Start with the problem
Technology earns a place only after the educational or engineering objective is clear.
OMLE helps engineering educators, academic leaders, and technology partners develop the judgment to evaluate, adopt, and apply AI and emerging technologies—without the hype or vendor bias.
We don't teach AI so students can use AI. We teach AI so students become better engineers.
Technology earns a place only after the educational or engineering objective is clear.
Evidence, ethics, constraints, cost, and learning outcomes matter more than novelty.
The goal is independent judgment—the ability to assess whatever technology comes next.
OMLE connects real engineering practice with faculty-led education. The work begins by defining the problem, not promoting a product.
Translate technical capability into faculty-relevant courses, labs, projects, and measurable adoption pathways.
Assess academic fit →Design pilots and curriculum around authentic outcomes, responsible experimentation, and evidence of student learning.
Discuss a faculty-led pilot →The OMLE pathway applies engineering discipline to educational adoption. Each stage produces a decision, not just an activity.
Define the educational or engineering problem.
Understand learners, workflow, context, and constraints.
Compare technology options objectively.
Test the choice against evidence and outcomes.
Reflect, measure, improve, and scale deliberately.
OMLE is led by Patrick Kane, an engineering technology adoption strategist with more than 25 years building global university alliances, curricula, hands-on learning systems, and industry–academic partnerships.
OMLE exists to replace technology anxiety and guesswork with curiosity, confidence, and practical action.
Experience reflects Patrick Kane's documented professional record. Named organizations in supporting materials do not imply current OMLE partnerships or endorsements.
Patrick turns rapid technology change into a decision leaders and educators can act on.
Each session is practical, evidence-minded, and shaped around the audience—not a parade of fashionable AI tools.
Develop solution-first thinkers who evaluate evidence, constraints, ethics, and trade-offs.
Build university ecosystems that create durable value for students, faculty, industry, and the workforce.
Move beyond licenses and demonstrations into courses, assignments, labs, and assessment.
Share the event, audience, timing, and change you want the session to create. Patrick will follow up directly about fit, format, and customization.
Tell Patrick what you are trying to improve, who must benefit, and where the technology decision is unclear.
Explore a university partnership, faculty program, curriculum initiative, keynote, or adoption strategy.