Datasets:
metadata
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:
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
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
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:
@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:
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