elimu-research-assistant


Nameelimu-research-assistant JSON
Version 1.0.4 PyPI version JSON
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home_pagehttps://github.com/ashioyajotham/elimu_research_assistant
SummaryAn intelligent research assistant for Kenyan educators to create localized, contextual educational content that bridges the context deficit in education.
upload_time2025-07-22 14:44:30
maintainerNone
docs_urlNone
authorAshioya Jotham
requires_python>=3.9
licenseNone
keywords education kenya ai research teaching localized-content curriculum pedagogy african-education context-aware educational-technology
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            # Elimu Research Assistant

**A Tool for Localized Educational Content Creation in Kenya**

*Elimu* (Swahili for "education") Research Assistant is an intelligent research tool using ReAct framework designed specifically for Kenyan educators to bridge the context deficit in education by generating locally relevant, credibly sourced educational content.

## The Challenge

Imagine a Kenyan geography teacher trying to explain economic principles using examples from a textbook written in London. The lesson falls flat. Now imagine that same teacher, in minutes, generating a custom handout on the economic impact of the new Lamu Port, complete with local statistics and sources. This is the gap Elimu Research Assistant fills.

### Core Problems We Address

- **Context Deficit**: Official curricula often rely on foreign examples, making subjects feel abstract and irrelevant to Kenyan students
- **Educator Overload**: Teachers have limited time to research local data, case studies, and examples to enrich their lessons
- **Digital Research Gap**: Finding credible, locally relevant content is time-consuming and can be costly due to data expenses
- **Pedagogical Stagnation**: Lack of accessible, relevant materials limits teaching innovation beyond traditional lecture formats

## The Solution

Elimu Research Assistant is not another search engine. It's an intelligent assistant that understands a teacher's educational needs, conducts targeted web research, and delivers structured, ready-to-use content that is both locally relevant and credibly sourced.

### Key Capabilities

#### 🎯 Context-Aware Content Generation
- **Example**: "Generate a 2-page brief for Form 3 Business Studies on M-Pesa's impact on small enterprises in Kenya, including three Rift Valley examples"
- **Output**: Coherent, structured document ready for classroom use

#### 📚 Adaptable Content Formatting
- **Lesson Plans**: Bulleted lists with learning objectives and activities
- **Student Handouts**: Comparison tables and visual summaries
- **Teacher References**: Detailed narrative summaries with background context
- **Assessment Materials**: Quiz questions and discussion prompts

#### 🔍 Credible & Localized Sourcing
- Prioritizes reputable Kenyan sources (universities, KICD, government publications)
- Combines local and global perspectives
- Provides proper citations for digital literacy
- Ensures information is verifiable and current

### Sample Use Cases

1. **Science Teacher**: "Create a lesson plan on renewable energy focusing on Kenya's geothermal projects in Olkaria"
2. **History Teacher**: "Develop a comparison table of pre-colonial trade routes through modern-day Kenya"
3. **Mathematics Teacher**: "Generate word problems using Kenyan currency, distances between major cities, and local business scenarios"
4. **Literature Teacher**: "Compile a study guide on themes in Kenyan literature comparing Ngugi wa Thiong'o and Grace Ogot"

## Technical Foundation

Built on the proven ReAct (Reasoning + Acting) AI framework, Elimu Research Assistant features:

- **Dynamic Task Analysis**: Understands educational context and content requirements
- **Multi-Strategy Synthesis**: Four distinct approaches for different content types
- **Entity-Aware Processing**: Tracks and connects relevant educational concepts
- **Robust Error Handling**: Multiple fallback strategies for reliable content generation

## Installation

### Prerequisites
- Python 3.9 or higher
- Google Gemini API key
- Serper.dev API key (for web search)

### Quick Start

```bash
# Clone the repository
git clone https://github.com/ashioyajotham/elimu_research_assistant.git
cd elimu_research_assistant

# Install dependencies
pip install -r requirements.txt

# Configure API keys
elimu config --api-key YOUR_GEMINI_API_KEY
elimu config --serper-key YOUR_SERPER_API_KEY

# Run your first research task
elimu research "Create a lesson outline on Kenya's coastal tourism industry for Form 2 Geography"
```

