Articles on: Double Marker

Double Marker

Our new assessment system combines AI-enhanced Comparative Judgment (CJ) with traditional marking against a standard mark scheme. This hybrid approach allows departments to conduct full-scale mock exams for English Language and Literature while reducing marking workload by approximately 90%. By merging CJ and AI scoring, schools receive detailed, question-level data and pupil feedback without the traditional administrative burden.

If you are interested in learning more, chat to us or email us at support@nomoremarking.com

How the Process Works

1. Unified Booklet System

Format: Pupils write in specific exam-formatted booklets.
Tracking: Every page features a unique barcode, ensuring the system automatically identifies the pupil and the specific question being answered.
Scanning: Once the exam is complete, booklets are guillotined and scanned back into the system for digital processing.

2. The Hybrid Marking Model

AI as First Marker: The AI uses official exam board mark schemes and CJ logic to provide an initial score and feedback for every pupil.
Teacher Quality Assurance: Staff mark a small, representative sample (typically 5–10 scripts per cohort).
Smart Flagging: The system automatically flags scripts for manual teacher review if the AI struggles—specifically cases with difficult handwriting or unusually short answers.

3. Moderation and QA

Consistency Tracking: The marking interface provides analytics on staff marking patterns, identifying "severe" or "generous" markers to ensure department-wide standardisation.

Key Benefits for Schools

🚀 Efficiency and Workload Reduction

Massive Time Savings: A department can finalise an entire cohort's results by marking only about 30 total scripts instead of hundreds.
Extra Capacity: This efficiency allows schools to run additional mocks (e.g., Paper 2) that might otherwise be avoided due to the marking burden.

📊 Enhanced Feedback and Data

Granular Data: Receive specific marks per question and per paper.
AI-Generated Feedback: Every pupil receives feedback linked directly to the mark scheme criteria.
Cohort Insights: Teachers can record audio notes on pupil work; the AI then synthesises these into a "whole-class" or "whole-cohort" feedback summary.

🛠️ Complete Control

Custom Boundaries: Teachers retain the final say on grade boundaries, allowing schools to adjust the grading "harshness" based on specific cohort goals.

Implementation & Trial Information

Category	Details
Subject Coverage	Currently optimised for GCSE English Language (Paper 1 & 2) and English Literature.
Setup Requirements	A CSV of pupil names is required to generate the unique PDF booklets.
Trial Period	Currently in a trial phase with no cost to participating schools through the end of the summer term.

Updated on: 14/04/2026

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