AI-Powered Auto-Generated 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:info@n3w.it) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).
- Platform
- n8n
- Category
- Education
- Price
- $24.99
- Creator
- Davide
- code
- googleDocs
- stickyNote
- httpRequest
- googleSheets
- convertToFile
- manualTrigger
- splitInBatches
- agent
- chainLlm
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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