AI for Professional Work: Designing a Professional Certificate Course in Applied AI

Faculty Mentor

Travis Masingale

Presentation Type

Poster

Start Date

4-14-2026 11:30 AM

End Date

4-14-2026 1:30 PM

Location

PUB NCR

Primary Discipline of Presentation

Design

Abstract

Eastern Washington University's Professional and Continuing Education department identified a need for AI-focused course material for working professionals. AI for Professional Work was developed in response - a five-week professional certificate course that teaches participants how to evaluate, implement, and sustain AI tools in their actual jobs, not as a conceptual exercise, but as a practical build. The course follows a Build-Govern-Sustain arc. Informed by emerging work on non-linear learning sequences, the course inverts the traditional pedagogical approach - students begin by generating real outputs with AI before analyzing them critically, then progress through structured prompting, workflow construction, governance and validation, and long-term sustainability practices. Each week connects to a single professional challenge the student brings to the course at the outset, creating a continuous t across all five weeks rather than a sequence of isolated activities. The design process surfaced a core tension in AI education: tool-specific knowledge changes faster than curriculum cycles. The resulting course prioritizes durable skills - evaluation, workflow architecture, governance - over platform-specific training, offering a transferable model for professional AI education that prioritizes what students can do after the course over what they knew during it.

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Apr 14th, 11:30 AM Apr 14th, 1:30 PM

AI for Professional Work: Designing a Professional Certificate Course in Applied AI

PUB NCR

Eastern Washington University's Professional and Continuing Education department identified a need for AI-focused course material for working professionals. AI for Professional Work was developed in response - a five-week professional certificate course that teaches participants how to evaluate, implement, and sustain AI tools in their actual jobs, not as a conceptual exercise, but as a practical build. The course follows a Build-Govern-Sustain arc. Informed by emerging work on non-linear learning sequences, the course inverts the traditional pedagogical approach - students begin by generating real outputs with AI before analyzing them critically, then progress through structured prompting, workflow construction, governance and validation, and long-term sustainability practices. Each week connects to a single professional challenge the student brings to the course at the outset, creating a continuous t across all five weeks rather than a sequence of isolated activities. The design process surfaced a core tension in AI education: tool-specific knowledge changes faster than curriculum cycles. The resulting course prioritizes durable skills - evaluation, workflow architecture, governance - over platform-specific training, offering a transferable model for professional AI education that prioritizes what students can do after the course over what they knew during it.