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Driving operational performance through data-informed instructional strategies and accessible digital learning experiences.
About Me
I am a Learning Designer with six years of experience blending mathematical precision with instructional science to build high-impact programs. Using Cognitive Load Theory and accessible design, I build learning environments that support measurable growth, including a 23.3% increase in learner performance.
Learn more about my work below. Let's discuss how we can restructure your learning architecture for high-performance results.
Challenge: Solving for Structural Mismatch
Corporate training environments often rely on rigid, synchronous models that ignore the fundamental realities of human cognitive processing. An operational audit of legacy corporate onboarding structures identified a critical 'instructional mismatch' causing significant workforce drag. To address this, I identified three pain-point areas of traditional onboarding:
Executive Function Saturation: Traditional "sit and stare" sessions force learners to suppress their natural focus patterns. This creates "laptop tacoing," where employees multitask to stay engaged, effectively nullifying the training’s intent.
The Individual Processing Bottleneck: Standard, single-speed lectures force a group to move at the pace of the slowest learner, creating a bottleneck that halts productivity.
Procedural Ambiguity: Information dumps disguised as training create "email fatigue," where employees are overwhelmed by passive documentation instead of receiving targeted support.
Solution: An Agile, Cognitive-Friendly Ecosystem
Applying a systems-thinking approach, leveraging the same analytical rigor I use in mathematical modeling, I engineered a 12-minute asynchronous microlearning module designed to optimize cognitive throughput. Grounded in Universal Design for Learning (UDL) and the Successive Approximation Model (SAM), I leveraged Generative AI to iterate and refine a scalable solution. Through iteration and prompt engineering, I moved away from "AI-default" templates to build a custom digital scaffold.
Strategic Architectural Upgrades:
Cognitive Load Regulation: By replacing passive text with interactive accordions, I allowed learners to control their own information-processing speed, preventing sensory over-stimulation.
Performance-Driven Sorting Filters: Using a gamified, logic-based filter, I forced learners to distinguish between static documentation lookups and active behavioral skill gaps, mirroring real-world decision-making.
Mathematical Modeling of Simulations: I built branching, pixel-aligned sandboxes that test a learner’s ability to prioritize resource retrieval under constraints, applying a logical complexity that ensures retention.
Performance-Based Assessments: Abandoning standard definitions, I implemented mini-scenarios that force learners to solve for real-world constraints, such as managing split-attention in high-stakes environments.
Impact: Measurable Operational Efficiency
By prioritizing cognitive architecture over passive consumption, this framework transformed the onboarding experience from a bottleneck into a performance tool.
Efficiency Gains: We reduced training runtime by 80%, reclaiming critical operational hours for production workflows without sacrificing learning outcomes.
Scalability & Maintenance: By utilizing a tool-agnostic framework and SCORMCloud "Dispatch," we enabled seamless updates across the organization’s tech stack, eliminating manual re-uploads.
Inclusivity by Design: The build exceeds WCAG 2.1 AA standards, ensuring universal accessibility through custom-engineered alt-text and clean type hierarchies.
Key Takeaways for L&D Architects
Design for the Human, Not the Tool: AI should be used for structural staging, but human intervention is required to strip out generic layouts in favor of performance-driven interactions.
Shift from Memorization to Retrieval: In a landscape of shifting policies, training should focus on teaching learners how to find resources independently rather than forcing rote memorization.
Respect Cognitive Load: Move away from high-stimulus gamification; focus on architectural choices that minimize sensory noise and support natural processing speeds.
Case Study: Architecting Psychological Safety in High-Stakes Environments
The Challenge: Solving for Structural Friction
My audit of existing professional development frameworks identified a critical instructional mismatch: training programs often targeted technical skill acquisition while ignoring the foundational psychological barriers—specifically "imposter syndrome" and high-stakes performance anxiety—that fundamentally limited learner adoption and engagement. This structural friction resulted in significant operational drag and low mastery rates, particularly in complex cognitive domains.
The Solution: Evidence-Based Intervention
To bridge this performance gap, I architected an asynchronous, trauma-informed learning ecosystem designed to lower cognitive load and scaffold successful retrieval.
Needs Analysis: Leveraged quantitative survey data to map the intersection between self-perception and technical performance barriers.
Instructional Architecture: Developed a series of micro-learning modules utilizing branching logic and iterative feedback loops to provide low-stakes, high-support practice environments.
Cognitive Load Management: Applied principles of UDL and evidence-based sequencing to strip away environmental noise, ensuring learners focused strictly on mastering the required cognitive pathways.
The Result: Measurable Behavioral Shift
By pivoting from passive lecture-based content to a learner-centered, cognitive-friendly ecosystem, we achieved:
23.3% Increase in Learner Performance: Verified through pre- and post-training summative assessments, mapping mastery of key cognitive strategies.
95% Organizational Adoption Rate: Achieved through tiered stakeholder communications and a scalable, repeatable evaluation framework that integrated directly into existing LMS workflows.
Key Takeaways for L&D Architects
Lead with Empathy, Not Just Analysis: Before architecting the solution, identify the "emotional load" of the learner. In high-stakes environments, technical skills are often hindered by psychological barriers (e.g., imposter syndrome); the design must be trauma-informed to be effective.
Bridge the Stakeholder Gap Early: A 95% adoption rate is not a feature of the module; it is a feature of the communication. By integrating tiered stakeholder updates throughout the build, you prevent the "black box" syndrome where leadership feels disconnected from the learning initiative.
Measure Success through Behavioral Change, Not Just Completion: Move beyond standard Kirkpatrick Level 1 (smile sheets) and Level 2 (quiz scores). Focus on Level 3 (Behavioral Application)—designing evaluation pathways that confirm the learner is actually applying the new strategy in their daily workflow.
Skills
Authoring Tools and LMS
Articulate Rise, Articulate Storyline, Adobe Captivate, Camtasia, Canvas LMS, Coassemble, Genially, GitHub, H5P, SCORMcloud LMS
Design and AI
Canva, ChatGPT, Claude, Gemini
Compliance and Frameworks
WCAG 2.1 AA, Kirkpatrick Model, ADDIE, SAM, AGILE, UDL, Bloom's Taxonomy
Google Sites
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