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 1. 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. 2. AI Processing: - Splits text into chunks and generates vector embeddings (via OpenAI) for semantic analysis. - Stores embeddings in Qdrant (vector database) for retrieval. 3. 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. 4. 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. 5. 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 1. 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. 2. Configure Connections: - Link credentials for: - Google Docs/Sheets (OAuth2). - OpenAI (API key). - Google Gemini (API key). - Qdrant (URL + API key). 3. 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. 4. Tweak Question Generation: - Modify prompts in: - "Open questions" node: Adjust criteria (e.g., difficulty, question types). - "Closed questions" node: Edit MCQ formatting rules. 5. Output Settings: - Update the Google Sheet ID in "Write open" and "Write closed" nodes. - Map columns in Google Sheets to match question/answer formats. 6. Run & Automate: - Trigger manually ("Test workflow") or schedule periodic runs (e.g., for updated content). --- Need help customizing? Contact me(mailto:[email protected]) for consulting and support or add me on Linkedin.