---
license: cc-by-4.0
task_categories:
- text-classification
- summarization
- text-generation
- question-answering
language:
- en
pretty_name: OER Foundation Dataset
size_categories:
- 100M<n<1B
---

# OER Foundation Dataset

The **OER Foundation Dataset** is a curated collection of educational resources designed to serve as a foundational input for creating **Open Educational Resources (OERs)** and ad hoc learning media. This dataset is structured to support machine learning models and other educational technologies in generating textbooks, lesson plans, quizzes, and other learning materials. 

By offering openly licensed and high-quality educational content, the **OER Foundation Dataset** aims to empower educators, developers, and researchers to innovate in the field of education.

## Key Features
- **Rich Metadata**: Each entry includes detailed metadata, such as subject area, grade level, and licensing information, to support diverse educational use cases.
- **Task Categories**:
  - Text classification
  - Question answering
  - Summarization
  - Text generation
  - Information retrieval
- **Optimized for LLMs**: Preprocessed and structured to enable seamless integration with large language models.
- **Open License**: Distributed under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license.

## Dataset Schema
The dataset is organized into a clear and extensible schema:
- **`id`**: Unique identifier for each resource.
- **`title`**: Title of the content or section.
- **`subject`**: Subject area (e.g., Mathematics, Science, History).
- **`grade_level`**: Intended grade level or proficiency tier.
- **`content`**: Main educational content (e.g., text, lecture notes, definitions).
- **`tags`**: Keywords for easy categorization and search.
- **`metadata`**:
  - **`source`**: Original source or citation of the material.
  - **`license`**: Licensing details for reuse.
  - **`educational_standards`**: Alignment with standards like Common Core or NGSS.
- **`media_links`**: URLs to images, videos, or external resources (if applicable).
- **`questions`**: Related assessment questions with answers.

Example Entry:
```json
{
  "id": "math_101",
  "title": "Introduction to Algebra",
  "subject": "Mathematics",
  "grade_level": "6",
  "content": "Algebra is the study of mathematical symbols and rules for manipulating these symbols...",
  "tags": ["algebra", "mathematics", "middle school"],
  "metadata": {
    "source": "OpenStax",
    "license": "CC BY 4.0",
    "educational_standards": ["Common Core: 6.EE.A.1"]
  },
  "media_links": ["https://example.com/image1.png"],
  "questions": [
    {
      "type": "multiple_choice",
      "question": "What is the value of x in the equation 2x + 3 = 7?",
      "options": ["2", "3", "4", "5"],
      "correct_answer": "2"
    }
  ]
}
```

## Use Cases
This dataset can be used for:
- **Fine-tuning language models** to generate educational content.
- **Creating ad hoc learning materials** such as quizzes, lesson plans, and study guides.
- **Developing educational applications** that require curriculum-aligned resources.
- **Semantic search and knowledge extraction** in education technology.

## License
This dataset is distributed under the **[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)** license.  
You are free to:
- Share: Copy and redistribute the material in any medium or format.
- Adapt: Remix, transform, and build upon the material for any purpose, even commercially.  

**Attribution is required**, meaning you must give appropriate credit, provide a link to the license, and indicate if changes were made.

---

## How to Use
1. Clone the repository:
   ```bash
   git clone https://huggingface.co/datasets/rolodexter/OER-Foundation.git
   ```
2. Load the dataset using the Hugging Face `datasets` library:
   ```python
   from datasets import load_dataset

   dataset = load_dataset("rolodexter/OER-Foundation")
   print(dataset)
   ```


## Contributing
We welcome contributions to expand and improve the dataset. If you have suggestions or additional resources to include:
1. Fork the repository.
2. Add your changes.
3. Submit a pull request for review.

## Contact
For inquiries or collaboration opportunities, please reach out via the [Hugging Face discussion board](https://huggingface.co/datasets/rolodexter/OER-Foundation/discussions).

## Acknowledgments
Special thanks to the open education community and contributors who made this dataset possible.