TREN

Educational content · Structured operations with high record volumes

AI System for Reviewing Course Content Accessibility

The accessibility editor sees the PDF, video transcript and checklist together before deciding whether the content is ready for publication. The system flags missing descriptions and suggests corrections; the editor selects the final wording that preserves the meaning of each formula.

Representative accessible content panel with a work queue, checks and an audit trail: accessibility remediation queue — **Accessibility remediation queue** Representative interface — contains no real data. Course and provider names are coded. The panel does not publish content; editor approval is required.

The problem

When the course PDF, video transcript and checklist are held in different sources, staff must match the fields manually before preparing the draft accessibility corrections.

The accessibility editor must compare every suggestion in the draft accessibility corrections with the source record; missing or conflicting evidence must not replace the final decision.

If a formula that cannot be described through simple alternative text is not routed for separate review, the resulting description could distort its technical meaning; the record must not proceed without a human decision.

What we set out to improve

Time taken for the draft accessibility corrections and their supporting evidence to reach the accessibility editor for review
Resolution outcomes for records routed to human review because a formula cannot be described through simple alternative text
Number of suggestions corrected after identifying the risk of a description distorting the technical meaning

How the system works

01 Retrieve the course PDF, video transcript and checklist from authorised sources
02 Verify field and document versions
03 Prepare the draft accessibility corrections with their supporting evidence
04 Check the exception: a formula cannot be described through simple alternative text
05 Have the accessibility editor accept, correct or reject the output
06 Decision gate: whether the content is ready for publication
07 Record the decision and source separately

Methods we used

A source-identified data schema for the course PDF, video transcript and checklist
A structure that separates deterministic rules from AI suggestions
A screen showing the draft accessibility corrections alongside their supporting evidence
A human review queue for formulae that cannot be described through simple alternative text
A record identifier that prevents duplicate processing

Where people stay involved

The accessibility editor compares the draft accessibility corrections with the source record. If the exception condition occurs, the workflow stops because a formula cannot be described through simple alternative text. The accessibility editor decides whether the content is ready for publication.

Data and security

Only the necessary fields from the course PDF, video transcript and checklist should be processed. Role-based access must be applied, and unnecessary identity, health, financial and internal institutional data must not be sent to the model. Source retrieval, AI suggestions and the accessibility editor's decision must be logged separately.

Who this suits

A good fit

Teams that regularly prepare draft accessibility corrections
Institutions that manually combine course PDF, video transcript and checklist data
Operations that keep the final decision with a person

Not a good fit

When source data is not current
When responsibility for the accessibility editor role is not defined
When AI suggestions would be applied without review

Frequently asked questions

What data is used?

The course PDF, video transcript and checklist are retrieved only from authorised sources. A field whose source and version cannot be identified is not treated as definitive information.

When does the process stop?

When a formula cannot be described through simple alternative text, the record is routed to the accessibility editor for review. If supporting evidence is missing, no change is made to the target record.

Does AI make the final decision?

No. The accessibility editor has authority over whether the content is ready for publication. Accept, correct and reject actions are logged as human decisions.

Project led by:DijitalPi

✦ PI ASSISTANT · ARTIFICIAL INTELLIGENCE

online

Ask the DijitalPi AI Assistant your question

No need to fill in a form and wait for a reply — write your question and let Pi, trained on DijitalPi's 20 years of know-how, answer within seconds.

Instant answers, 24/7
Service-specific context — no generic replies
Can connect you to a free consultation if you wish

Hi! 👋 I'm Pi — DijitalPi's AI assistant. Write whatever you'd like to know about AI System for Reviewing Course Content Accessibility and I'll answer right away.

Pi Assistant answers are for information purposes; for a proposal get in touch.

ASK AI ABOUT DIJITALPI

Let an AI explain what DijitalPi does.

Opens your chosen assistant with a ready research prompt. It reads the site live and answers.

ChatGPT Claude Gemini Grok Perplexity