Better assessments start with better questions.

My career began in a middle grades math and science classroom, where I cared deeply about my students and believed I was helping them grow. Like many educators, I knew how to teach and how to use the tests and quizzes available to me. What I did not yet understand was how much assessment quality shapes the conclusions we draw about what students know, what they do not know, and what they need next.

That realization came later, during my doctoral studies, in an elective course called "Testing and Grading." I still remember walking out of class embarrassed by how much I had not known while I was teaching. I was not careless. I was not uncommitted. I simply had not been taught.

Since then, I have been on a mission to help assessment creators do that work better and with greater confidence. I have trained K-12 teachers and administrators, future and current college faculty, and subject matter experts writing high-stakes certification exam items in education and medical fields.

Across those settings, the pattern is consistent: people are asked to create assessments that shape important decisions, but most have not been given a practical toolkit for doing that work well.

When AI tools made test and quiz generation faster, the promise was obvious. So was the risk. Questions could look professional while still being unclear, misaligned, or weak measures of learning. Archaine was created to bring psychometric expertise into the process from the start — and to build it with people who could turn that expertise into a real product.

Roger leads the engineering behind Archaine's item-generation technology — the system that turns course content, standards, and certification blueprints into psychometrically structured draft items in under 30 seconds.

What drew him to Archaine was a familiar pattern from past projects: capable people burning hours on manual, repetitive work that software could do faster and more consistently, without asking them to trust a black box. He wanted to build the AI-assisted layer that speeds that work up without hiding how it works. draft — replace with Roger's own account

Zenobia built the SME review workflow that keeps human judgment at the center of every assessment Archaine helps create — the approval, feedback, and refinement loops that turn AI-generated drafts into assessments teams can stand behind.

She's seen firsthand how easily a good idea gets lost without a clear process behind it, and she was drawn to Archaine's insistence that speed and human oversight not be traded off against each other — that the workflow itself should make rigor the easy default, not an extra step people skip under deadline. draft — replace with Zenobia's own account