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OMOJEJE/africa-synth-education-neco-results-nigeria

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. Nigeria Education – NECO Results Dataset Description NECO SSCE exam results (alternative to WAEC). Category: Student Performance & ExamsRows: 250,000Format: CSV, ParquetLicense: MITSynthetic: Yes (generated using reference data from WAEC, JAMB, UBEC, NBS, UNESCO) Dataset Structure Schema… See the full description on the dataset page: https://huggingface.co/datasets/OMOJEJE/africa-synth-education-neco-results-nigeria.

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⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

Nigeria Education – NECO Results

Dataset Description

NECO SSCE exam results (alternative to WAEC).

Category: Student Performance & Exams Rows: 250,000 Format: CSV, Parquet License: MIT Synthetic: Yes (generated using reference data from WAEC, JAMB, UBEC, NBS, UNESCO)

Dataset Structure

Schema

  • —student_id: string
  • —year: integer
  • —state: string
  • —school_type: string
  • —subject: string
  • —score: float
  • —grade: string
  • —exam_type: string

Sample Data

| student_id   |   year | state       | school_type      | subject         |   score | grade   | exam_type   |
|:-------------|-------:|:------------|:-----------------|:----------------|--------:|:--------|:------------|
| STU-0475688  |   2023 | Akwa Ibom   | private_standard | Physics         |    64.7 | F9      | NECO        |
| STU-0149740  |   2023 | Bayelsa     | public_lga       | Physics         |    55.6 | C5      | NECO        |
| STU-0021275  |   2022 | Gombe       | private_low_cost | Mathematics     |    63.7 | C4      | NECO        |
| STU-0334560  |   2024 | Oyo         | public_lga       | Civic Education |    53.1 | C6      | NECO        |
| STU-0097246  |   2023 | Cross River | private_low_cost | Chemistry       |    60.6 | C4      | NECO        |

Data Generation Methodology

This dataset was synthetically generated using:

  1. 1.Reference Sources:
  2. 2.WAEC (West African Examinations Council) - exam results, pass rates, grade distributions
  3. 3.JAMB (Joint Admissions and Matriculation Board) - UTME scores, subject combinations
  4. 4.UBEC (Universal Basic Education Commission) - enrollment, infrastructure, teacher data
  5. 5.NBS (National Bureau of Statistics) - education surveys, literacy rates
  6. 6.UNESCO - Nigeria education statistics, enrollment ratios
  7. 7.UNICEF - Out-of-school children, gender parity indices
  1. 1.Domain Constraints:
  2. 2.WAEC grading system (A1-F9) with official score ranges
  3. 3.JAMB UTME scoring (0-400 points, 4 subjects)
  4. 4.Nigerian curriculum structure (Primary, JSS, SSS)
  5. 5.Academic calendar (3 terms: Sep-Dec, Jan-Apr, May-Jul)
  6. 6.Regional disparities (North-South education gap)
  7. 7.Gender parity indices by region and level
  1. 1.Quality Assurance:
  2. 2.Distribution testing (WAEC grade distributions match national patterns)
  3. 3.Correlation validation (attendance-performance, teacher quality-outcomes)
  4. 4.Causal consistency (educational outcome models)
  5. 5.Multi-scale coherence (student → school → state aggregations)
  6. 6.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 – NECO Results},
  author = {Electric Sheep Africa},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_education_neco_results}
}

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
  • —250,000 synthetic records
  • —Quality-assured using WAEC/JAMB/UBEC/NBS reference data