Who Is This For?

This workflow is designed for educators, universities, examination departments, and EdTech institutions that need a faster, smarter, and standardized way to prepare exam question papers.

What Problem Does This Solve?

Creating balanced, outcome-based question papers can take hours or even days of manual effort. Faculty often struggle to:

• Ensure syllabus coverage across units
• Maintain Bloom’s Taxonomy alignment
• Keep a consistent difficulty balance
• Format papers in institution-specific templates

How it works

This workflow automatically generates an exam question paper based on syllabus topics submitted via a form and sends it to the entered email address.

Here’s the flow in simple steps:

Form Submission – A student or faculty fills out a form with subject code, syllabus topics, and their email.

AI Question Generation – The workflow passes the syllabus to AI agents (Part A with 2 Marks, Part B with 13 Marks, and Part C with 14 Marks) to create question sets. The marks and the no. of question generated can be customized according to the convenience.

Merging Questions – All AI-generated questions are combined into a single structured document.

Format into HTML – The questions are formatted into a clean HTML exam paper (can also be extended to PDF).

Send by Email– The formatted exam paper is sent to the user’s email (with option to CC/BCC).

Set up steps

Connect Accounts

• Connect your OpenAI (or LLM) credentials for AI-powered question generation.
• Connect your Gmail (or preferred email service) to send emails.

Prepare Form

• Create an n8n form trigger with required fields:
  • Subject with Code
  • Syllabus for Unit 1, 2, 3…
  • Email to receive the paper

Customize Question Generation

• Modify the AI prompts for Parts A, B, and C to fit your syllabus style (e.g., 2-mark, 13-mark, 14-mark).

Format the Exam Paper

• Adjust the HTML template to match your institution’s exam paper layout.

Test & Deploy

• Submit a test form entry.
• Check the received email to ensure formatting looks good.
• Deploy the workflow to production for real usage.