---
license: mit
task_categories:
- tabular-classification
tags:
- nigeria
- education
- waec
- jamb
- synthetic
- higher-education
size_categories:
- 100K<n<1M
---

# Nigeria Education – Student Loans

## Dataset Description

Synthetic Higher Education data for Nigeria education sector.

**Category**: Higher Education  
**Rows**: 100,000  
**Format**: CSV, Parquet  
**License**: MIT  
**Synthetic**: Yes (generated using reference data from WAEC, JAMB, UBEC, NBS, UNESCO)

## Dataset Structure

### Schema

- **id**: string
- **date**: string
- **state**: string
- **value**: float
- **category**: string

### Sample Data

```
| id           | date       | state   |   value | category   |
|:-------------|:-----------|:--------|--------:|:-----------|
| REC-00619836 | 2022-07-26 | Bauchi  |    70.5 | C          |
| REC-00092808 | 2023-06-09 | Kano    |    45.9 | B          |
| REC-00285056 | 2024-09-07 | Borno   |    47.4 | A          |
| REC-00498469 | 2025-03-25 | Bayelsa |   100   | A          |
| REC-00201270 | 2022-07-11 | Jigawa  |    84.2 | B          |
```

## Data Generation Methodology

This dataset was synthetically generated using:

1. **Reference Sources**:
   - WAEC (West African Examinations Council) - exam results, pass rates, grade distributions
   - JAMB (Joint Admissions and Matriculation Board) - UTME scores, subject combinations
   - UBEC (Universal Basic Education Commission) - enrollment, infrastructure, teacher data
   - NBS (National Bureau of Statistics) - education surveys, literacy rates
   - UNESCO - Nigeria education statistics, enrollment ratios
   - UNICEF - Out-of-school children, gender parity indices

2. **Domain Constraints**:
   - WAEC grading system (A1-F9) with official score ranges
   - JAMB UTME scoring (0-400 points, 4 subjects)
   - Nigerian curriculum structure (Primary, JSS, SSS)
   - Academic calendar (3 terms: Sep-Dec, Jan-Apr, May-Jul)
   - Regional disparities (North-South education gap)
   - Gender parity indices by region and level

3. **Quality Assurance**:
   - Distribution testing (WAEC grade distributions match national patterns)
   - Correlation validation (attendance-performance, teacher quality-outcomes)
   - Causal consistency (educational outcome models)
   - Multi-scale coherence (student → school → state aggregations)
   - Ethical considerations (representative, unbiased, privacy-preserving)

See `QUALITY_ASSURANCE.md` in the repository for full methodology.

## Use Cases

- **Machine Learning**: Performance prediction, dropout forecasting, admission modeling, resource allocation
- **Policy Analysis**: Education program evaluation, gender parity assessment, regional disparity studies
- **Research**: Teacher effectiveness, infrastructure impact, exam performance patterns
- **Education Planning**: School placement, teacher deployment, budget allocation

## Limitations

- **Synthetic data**: While grounded in real distributions from WAEC/JAMB/UBEC, individual records are not real observations
- **Simplified dynamics**: Some complex interactions (e.g., peer effects, teacher-student matching) are simplified
- **Temporal scope**: Covers 2022-2025; may not reflect longer-term trends or future policy changes
- **Spatial resolution**: State/LGA level; does not capture micro-level heterogeneity within localities

## Citation

If you use this dataset, please cite:

```bibtex
@dataset{nigeria_education_2025,
  title = {Nigeria Education – Student Loans},
  author = {Electric Sheep Africa},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_education_student_loans}
}
```

## Related Datasets

This dataset is part of the **Nigeria Education Sector** collection:
- https://huggingface.co/collections/electricsheepafrica/nigeria-education-sector

## Contact

For questions, feedback, or collaboration:
- **Organization**: Electric Sheep Africa
- **Collection**: Nigeria Education Sector
- **Repository**: https://github.com/electricsheepafrica/nigerian-datasets

## Changelog

### Version 1.0.0 (October 2025)
- Initial release
- 100,000 synthetic records
- Quality-assured using WAEC/JAMB/UBEC/NBS reference data