### Command Line Usage

```bash
# Single research query
elimu research "Generate examples of quadratic equations using Kenyan sports statistics"

# Batch processing from file
elimu batch-research lesson_requests.txt --output classroom_materials/

# Configure settings
elimu config --show  # View current settings
elimu config --format markdown  # Set default output format
```

## Educational Impact

### For Teachers
- **Time Savings**: Reduce research time from hours to minutes
- **Quality Content**: Access to verified, locally relevant materials
- **Pedagogical Innovation**: Enable more engaging, context-rich lessons
- **Professional Development**: Exposure to diverse, credible educational sources

### For Students
- **Improved Engagement**: Learning through familiar, relevant examples
- **Better Comprehension**: Complex concepts explained through local context
- **Cultural Pride**: Seeing their country and culture represented in education
- **Global Perspective**: Local examples connected to international concepts

### For the Education System
- **Curriculum Enhancement**: Supplement official materials with local content
- **Digital Literacy**: Promote research skills and source verification
- **Educational Equity**: Provide quality content across resource-diverse schools
- **Innovation Culture**: Encourage teachers to experiment with AI-assisted pedagogy

## Project Status

The core AI engine is technologically mature, evolved from the 'Web Research Agent' academic project. This educational adaptation is being developed through:

- **Pilot Partnership**: Collaboration with Kenyan secondary school teachers
- **User-Centric Design**: Direct feedback from classroom practitioners
- **Iterative Development**: Continuous improvement based on real-world usage
- **Field Testing**: Validation in actual classroom environments

## Architecture

```mermaid
graph TD
    A[Teacher Request] --> B[Educational Task Analysis]
    B --> C[Kenya-Focused Search Strategy]
    C --> D[Multi-Source Research]
    D --> E[Context-Aware Synthesis]
    E --> F[Educational Content Format]
    F --> G[Ready-to-Use Materials]
    
    style B fill:#e1f5fe
    style E fill:#e8f5e8
    style F fill:#fff3e0
```

### Workflow for Educators

1. **Request Analysis**: System understands educational level, subject, and content type needed
2. **Intelligent Search**: Prioritizes Kenyan sources while maintaining global perspective
3. **Content Synthesis**: Combines multiple sources into coherent educational materials
4. **Format Optimization**: Delivers content in teacher-specified format (lesson plan, handout, etc.)
5. **Quality Assurance**: Provides citations and source verification for credibility

## Contributing

We welcome contributions from educators, developers, and anyone passionate about improving education in Kenya.

### For Educators
- Provide feedback on generated content
- Suggest common use cases and scenarios
- Share successful classroom implementations
- Report content gaps or inaccuracies

### For Developers
- Enhance localization algorithms
- Improve educational content formatting
- Add new source integration capabilities
- Optimize for low-bandwidth environments

## Roadmap

### Phase 1: Foundation (Current)
- ✅ Core AI research and synthesis engine
- ✅ Basic educational content formatting
- 🔄 Pilot testing with Kenyan educators

### Phase 2: Enhancement (Q2 2025)
- 📋 Advanced curriculum alignment features
- 📋 Multilingual support (English, Swahili)
- 📋 Offline content generation capabilities
- 📋 Mobile app development

### Phase 3: Scale (Q3-Q4 2025)
- 📋 Integration with existing LMS platforms
- 📋 Collaborative content sharing among teachers
- 📋 Assessment and quiz generation
- 📋 Student-facing research tools

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Citation

If you use Elimu Research Assistant in your research or educational work, please cite:

```
Ashioya, J. (2025). Elimu Research Assistant: An AI-Powered Tool for Localized Educational Content Creation in Kenya. GitHub. https://github.com/ashioyajotham/elimu_research_assistant
```

## Contact

**Ashioya Jotham**  
Individual Researcher & Developer  
Email: victorashioya960@gmail.com  
Project: Elimu Research Assistant  

