Datasets:

electricsheepafrica
/

nigerian_education_student_loans

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:

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 – 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