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---
license: mit
task_categories:
- tabular-classification
tags:
- nigeria
- education
- waec
- jamb
- synthetic
- teachers-and-workforce
size_categories:
- 100K<n<1M
---
# Nigeria Education – Teacher Salaries
## Dataset Description
Synthetic Teachers & Workforce data for Nigeria education sector.
**Category**: Teachers & Workforce
**Rows**: 160,000
**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-00499224 | 2022-11-08 | Cross River | 82.9 | C |
| REC-00142996 | 2024-11-20 | Kwara | 66.8 | A |
| REC-00677334 | 2024-12-14 | Osun | 85.4 | A |
| REC-00666262 | 2024-12-22 | Jigawa | 61.9 | C |
| REC-00202223 | 2024-10-13 | Nasarawa | 71.1 | 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 – Teacher Salaries},
author = {Electric Sheep Africa},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_education_teacher_salaries}
}
```
## 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
- 160,000 synthetic records
- Quality-assured using WAEC/JAMB/UBEC/NBS reference data