Creating Question-Level Granularity for AI-Driven Item Selection

A UK-based education publisher operating a digital GCSE Assessment Hub needed to restructure legacy assessment content to support item-level reuse, analytics, and AI-assisted assessment workflows. Integra partnered with the publisher to convert multi-part questions into machine-addressable units with consistent metadata and aligned HTML without disrupting platform ingestion or assessment intent.

Discover how Integra helped them to:

• Restructure 238 assessments into atomic, question-level items suitable for digital and AI-driven use

• Create over 1,400 new assessment items by splitting complex multi-part questions

• Replace approximately 2,500 legacy learning outcome mappings with a standardized framework

• Align metadata and HTML to support reliable platform ingestion and automated analysis

• Prepare assessment content for item-level diagnostics, analytics, and AI-assisted question selection