AI-Powered Auto-Generate Exam Questions and Answers from Google Docs with Gemini

This workflow automates the creation of exam questions (both open-ended and multiple-choice) from educational content stored in Google Docs, using AI-powered analysis and vector database retrieval

This workflow saves educators hours of manual work while ensuring high-quality, curriculum-aligned assessments. Let me know if you'd like help adapting it for specific subjects!

Use Cases
Educators**: Rapidly generate quizzes, midterms, or flashcards.
E-learning platforms**: Automate question banks for courses.
Corporate training**: Create assessments for employee onboarding.

Technical Requirements:
APIs**: Google Gemini, OpenAI, Qdrant, Google Workspace.
n8n Nodes**: LangChain, Google Sheets/Docs, HTTP requests, code blocks.

This workflow combines AI efficiency with human-curated quality, making it a powerful tool for modern education and training.

Advantages of This Workflow

✅ Fully Automated Exam Generation: From document to fully formatted quiz content with no manual intervention. ✅ Supports Comprehension and Critical Thinking: Questions are designed to go beyond factual recall, including inference and application. ✅ Uses AI and RAG for Accuracy: Ensures that answers are grounded in the document content, reducing hallucination. ✅ Seamless Google Integration: Pulls content from Google Docs and writes outputs to Google Sheets. ✅ Scalable for Any Subject: Works with any article or content domain as input. ✅ Modular and Customizable: Can be easily adapted to generate different question types or to use other LLMs or storage systems.

How It Works
Document Ingestion:
The workflow starts by fetching an educational document (e.g., textbook chapter, lecture notes) from Google Docs.
Converts the document to Markdown for structured processing.

AI Processing:
Splits text into chunks and generates vector embeddings (via OpenAI) for semantic analysis.
Stores embeddings in Qdrant (vector database) for retrieval.

Question Generation:
Open-ended questions: Google Gemini AI creates 10 critical-thinking questions.
Multiple-choice questions: Generates 10 MCQs (1 correct + 3 plausible distractors) using RAG to validate answers against the vector DB.

Answer Validation:
For open questions: Retrieves context-aware answers from the vector store.
For MCQs: Ensures distractors are incorrect but believable via AI cross-checking.

Output:
Saves questions/answers to Google Sheets in two tabs:
Open questions: Question + AI-generated answer.
Closed questions: MCQ + options + correct answer.

Set Up Steps
Prerequisites:
APIs/Accounts:
Google Workspace (Docs + Sheets).
OpenAI (for embeddings).
Google Gemini (for question generation).
Qdrant (vector DB – self-hosted or cloud).
n8n Nodes: Ensure LangChain, Google Sheets/Docs, and HTTP request nodes are installed.

Configure Connections:
Link credentials for:
Google Docs/Sheets (OAuth2).
OpenAI (API key).
Google Gemini (API key).
Qdrant (URL + API key).

Customize Input:
Replace the default Google Doc ID in the "Get Doc" node with your source document.
Adjust chunk size/overlap (Token Splitter node) for optimal text processing.

Tweak Question Generation:
Modify prompts in:
"Open questions" node: Adjust criteria (e.g., difficulty, question types).
"Closed questions" node: Edit MCQ formatting rules.

Output Settings:
Update the Google Sheet ID in "Write open" and "Write closed" nodes.
Map columns in Google Sheets to match question/answer formats.

Run & Automate:
Trigger manually ("Test workflow") or schedule periodic runs (e.g., for updated content).

Need help customizing?
Contact me for consulting and support or add me on Linkedin.