Prediction is useless until a teacher knows what to do next.
An AI-assisted teacher dashboard turning learning diagnostics into daily classroom decisions for US K-12 educators.
Teachers were teaching and configuring software built for someone else
Existing LMS dashboards treated teachers as data-entry clerks. The product opportunity was not more data. It was a dashboard a teacher would actually want to open in the morning: reduce interpretation work, expose the next useful action, and keep the teacher in teaching mode while the system does the bookkeeping.
The design was grounded in teacher and administrator research and prototype testing conducted during the contract; the case study stays on the interface decisions that research shaped.
The product had to answer more than one kind of urgency
- Class signal. A fast answer to how the class is doing without turning the morning into chart interpretation.
- Student attention. A way to spot students trending in the wrong direction before they slipped further behind.
- Assignment state. A coherent picture of work across grading, submitted, and not-yet-due states.
- Roster setup. An onboarding flow that did not require an IT ticket before a teacher could start.
The journey map ran from logistics back to teaching
The research connected what teachers said they were trying to do with what they were actually doing, and where those two things conflicted. Teachers said they were trying to teach, but the tools kept pulling them into logistics. Dashboards surfaced information that did not lead anywhere; the design work was making information actionable so the same screen could answer what changed, who needs help, and what to do next.
Every surface had one rule: make the next decision visible
Assignment management became a board with clear states (needs grading, in progress, not yet due). Classroom setup became a Clever roster sync: pull rosters automatically, surface reconciliation conflicts in plain language, give teachers a single approval step. The information architecture followed the work teachers were already trying to clear.
The dashboard leads with the student, not the average
The design emphasis sat on per-student action rather than class-level charts: surface the next useful decision first, let the class view summarise, and let the student view lead.
Closing thesis
Model output only matters when the interface makes the next action obvious. Reduce uncertainty, surface urgency, keep the teacher moving.
