This journey map illustrates how I design end-to-end learning experiences that move beyond onboarding and courses into continuous skill development, reinforcement, and in-workflow performance support. It shows how behavioral design, learning science, and AI-assisted guidance combine to support real-world performance.
This representative model is based on my experience designing enterprise onboarding, product enablement, and AI-supported performance learning. It reflects how I design end-to-end learner experiences that align user needs, business goals, and technology into a cohesive learning system.
When learning is not designed around real user behavior and performance needs, learners experience fragmented journeys, low engagement, poor retention, and limited transfer of skills to the workplace. Courses alone do not drive behavior change without reinforcement and in-workflow support.
I design learner journeys using a behavior-first, experience-driven methodology:
Understand user roles, motivations, and performance contexts
Identify friction points and moments of need
Design targeted learning and support experiences at each stage
Reinforce behavior through practice, spacing, and feedback
Measure impact on performance and adoption
User-centered and experience-driven learning design
End-to-end learner journey orchestration
Behavioral design and motivation strategies
Application of learning science (practice, reinforcement, spacing)
AI-enabled performance support and personalization
Journey mapping, persona development, UX design principles, behavioral design frameworks, learning science, AI-assisted personalization, performance support design.