Learning Architecture
I translate complex source material, standards, competencies, and stakeholder priorities into clear learning pathways, objectives, assessment, and practical implementation structures.
Learning Experiences
I design digital, blended, and facilitated experiences in which learners practice authentic decisions, apply learning in context, and receive feedback they can use.
Implementation & Improvement
I develop facilitator supports, quality standards, professional learning, and evidence structures that help learning work in practice and improve over time.
Translating a complex behavioral framework into a coherent, scenario-based learning system.
Instructional Designer & Learning Systems Consultant • Claude: AI, Design, & Code
The Challenge
The organization needed to turn more than 250 pages of behavioral-framework documentation into a structured learning pathway for B2B and B2C audiences.
The Design Response
I translated the source material into a five-module, 20-lesson architecture with competency progressions, aligned practice and assessment, evaluation touchpoints, and a storyboard and MVP for the first module.
Selected Evidence
Curriculum map and learning architecture
Competency and learner-evaluaton matrices
Module 1 storyboard, MVP, and webinar materials
A multilingual program that helps learners recognize manipulation, evaluate risk, and make safer decisions.
Learning Experience Designer • Articulate Storyline and facilitated learning
The Challenge
Youth and young adults across the Greater Mekong Subregion face growing risks ranging from fraudulent offers to and digital exploitation, yet access to prevention education remains limited.
The Design Response
I designed a complete mobile-first eLearning course around the original S.C.A.M. framework - Stop, Check, Ask, Move - followed by facilitated learning for deeper discussion and complex case analysis.
Selected Evidence
Trauma-informed, culturally responsive branching scenarios
Mobile-first, low-bandwidth eLearning course design
Facilitator ILT, resources, job aids
A guided course that helps employees test generative AI safely, evaluate its output, and make informed adoption decisions.
Learning Experience Designer • Rise 360 and performance support
The Challenge
Access to generative AI does not automatically give employees the judgment to choose appropriate tasks, verify unreliable output, or recognize when additional review is needed.
The Design Response
I designed a seven-lesson guided experiment that moves learners from task selection and safety checks through output verification, workflow analysis, and an evidence-based Keep, Change, or Drop decision.
Selected Evidence
Scenario-based judgment checks
AI Experiment Planner and quick-reference aid
30/60/90-day follow-through plan
I begin with the problem, the people affected, and the conditions in which learning must work.
Look beneath the request. Clarify the performance or learning need before assuming training is the answer.
Learn the system. Work through unfamiliar content, context, and constraints with stakeholders until the problem and shared priorities are clear.
Design for sustainable transfer. Select the right modality and align outcomes, practice, feedback, assessment, and evaluation for application, consistent application, and continued improvement.