About

I'm Chris Andrews — a senior UX researcher with a PhD in learning sciences from Indiana University Bloomington. Across ten years of applied research and four years in industry UX, I've focused on one question in different forms: how do people actually use, learn, and adopt the things we build for them? I also bring a learning-design background: I have built courses and professional-learning programs myself.

The arc

I started as a high school career and technical education (CTE) teacher in Utah. Over seven years I built seven digital-media courses from scratch, wrote my own rubrics, performance tasks, and portfolio assessments, and revised each unit after I taught it. That is where the underlying interest came from: I wanted to understand learning well enough to design for it.

The PhD at Indiana University turned that interest into a research practice — mixed-methods, grounded in evidence, willing to live with uncertainty long enough to surface real patterns. Alongside the research I kept designing learning: I designed the workshops for ALL IN, a statewide assessment-literacy program for Indiana educators, and taught educational psychology to future teachers.

From there I moved into industry as the first UX researcher embedded in Cisco Meraki's Product Enablement team, which ran customer and partner training. The brief was to build a research function from scratch. Over three years I shipped end-to-end studies, built mixed-methods practice into the team, worked alongside instructional designers on formative testing of new training, scaled research infrastructure so non-researchers could run their own studies, and increasingly used AI to extend what one researcher could cover.

I also explore what AI changes about research practice — both as a researcher who uses AI in the research workflow, and (volunteering at Empowered.Vote) as someone who actually ships product features built with AI as my primary development partner. The two angles inform each other.

What I care about

Research that actually changes decisions. I'd rather deliver one study that shifts a real choice than five that decorate the slides for a choice that was already made. Methods serve the question; the question serves the decision. Honest framing of what evidence supports and what it doesn't is non-negotiable.

Outside the technical craft, I care about whether the products and systems we build actually improve human experiences — and about the ethics of how AI gets folded into that. The Foundations of Humane Technology framing has been a useful anchor.

More

Selected work · Resume · Publications and talks (mostly on instructional design, social annotation, and assessment)

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