Capture the student work
Students upload photos, scans, PDFs, or tablet exports from the assignment page.
Handwritten math grading
AI grading for handwritten math that keeps the working visible
Gradenza grades handwritten math from photos, scans, PDFs, and tablet exports without forcing students into typed-answer boxes. The AI reads the working, applies the markscheme, flags uncertain decisions, and gives teachers a reviewable report before feedback is released.
Grading report
Photophone and scan submissions
Methodworking-aware grading
Reviewteacher-visible flags
Audience
Who this is for
This workflow fits math classes where handwritten reasoning is the evidence teachers care about.
Teachers grading notebook homework, topic tests, and worked solutions.
IB Math tutors who need method-mark feedback between sessions.
Schools that want AI grading without replacing handwritten assessment.
Students using paper notebooks, stylus apps, scanned PDFs, or Google Drive files.
Workflow
How handwritten AI grading works
The pipeline treats handwriting capture, OCR, grading, and review as one connected workflow.
Read and structure the working
The system extracts lines of mathematical reasoning and keeps pages attached to the correct question and student.
Apply the marking logic
Gradenza grades against the assignment context, including method marks, accuracy marks, and dependencies where available.
Send decisions to teacher review
Teachers inspect the report, adjust marks where needed, then release feedback and mastery updates.
Use cases
Concrete handwritten math grading examples
Use handwritten AI grading when student process matters more than a single answer field.
Multi-step algebra
A student expands, rearranges, and solves across several lines; the report can identify where the method first went wrong.
Geometry with a sketch
Students can submit a page containing a diagram, labels, and calculations, with teacher review for ambiguous visual evidence.
Exam-style calculus
The grader can evaluate derivative or integral setup, method marks, and final accuracy separately.
Benefits
Why handwritten AI grading is different
Math assessment needs the route to the answer, not just the answer itself.
Students keep natural working
They do not need equation editors or rigid form fields for every step of a solution.
Teachers keep review control
The AI report is inspectable, and final release remains a teacher action.
Feedback becomes analytics
Reviewed results can update mastery maps and topic reports instead of disappearing into a pile of images.
Proof and trust
Trust points for handwritten grading
Handwriting quality varies, so the workflow includes checks and human review.
Submission quality matters
Poor photos can be flagged instead of silently turning unreadable work into unreliable marks.
Source work stays attached
Teachers can compare the report against the original page before releasing feedback.
Built for markschemes
The grading model is designed for method, accuracy, reasoning, and dependency decisions.
Related resources
Related Gradenza pages and guides
Continue into the adjacent workflow instead of treating this page as a dead end.
FAQ
Common questions
Can AI grade messy handwritten math?
It can grade many handwritten submissions, but poor image quality or ambiguous working should be reviewed by the teacher. Gradenza is designed to flag uncertain cases.
Do students need to type their solutions?
No. Students can upload phone photos, scans, PDFs, stylus exports, or Google Drive files.
Can handwritten grading update mastery analytics?
Yes. Once results are reviewed and finalised, they can update topic and subtopic mastery data.
Next step
Try AI grading on real handwritten math
Start with one handwritten assignment and review the report against the original student pages.