Built by a mathematics professor. For the next wave of Texas math teachers.

A teacher-first approach to exam readiness

Dr. Mienie Roberts is a mathematics professor whose classroom practice sits at the intersection of advanced mathematics and the learning sciences. Her university teaching has focused on helping pre-service and early-career educators move from procedural fluency to conceptual mastery — the same transition the TExES Mathematics 7-12 (235) examination was designed to assess.

QuantegyAI grew out of that work. After watching capable, mathematically prepared candidates struggle with an exam that rewards adaptive diagnosis and misconception repair rather than rote review, Dr. Roberts set out to build something different: a platform that mirrors the way mathematics is actually learned — one targeted problem at a time, with immediate feedback, and with a deliberate loop back to the missing prerequisite whenever a point-losing gap is detected. But she also knew that the best adaptive engine in the world is useless if students don't show up tomorrow. So she wrapped it in a mission system: gamified journeys, XP, combos, and boss battles that make studying feel less like a chore and more like leveling up.

Pedagogy, not product marketing

Every design decision in the platform is anchored in the adaptive-learning and intelligent-tutoring literature. Every question is chosen specifically for the learner's current ability — not too easy, not impossibly hard — so time is never wasted on items that don't move the student's score. When a misconception is inferred, the system opens a short remediation loop on the missing prerequisite and then returns the learner to the original item to verify mastery, a structure supported by the tutoring-effectiveness literature.

The science: a three-parameter logistic (3PL) Item Response Theory model estimates your ability after every response and selects the next item from the region where growth is most likely — the same framework behind the SAT, GRE, and TExES itself.

Engagement is a pedagogy problem

The best question bank in the world is worthless if the student quits in week two. Traditional prep sites are static, text-heavy, and joyless — and the students who need them most are the ones least likely to stick with them. QuantegyAI's mission system was designed to solve this without compromising rigor.

Every session is a mission: a short, adaptive sequence of questions, interactive lessons, and mini-games targeting the student's biggest gaps. One tap starts it. Combos reward consecutive correct answers with XP multipliers. Boss battles combine competencies under time pressure. Streaks, personal bests, and level-up celebrations keep the student coming back. The predicted score — the system's most commercially valuable metric — updates after every session, making progress visible and tangible.

The design principle: the student should almost never need to decide what to do next. Every action should produce visible progress toward passing.

A reviewer's perspective on instructional materials

Dr. Roberts currently serves as an active reviewer under the Texas Instructional Materials Review and Approval (IMRA) process, established by House Bill 1605. In that role she evaluates K–12 mathematics materials against the Texas Essential Knowledge and Skills (TEKS), the English Language Proficiency Standards (ELPS), and state-defined suitability and quality rubrics. That reviewer lens — alignment, quality, suitability, and factual accuracy — is applied to every item in the QuantegyAI bank.

Although QuantegyAI is a teacher-certification preparation product rather than a K–12 classroom resource (and therefore not itself an IMRA-eligible submission), the same standards of evidence, alignment, and pedagogical rigor inform its construction.