AI essay marking that follows your rubric

Feedback Flows helps UK educators mark extended writing faster—essays, coursework, reports, and vocational portfolios—without handing over final grading decisions to a black box.

Why teams search for AI essay marking

Essay-heavy subjects create predictable workload spikes: mock seasons, coursework deadlines, and end-of-unit writes all land at once. Traditional marking is thorough but slow. AI essay marking tools promise speed, but many ignore rubrics, produce generic comments, or feel unsafe for moderation.

Feedback Flows is built around a simple workflow: upload student work, apply your mark scheme or rubric, review AI-drafted feedback line by line, then publish. You stay in control of borderline grades, moderation samples, and the tone of feedback students receive.

How automated essay marking works in Feedback Flows

• Rubric alignment — Criteria, weightings, and descriptors you define drive the draft grade and comments.
• Batch or single marking — Mark one essay in depth or upload a full class set for cohort processing.
• Personalised feedback — Comments reference specific strengths and gaps rather than boilerplate paragraphs.
• Integrity checks — Optional style comparison and reference checking for confidence in submissions.
• Exports for moderation — Evidence-friendly outputs for internal QA, MAT reviews, or ITP gateway preparation.

Who uses AI essay marking on the platform

Secondary English and humanities teachers use it for extended responses and mock papers. FE lecturers mark reports and vocational assignments. ITP assessors handle portfolio evidence and EPA-style written tasks. MAT leads value consistent criteria applied across schools while reducing teacher admin.

Responsible use in UK settings

Student work is processed over encrypted connections. We do not sell student data or use your submissions to train public models. Many teams start with a pilot cohort, compare AI drafts to human marks, and scale once moderators are confident in the workflow.