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Business Studies Lesson Planning Assistant

An AI-powered chatbot that helps Business Studies teachers in Tanzania create structured, practical lessons following the MEWAKA pedagogical framework. The assistant guides teachers through the EXPECT-CONNECT-PROJECT methodology to develop 80-minute lessons that inspire students to become job creators rather than just exam-takers.

Purpose

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This workflow serves Business Studies teachers in MEWAKA Cohort schools (Forms 1-4) in Tanzania who need to prepare lessons aligned with CBC (Competency-Based Curriculum) and PBA (Project-Based Assessment) standards. The assistant helps teachers design lessons that:

  • Develop job-creator skills and entrepreneurial mindsets in students
  • Connect theoretical business concepts to real-world applications
  • Structure practical projects that students can implement
  • Use local, familiar examples relevant to Tanzanian students
  • Balance syllabus coverage with business inspiration

How It Works

  1. Chat Interface: Teachers access the assistant through a public chat interface
  2. AI Processing: Messages are processed by Google's Gemini 3 Flash model via OpenRouter
  3. Structured Guidance: The AI follows a detailed system prompt to guide teachers through lesson planning using the EXPECT-CONNECT-PROJECT framework
  4. Memory Retention: The system remembers the conversation context for up to 20 exchanges
  5. Lesson Output: Teachers receive structured lesson plans with clear activities, timelines, and assessment strategies

Workflow Diagram

graph TD
    A[When chat message received] --> B[AI Agent1]
    C[OpenRouter Chat Model] --> B
    D[Simple Memory] --> B

    B --> E[Structured Lesson Plan Output]

    style A fill:#e1f5fe
    style B fill:#f3e5f5
    style C fill:#fff3e0
    style D fill:#e8f5e8
    style E fill:#fce4ec

Trigger

Chat Trigger: The workflow activates when users send messages to the public chat interface. The initial greeting message welcomes teachers with: "Hi there! 👋Business Studies Teacher ready to help you prepare for your business studies lesson."

Nodes Used

Node Type Node Name Purpose
Chat Trigger When chat message received Receives user messages and starts the workflow
AI Agent AI Agent1 Processes messages using the MEWAKA lesson planning framework
Language Model OpenRouter Chat Model Provides AI responses using Google Gemini 3 Flash
Memory Simple Memory Maintains conversation context for up to 20 exchanges

External Services & Credentials Required

OpenRouter API

  • Service: OpenRouter (proxy for Google Gemini 3 Flash)
  • Credential Name: "Prompt Testing for Design team"
  • Required: API key for OpenRouter service
  • Purpose: Powers the AI language model responses

Environment Variables

No environment variables are required for this workflow. All configuration is handled through node parameters and credentials.

Data Flow

Input

  • User Messages: Text messages from Business Studies teachers requesting lesson planning assistance
  • Context: Conversation history maintained in memory buffer

Processing

  • System Prompt: Detailed instructions for MEWAKA lesson planning methodology
  • AI Analysis: Gemini model processes requests according to EXPECT-CONNECT-PROJECT framework
  • Memory Integration: Previous conversation context influences responses

Output

  • Structured Lesson Plans: 80-minute lesson plans with:
    • Clear learning objectives and job-creator skills
    • CBC expectation statements
    • Local case studies and real-world connections
    • Project assignments with timelines and deliverables
    • Assessment strategies using NECTA rubrics

Error Handling

The workflow uses n8n's default error handling. No custom error paths are implemented in the current configuration. Potential failure points include:

  • OpenRouter API connectivity issues
  • Model response timeouts
  • Memory buffer overflow (after 20 exchanges)

Known Limitations

  • Memory is limited to 20 conversation exchanges
  • Designed specifically for Tanzanian educational context and MEWAKA framework
  • Requires stable internet connection for OpenRouter API access
  • No offline capability or local model fallback

No related workflows are mentioned in the current configuration.

Setup Instructions

  1. Import Workflow: Import the JSON configuration into your n8n instance

  2. Configure OpenRouter Credentials:

    • Create new OpenRouter API credentials
    • Add your OpenRouter API key
    • Name the credential appropriately

  3. Test Chat Interface:

    • Activate the workflow
    • Access the public chat URL provided by the Chat Trigger node
    • Send a test message to verify the assistant responds correctly

  4. Customize System Prompt (Optional):

    • Modify the system message in the AI Agent node to adjust the assistant's behavior
    • Update local examples or pedagogical frameworks as needed

  5. Monitor Usage:

    • Check workflow execution logs for performance
    • Monitor OpenRouter API usage and costs
    • Adjust memory window size if needed for longer conversations

The workflow is ready to use once credentials are configured and the workflow is activated.