboration with others to incorporate AI-driven scenario-based learning and assessment.
See the full project submission with details on all ADDIE stages >
Or continue below for the highlights!
My role.
I led the full design and development of the course, from topic selection to prototyping. I created the learning plan, wrote the content, and built a video-based prototype to demonstrate the course experience. While I worked independently, I collaborated with two external advisors—a healthcare subject matter expert and a learning strategist—to ensure both content accuracy and instructional effectiveness.
What I did.
I conducted secondary research on adult-onset allergies and met with advisors to identify real-world challenges faced by medical professionals, particularly around adopting AI in clinical settings. I created personas such as the one below to help focus on the medical professionals who were most likely to seek out this training.
A learner persona developed to ground the course in the real-world needs of medical professionals adapting to AI-assisted care.
Using the ADDIE framework, I designed a modular course that blended foundational knowledge with applied learning and ethical reflection. The learning outcomes were structured across Bloom’s Taxonomy—from understanding allergy types and physiological differences, to analyzing AI-generated data, and creating personalized care plans and workflow strategies.
The course structure mapped across learning outcomes, showing how foundational knowledge builds toward applied AI usage and ethical decision-making. The core experience is largely asynchronous due to the schedules of medical professionals, but supports this with social learning opportunities and optional synchronous touchpoints with instructors and student support.
I explored and integrated tools such as Articulate 360, Powtoon, Camtasia, Notion, and AI platforms like ChatGPT and Claude to prototype a learning experience that’s both grounded and forward-thinking.
As part of my exploration, in addition to the prototype for the class, I created a module using Articulate 360.
See my separate spotlight for the Articulate 360 module.
Wrapping up…
This project pulled together everything I love about instructional design: digging into a real-world problem, structuring content for clarity and impact, and exploring new technologies to make learning more useful and engaging. It was a chance to fully apply the ADDIE model while designing for an audience facing complex, high-stakes decisions—medical professionals navigating both patient care and AI adoption. It also reflects my ongoing curiosity about how learning can empower people at the intersection of innovation and practice.