About
Instructional Designer · AI Strategist · Software Engineer
I'm a problem solver at heart. Whether it's designing a course or streamlining a process, I love the thrill of digging deep, defining problems, and building solutions that change things for the better.
Can break problems down into actionable steps.
I find ways to explain complex problems and concepts understandably.
I know how to help students and stakeholders bridge understanding gaps and relate new concepts to what they already know.
Subject matter experts find me pleasant to deal with, and efficient. I know how to ask the right questions to understand business processes and solution requirements.
Approach
I utilize a "Backward Design" approach called Understanding by Design that begins with understanding the desired transformation, and works backward, defining the "enduring understandings", knowledge, and skills needed to achieve the transformation. UBD focuses on engaging higher-order thinking, and on utilizing assessments that are as real-world as possible (simulation over factoids).
UBD is applied in the Analysis and Design phases of ADDIE. In the Development and Implementation phases, activities are primarily driven by Gagne's nine events, as it provides a solid framework for adult learner engagement. My approach does hit all of the phases of ADDIE, though I actually follow a more iterative "design thinking" process more compatible with the Successive Approximation Model.
When analyzing and defining course objectives, I look for the deeper value that comes from examining the "why" of what we teach.
Approach
AI can build workflows, apps, and agents at lightning speed, but none of these solutions make sense if we haven't taken the time to listen to our users, analyze our processes, and decide (in documented form) how those solutions should work.
Loading detailed requirements documentation into a project baseline, and carefully controlling conversation handoffs to maintain an effective focus on current problems.
AI works more effectively when it is given a series of smaller, well-defined problems to solve.
I conduct clarifying conversations with AI before committing to any build. I prompt AI to ask clarifying questions and identify ambiguities. When faced with options, I collaborate with AI to reach conclusions.
Asking AI to review its own work almost always yields a net gain. Setting up AI agents to review each other's work based on certain criteria yields even better results.
Working with AI requires thinking like a manager — understanding capabilities and limitations, delegating tasks, ensuring results meet standards, reviewing, scaffolding, and establishing automaticity in processes.
AI capabilities and the way we implement them are constantly changing. I embrace that change.