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Question-level marking
Evaluate pupil responses against the assessment and mark-scheme evidence, producing marks and feedback that can be reviewed in context.
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AI Marking & Analytics
Feedback, marks and class insight from completed scripts.
✦ Teacher-first assessment intelligence
Move from stacks of scripts to the next teaching decision.
EduPaper AI combines AI-assisted marking with question-level feedback, grades and class analytics. The aim is not simply to produce a score faster, but to help teachers understand what pupils have done well, what they have misunderstood and what should be taught next.
Designed around the way teachers actually work
Practical benefits for everyday assessment, independent learning and departmental improvement.
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Class and pupil analytics
Bring marked outcomes together to reveal patterns across questions, topics and pupils rather than leaving useful evidence scattered across individual scripts.
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Teaching insight
Use assessment evidence to inform reteaching, intervention, revision and next-lesson priorities — turning marking data into something operational.
AI supports the workflow; teachers retain professional judgement
The system is built to make assessment evidence easier to process and use. AI-assisted marking can reduce repetitive workload and surface patterns at scale, while teachers remain responsible for interpreting outcomes, checking unusual cases and making the final educational decisions.
Marks with feedback evidence
Whole-class performance patterns
Pupil-level strengths and gaps
Teaching and intervention priorities
Frequently asked questions
Select a question to reveal the answer. Only one answer is expanded at a time to keep the page easy to scan.
A completed pupil script is processed alongside the relevant paper structure and mark-scheme evidence. The marking model evaluates the pupil's actual response and returns marks and feedback at question level.
The marking approach is designed to judge the pupil's actual page images rather than relying on OCR text alone. This is particularly important where layout, workings, diagrams or handwriting context matters.
EduPaper AI is being designed as a broad marking platform rather than a single-subject tool. The quality of marking still depends on the assessment structure, mark-scheme evidence and suitability of the chosen marking configuration.
No AI system should be presented that way. Marking can involve judgement, ambiguous handwriting and borderline responses. EduPaper AI is intended to assist assessment at scale, with teachers able to review outputs and investigate unusual results.
The marking workflow is designed to distinguish genuine pupil evidence from blank or unanswered areas so it does not invent an answer that is not present on the script.
Marked results can be aggregated into pupil and class views, including overall outcomes and question-level patterns. Teaching Insights can use these results to highlight areas for reteaching, intervention and revision.
Yes. Question-level analysis is one of the most useful outcomes of connected marking: teachers can identify common weak questions and use that evidence to shape the next lesson or intervention.
Teaching Insights is designed to compare marked evidence with curriculum or specification information so assessment outcomes can be translated into more meaningful topic and teaching priorities.
No. Schools should retain appropriate professional checks, especially for high-stakes decisions, unusual responses, borderline grades or assessments where significant judgement is involved.
The biggest benefit is connecting stages that are usually separate: processing scripts, applying marks, producing feedback, aggregating class results and identifying teaching priorities. That can reduce repetitive administration around assessment.
Yes. The marking workflow is designed to produce question-level feedback alongside marks, allowing pupils to see where their response met the requirements and where improvement is needed.
Exam Builder helps teachers create focused assessment; AI Marking processes completed scripts; Analytics identifies strengths and gaps; Revision can then provide structured follow-up learning. Together they form a continuous assessment-to-action workflow.
RevisionDirect pupils towards structured follow-up learning.
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Exam BuilderCreate the next focused assessment from reusable questions.
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