The short version
Explore responsible AI use in scholarship review and authentic student writing.
Reading my email this morning, I stumbled across this message from the National Scholarship Providers Association (NSPA). What nice things they had to say:
My favorite part?
Led by technology expert Miguel Guhlin, this series gives you the tools to work smarter, not harder.
Ok, that aside, you can BEGIN YOUR JOURNEY with NSPA using this link.
Upcoming Conference
This October, at the NSPA 2026 Continuity Conference, you can catch me in San Antonio, Texas presenting on a session focused on the following:
As generative AI becomes an everyday tool for students, scholarship providers face a double-sided challenge: how to responsibly use AI to streamline heavy application review workflows while simultaneously evaluating whether applicants’ responses are authentically their own. This interactive, 90-minute workshop delivers the core prompting and evaluation frameworks needed to manage both sides of the coin. Attendees will learn the fundamental mechanics of setting up structured AI evaluation models securely and exploring the realistic limits of AI detection.
Session Agenda Breakdown:
**Part 1: The Basics of Structured AI Prompting (~25 Minutes)
- _The Focus:_ Core prompting frameworks to prevent AI "hallucinations" and bias.
- _The Walkthrough:_ Universal mechanics on how to write clear, bounded rules for an AI model so it actually listens and analyzes text based _only_ on the parameters provided.Part 2: Safe AI Integration in Application Review (~35 Minutes)
- _The Focus:_ Speeding up administrative review without compromising data privacy.
- _The Walkthrough:_ A live, step-by-step demo showing how to plug anonymous applicant essays into a prompt alongside a specific rubric to let the AI score or sort them. Crucially, this covers the hard boundary on what info is safe to use and what needs to be scrubbed.Part 3: Dealing with Applicant AI Use & Detection (~30 Minutes)
- _The Focus:_ Managing student AI usage and setting realistic expectations.
- _The Walkthrough:_ A transparent look at the limits and false-positive risks of current AI writing detectors. We'll give them a canvas to help their teams decide on a policy stance and spot highly standardized, non-authentic submissions.