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Education

Faster, more consistent grading of handwritten assignments

AI onderwijs assistent, uses AI to read and help grade handwritten assignments, giving teachers back time and making evaluation more consistent.

Client
Industry
Education

AI onderwijs assistent operates in education, where teachers assess large volumes of handwritten work. The organization wanted to reduce the grading workload and set a new standard for consistent evaluation. We worked with AI onderwijs assistent on its grading and assessment process.

95%
Handwriting recognition accuracy in phase 1
3 steps, 1 workflow
transcribe, correct, grade

Challenge

Too much grading by hand

Teachers graded handwritten assignments manually, one paper after another. Every answer had to be read, interpreted and scored by hand. That took an enormous amount of time, especially with large volumes of work. Handwriting differs widely between students, which made each paper slower and harder to assess. Because grading happened in sequence and under time pressure, results varied. The same answer could be scored differently from one assignment to the next. The workload put constant pressure on teachers and left less time for students and curriculum development. AI onderwijs assistent had no scalable, objective way to handle the volume and variety of handwritten work.

Solution

AI that reads and helps grade handwriting

We built an AI grading assistant for handwritten assignments. It reads students' handwriting, supports a consistent evaluation and gives teachers a clear overview of results. It fits into the way teachers already work, so adoption stays simple.

  • Handwriting recognition: turns handwritten answers into text the system can evaluate.
  • Evaluation system: supports objective assessment at scale, across many assignments.
  • Teacher dashboard: shows real-time insights into grading and results.
  • Secure login: each teacher signs in with a personal account, so student work stays in a secure, protected environment.
Human-in-the-loop

Approach

A phased path to AI-supported grading

We built the AI core first, then the system around it.

  1. Handwriting recognition We started with AI handwriting recognition, the foundation for faster and more accurate grading.
  2. Evaluation system We built a scalable evaluation system with a user-friendly dashboard for real-time insights.
  3. Phased rollout We expanded digital assessments and metrics step by step. This kept integration with existing workflows smooth and stable.
  4. Secure access We added user authentication, giving every teacher a secure and personalized experience.
Built by
Noah van PottenNoah van PottenAI Engineer
Roel RotteveelRoel RotteveelAI Project Manager & COO
Hamza LamrabetHamza LamrabetAI Engineer

Impact

More time for teaching

In the first phase, the assistant read handwriting with high accuracy and met its agreed deliverables. Teachers now spend substantially less time on manual grading. The grading workflow is more streamlined, and assessments are more consistent from one assignment to the next. Teachers also report better feedback quality. Because assessment is now scalable and objective, the system can grow with the organization and supports future enhancement phases. The time teachers save goes back into educational quality: more room for students, lesson preparation and curriculum development.

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