AI marking software

AI marking software for schools and training providers

One platform for rubric marking, handwritten mocks, integrity checks and evidence. Upload work, apply your criteria, review every draft, then publish with professional judgement intact.

  • Rubric-aligned drafts
  • Teacher review before publish
  • Batch cohort marking
  • ICO registered · UK-built
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Category overview

What AI marking covers on Feedback Flows

AI marking drafts grades and feedback against criteria you supply: a multi-band rubric, a board mark scheme, or vocational descriptors. The AI reads essays, structured answers, scanned handwriting and portfolio evidence, then returns a draft for educator review. Nothing reaches a learner until a person confirms it.

A typical run looks like this: a Year 10 English teacher uploads 28 coursework essays and the department’s shared rubric. AI drafts a band per criterion with quoted evidence. The teacher changes two borderline Merit/Distinction calls, softens one comment, then releases the set. The same workflow covers provider KSB evidence and mock exam scripts once you pick the matching tool.

Supported inputs include PDF, Word, text, ordered scan images and cohort ZIPs. Limits: poor scans, ambiguous criteria and low-confidence OCR always need a human look; regulated high-stakes awards stay under your centre policy. Schools: AI marking for UK schools. Providers: training providers. Detail: rubric marking and handwritten exam marking.

Workflow

How AI marking works in Feedback Flows

Built around teacher control and moderation-friendly evidence.

1

Upload

Single scripts or whole cohort batches (PDF, Word, and common formats).

2

Apply your rubric

Use the rubric builder or import criteria your department already trusts.

3

AI drafts marks

Criterion-level comments reference specific strengths and gaps in the work.

4

You review

Adjust borderline grades, tone, and moderation samples before release.

5

Publish & follow up

Export feedback, generate targeted worksheets, and track progress.

See the full toolkit on our platform features page, or explore AI essay marking and rubric marking software.

In the product

Rubric-aligned results you can edit

Criterion-level feedback references the student’s work against your descriptors, editable before anyone sees a grade.

  • Band and score drafts per criterion
  • Personalised comments, not boilerplate
  • Exports ready for internal moderation
AI marking results aligned to a rubric in Feedback Flows

Rubric-aligned AI marking with criterion-level feedback, editable before students see results.

Compare

Manual vs generic AI vs rubric-based AI marking

Approach Speed Consistency Rubric alignment Teacher control
Manual marking Slow at scale Varies by marker fatigue High when done well Full
Generic AI graders Fast High but shallow Low: often ignores your scheme Limited
Feedback Flows AI marking Fast first pass High against your rubric High: criteria you define Full review before publish

Read our comparison article: AI marking vs manual marking.

Audiences

Who uses AI marking on Feedback Flows

Teachers

Cut mock-season and coursework spikes without generic comments.

For teachers →
AI feedback for teachers →
Students and classes →

ITPs & assessors

EPA-ready evidence, audit-friendly exports, outsourced marking options.

For ITPs →

MATs & trusts

Consistent criteria trust-wide with shared rubric libraries.

For MATs →

Schools and colleges: see AI marking for UK schools for GCSE, A-Level, ICO and DPA guidance.

FAQ

Frequently asked questions about AI marking

AI marking uses large language models to read student work, apply your rubric or mark scheme, and draft grades and feedback. Professional educators review and publish the final result.

No. Feedback Flows is designed as an assistant. AI handles the repetitive first pass against your criteria; teachers retain final grading authority and professional judgement.

Accuracy improves when marking is rubric-aligned rather than generic. Teams typically pilot with a sample set, compare AI drafts to human marks, and scale once moderators are confident.

Yes. Upload a cohort, apply one rubric, review batch results, and release feedback when you are ready. Batch marking is core to the platform workflow.

Feedback Flows processes work over encrypted connections, does not sell student data, and does not use submissions to train public models. We are ICO registered. See our UK schools guide for DPAs and governance detail.

Individual educators use pay-as-you-go credits with free welcome credits on sign-up. Schools, ITPs and MATs get a custom quote based on markers, learners and marking volume. Organisation plans are usually cheaper than stacking individual packs, and we offer no-pressure trials.

Essays, coursework, reports, structured exam papers, vocational portfolios, and other extended writing. Rubric or mark-scheme alignment drives quality.

Generic tools produce one-size-fits-all comments. Feedback Flows applies your rubric, supports batch cohort marking, moderation exports, integrity checks, and UK-focused governance expectations.

Under EAL's current AI Position Statement, AI may support assessment provided it is not used in isolation. AI may generate a suggested outcome or grade (for example Pass, Merit or Distinction) for consideration, but the final assessment decision and award must be made by an appropriately qualified and competent human assessor who independently reviews learner evidence and applies professional judgement before confirming the result.

Responsibility for the assessment decision must remain entirely with the human assessor. Every assessment decision informed by AI should be reviewed by the assessor, rather than relying on sampling or quality assurance checks of only a proportion of AI-generated outcomes. AI may inform the assessment process but must not determine the final outcome.

More on privacy and school rollout: AI marking for UK schools · Safe & responsible AI in classrooms

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View pricing → AI marking for UK schools → Compare AI marking tools → AI essay marking → Rubric marking →