How does Measura work?
Measura follows each student through a four-step loop: it measures, shows the result, turns it into this week’s task for the teacher, and measures the same outcome again once support has been given. Every result comes with its evidence level and uncertainty; the decision is the teacher’s.
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Measure
Measurement happens on screen or on paper answer sheets. In the example, class 7-B takes a short 20-minute assessment on ratio and proportion. Questions are tagged to outcomes and come from a teacher-approved pool.
For mock exams and other paper tests, answer sheets are scanned and read, and results go onto the same outcome map as on-screen checks. Schools with few devices can take part too.
You define your own outcome framework: a national curriculum, international programmes or institution-specific learning goals. It is divided into outcomes and the prerequisite links between them, so a result is seen as a status per outcome rather than a single subject grade.
See
In the example, the outcome looks weak for 9 students. The prerequisite map points to a likely source: operations with fractions from grade 6. That is a likely source, not a diagnosis.
Every result is shown with its evidence level (high, medium or limited) and its uncertainty. When data is thin the system does not draw a conclusion; it suggests a short check that would clarify the picture.
Question quality is monitored too: an item that misleads high-achieving students or draws objections goes to a specialist. If the answer key is corrected, affected results are recalculated and both the old and new records are kept.
Act
A suggestion lands on the teacher’s weekly list, and the teacher accepts, edits or declines it. School leaders see priorities at class, school and institution level in a morning brief; each one comes with its source, time and evidence level.
AI drafts questions and suggestions; it does not publish them and does not assign grades. Scores come from defined calculation services. Identifiable student data is not sent to external AI services.
Measure again
Two to three weeks later the same outcome is measured again with a comparable check. The change is added to the student’s record, and the support given is stored together with what followed.
That lets “what changed after the support?” be answered by comparing before and after. Measurement is there to strengthen the teacher’s judgement, not to replace it.
Mock exams, paper tests and optical reading
Mock exams and multiple-choice paper tests continue in schools and tutoring centres, and Measura does not leave them out. Outcome-tagged answer sheets are designed, scanned and read, and results go straight onto the student’s outcome map.
Reading accuracy is measured by comparing against a manual check of sample sheets, and reported.
Report cards and transcripts
Report cards and transcripts carry an outcome-level growth summary next to the grade and letter grade. Templates adapt to country and school type, and are written for parents in plain language without labels.
Setup options
Cloud: for single schools and tutoring centres. No installation; Measura hosts and updates it. Annual subscription. Hosting location: a data centre within the European Union.
Institution server: for school groups and institutions. Installation and data on your own server. Licence, source code handover and transfer terms are detailed in the enterprise agreement. The choice depends less on institution size than on data policy and operating capacity.
Student, class and subject lists exported from your school management system as Excel / CSV, and optical reader output, can be imported; a direct connection is assessed separately for your institution’s system.
Permissions, security and data
Role-based permissions, two-factor sign-in and an audit trail cover every in-scope screen. Data is kept according to the setup you choose and can be exported in open formats.
How do we start?
The start is a 90-day pilot on a subject and classes you choose. The pilot has four deliverables: outcome mapping, a first report, support carried out and a comparable re-check. Success criteria are written before the pilot; numerical thresholds are finalised together in the first four weeks, once there is first data.
How to read status
Status has two dimensions: level (colour) and direction (arrow and text). An outcome can be “Needs support” and “improving” at the same time.
- Level:
- Proficient
- Partial
- Needs support
- Not enough data
- Direction:
- improving
- no change
- declining