Artificial Intelligence & Decision-Making
AI fluency, responsible adoption, human judgment, ethical questions, and leading change in technology-enabled organizations.
Teaching Studio
Where ideas become learning experiences.
A working space for exploring technology, designing meaningful learning activities, and turning concepts into things people can use, question, and improve.
More than a collection of courses.
Teaching is about helping people understand how systems work, why decisions matter, and what to do with what they learn. This studio brings together practical projects, instructional experiments, and resources developed around those ideas. Some are classroom-ready. Others are still taking shape.
Areas of exploration
What I'm working with
These themes connect technology to organizational practice, critical thinking, and purposeful learning.
Intelligent Business Analytics
Interpreting dashboards, questioning data quality and bias, evaluating AI-supported insights, and communicating evidence-based recommendations.
Databases & Data Warehousing
Conceptual modeling, relational design, SQL, and connecting sound data structures to useful information and working applications.
Enterprise Resource Planning
Understanding integrated business processes, enterprise information flows, and the organizational choices behind complex systems.
Interactive Teaching Tools
Hands-on labs, simulations, learning activities, and small applications that let learners experiment rather than simply read about a concept.
Emerging Technology Experiments
Text-based AI agents, creative tools, educational games, and other ideas worth investigating before deciding whether they belong in a course.
Teaching philosophy
How learning becomes meaningful
Understand the concept
Begin with the principles, assumptions, and relationships that explain how something works.
Apply it in context
Use realistic cases, authentic problems, and practical tools to turn knowledge into experience.
Question the result
Evaluate evidence, recognize limitations, explain decisions, and remain accountable for the outcome.
From ideas to practice
A studio for things that can be tried.
The most useful teaching resources do more than explain. They create opportunities to investigate, build, interpret, and revise.
- Database labs: explore schemas, write queries, and see the consequences of design choices.
- Leadership scenarios: examine when AI recommendations should be trusted, challenged, or rejected.
- Analytics exercises: turn dashboards and model outputs into defensible decisions.
- Learning prototypes: experiment with simulations, interactive tools, and AI-assisted experiences.
An evolving workspace
Curiosity still belongs in teaching.
This site isn't a fixed syllabus or a promise that every experiment will become a course. It's a place to keep exploring how people learn, how technology changes practice, and how good ideas can become useful experiences.