---

*"Education is the most powerful weapon which you can use to change the world." - Nelson Mandela*

*Let's make that education relevant, accessible, and proudly Kenyan.*

            

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    "description": "# Elimu Research Assistant\n\n**A Tool for Localized Educational Content Creation in Kenya**\n\n*Elimu* (Swahili for \"education\") Research Assistant is an intelligent research tool using ReAct framework designed specifically for Kenyan educators to bridge the context deficit in education by generating locally relevant, credibly sourced educational content.\n\n## The Challenge\n\nImagine a Kenyan geography teacher trying to explain economic principles using examples from a textbook written in London. The lesson falls flat. Now imagine that same teacher, in minutes, generating a custom handout on the economic impact of the new Lamu Port, complete with local statistics and sources. This is the gap Elimu Research Assistant fills.\n\n### Core Problems We Address\n\n- **Context Deficit**: Official curricula often rely on foreign examples, making subjects feel abstract and irrelevant to Kenyan students\n- **Educator Overload**: Teachers have limited time to research local data, case studies, and examples to enrich their lessons\n- **Digital Research Gap**: Finding credible, locally relevant content is time-consuming and can be costly due to data expenses\n- **Pedagogical Stagnation**: Lack of accessible, relevant materials limits teaching innovation beyond traditional lecture formats\n\n## The Solution\n\nElimu Research Assistant is not another search engine. It's an intelligent assistant that understands a teacher's educational needs, conducts targeted web research, and delivers structured, ready-to-use content that is both locally relevant and credibly sourced.\n\n### Key Capabilities\n\n#### \ud83c\udfaf Context-Aware Content Generation\n- **Example**: \"Generate a 2-page brief for Form 3 Business Studies on M-Pesa's impact on small enterprises in Kenya, including three Rift Valley examples\"\n- **Output**: Coherent, structured document ready for classroom use\n\n#### \ud83d\udcda Adaptable Content Formatting\n- **Lesson Plans**: Bulleted lists with learning objectives and activities\n- **Student Handouts**: Comparison tables and visual summaries\n- **Teacher References**: Detailed narrative summaries with background context\n- **Assessment Materials**: Quiz questions and discussion prompts\n\n#### \ud83d\udd0d Credible & Localized Sourcing\n- Prioritizes reputable Kenyan sources (universities, KICD, government publications)\n- Combines local and global perspectives\n- Provides proper citations for digital literacy\n- Ensures information is verifiable and current\n\n### Sample Use Cases\n\n1. **Science Teacher**: \"Create a lesson plan on renewable energy focusing on Kenya's geothermal projects in Olkaria\"\n2. **History Teacher**: \"Develop a comparison table of pre-colonial trade routes through modern-day Kenya\"\n3. **Mathematics Teacher**: \"Generate word problems using Kenyan currency, distances between major cities, and local business scenarios\"\n4. **Literature Teacher**: \"Compile a study guide on themes in Kenyan literature comparing Ngugi wa Thiong'o and Grace Ogot\"\n\n## Technical Foundation\n\nBuilt on the proven ReAct (Reasoning + Acting) AI framework, Elimu Research Assistant features:\n\n- **Dynamic Task Analysis**: Understands educational context and content requirements\n- **Multi-Strategy Synthesis**: Four distinct approaches for different content types\n- **Entity-Aware Processing**: Tracks and connects relevant educational concepts\n- **Robust Error Handling**: Multiple fallback strategies for reliable content generation\n\n## Installation\n\n### Prerequisites\n- Python 3.9 or higher\n- Google Gemini API key\n- Serper.dev API key (for web search)\n\n### Quick Start\n\n```bash\n# Clone the repository\ngit clone https://github.com/ashioyajotham/elimu_research_assistant.git\ncd elimu_research_assistant\n\n# Install dependencies\npip install -r requirements.txt\n\n# Configure API keys\nelimu config --api-key YOUR_GEMINI_API_KEY\nelimu config --serper-key YOUR_SERPER_API_KEY\n\n# Run your first research task\nelimu research \"Create