Teaching Philosophy
Students learn technology best when lessons are practical, structured, ethical, and connected to the real decisions people make in the workplace.
Student-Centered Learning
I encourage problem-solving, logical thinking, collaboration, and persistence in every class period. Lessons are differentiated so students with no coding background and students with prior experience both make measurable progress.
Evidence: AI Literacy student routines
Technology Integration
I use Python, spreadsheets, security examples, and AI tools to make instruction practical and career-connected. Computer science should help students see clear pathways from classroom skills to real-world opportunities.
Evidence: AI + Coding lesson artifacts
Assessment & Feedback
I combine quizzes, projects, rubrics, and reflection to evaluate growth and communicate expectations clearly. I also reinforce ethical computing and responsible technology use as core habits for future professionals.
Evidence: Responsible AI coding rubric
Equity & Inclusion
In substitute and interim teaching roles, I prioritize an inclusive environment where diverse learners feel safe, supported, and challenged. Every student deserves access to rigorous and relevant technical learning.
Evidence: Student-safe digital habits activities
How Industry Experience Shapes My Teaching
My technology career taught me that technical skill is only part of success. Professionals also need communication, documentation, testing habits, ethical judgment, persistence, and the ability to learn from mistakes. I bring that perspective into the classroom by asking students to explain their reasoning, verify outputs, protect privacy, and connect each skill to real work they may encounter in computer science, business technology, or health IT.
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