a lesson outline on Kenya's coastal tourism industry for Form 2 Geography\"\n```\n\n### Command Line Usage\n\n```bash\n# Single research query\nelimu research \"Generate examples of quadratic equations using Kenyan sports statistics\"\n\n# Batch processing from file\nelimu batch-research lesson_requests.txt --output classroom_materials/\n\n# Configure settings\nelimu config --show  # View current settings\nelimu config --format markdown  # Set default output format\n```\n\n## Educational Impact\n\n### For Teachers\n- **Time Savings**: Reduce research time from hours to minutes\n- **Quality Content**: Access to verified, locally relevant materials\n- **Pedagogical Innovation**: Enable more engaging, context-rich lessons\n- **Professional Development**: Exposure to diverse, credible educational sources\n\n### For Students\n- **Improved Engagement**: Learning through familiar, relevant examples\n- **Better Comprehension**: Complex concepts explained through local context\n- **Cultural Pride**: Seeing their country and culture represented in education\n- **Global Perspective**: Local examples connected to international concepts\n\n### For the Education System\n- **Curriculum Enhancement**: Supplement official materials with local content\n- **Digital Literacy**: Promote research skills and source verification\n- **Educational Equity**: Provide quality content across resource-diverse schools\n- **Innovation Culture**: Encourage teachers to experiment with AI-assisted pedagogy\n\n## Project Status\n\nThe core AI engine is technologically mature, evolved from the 'Web Research Agent' academic project. This educational adaptation is being developed through:\n\n- **Pilot Partnership**: Collaboration with Kenyan secondary school teachers\n- **User-Centric Design**: Direct feedback from classroom practitioners\n- **Iterative Development**: Continuous improvement based on real-world usage\n- **Field Testing**: Validation in actual classroom environments\n\n## Architecture\n\n```mermaid\ngraph TD\n    A[Teacher Request] --> B[Educational Task Analysis]\n    B --> C[Kenya-Focused Search Strategy]\n    C --> D[Multi-Source Research]\n    D --> E[Context-Aware Synthesis]\n    E --> F[Educational Content Format]\n    F --> G[Ready-to-Use Materials]\n    \n    style B fill:#e1f5fe\n    style E fill:#e8f5e8\n    style F fill:#fff3e0\n```\n\n### Workflow for Educators\n\n1. **Request Analysis**: System understands educational level, subject, and content type needed\n2. **Intelligent Search**: Prioritizes Kenyan sources while maintaining global perspective\n3. **Content Synthesis**: Combines multiple sources into coherent educational materials\n4. **Format Optimization**: Delivers content in teacher-specified format (lesson plan, handout, etc.)\n5. **Quality Assurance**: Provides citations and source verification for credibility\n\n## Contributing\n\nWe welcome contributions from educators, developers, and anyone passionate about improving education in Kenya.\n\n### For Educators\n- Provide feedback on generated content\n- Suggest common use cases and scenarios\n- Share successful classroom implementations\n- Report content gaps or inaccuracies\n\n### For Developers\n- Enhance localization algorithms\n- Improve educational content formatting\n- Add new source integration capabilities\n- Optimize for low-bandwidth environments\n\n## Roadmap\n\n### Phase 1: Foundation (Current)\n- \u2705 Core AI research and synthesis engine\n- \u2705 Basic educational content formatting\n- \ud83d\udd04 Pilot testing with Kenyan educators\n\n### Phase 2: Enhancement (Q2 2025)\n- \ud83d\udccb Advanced curriculum alignment features\n- \ud83d\udccb Multilingual support (English, Swahili)\n- \ud83d\udccb Offline content generation capabilities\n- \ud83d\udccb Mobile app development\n\n### Phase 3: Scale (Q3-Q4 2025)\n- \ud83d\udccb Integration with existing LMS platforms\n- \ud83d\udccb Collaborative content sharing among teachers\n- \ud83d\udccb Assessment and quiz generation\n- \ud83d\udccb Student-facing research tools\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Citation\n\nIf you use Elimu Research Assistant in your research or educational work, please cite:\n\n```\nAshioya, J. 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