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Machine Learning · ML-07

Predict progression into higher education

Explore progression models that connect education stages with household circumstances and subsequent study or work.

  • Synthetic records
  • Longitudinal
  • Nairobi + Lagos
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Scope & purpose

Connected scope

Connect schooling, higher education entry, household circumstances and later employment to study education transitions.

  • Education
  • Households
  • Demographics
  • Employment

Define the prediction date and horizon. Keep earlier inputs separate from later outcomes.

Possible uses

Prediction prototyping · Feature exploration · Temporal validation · Cohort comparison

Who it is for

Education researchers · universities · ML teams · policy analysts

Preview type
Illustrative format preview
Shows example structure and fields. It is not a sample extracted from the paid release.
Commercial availability
Confirmed in your written quote
The listed cities describe catalogue coverage. We confirm the exact release and available extract before agreement.
Starting-price basis
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Scope and supporting artifacts listed in the quote
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Paid dataset delivery

What you receive

SD delivery standard
Published cities
Nairobi + Lagos
Record scope
Resident-level
Structure
Longitudinal

Striped Donkey delivery package

  • data/Agreed extract and formats
  • documentation/Schema, fields and relationships
  • evidence/Agreed release checks and limits
  • examples/Agreed loading and join examples
  • LICENSEApplicable rights
  • MANIFESTRelease and file inventory
  • CHECKSUMSSHA-256 fingerprints
  • DELIVERY_NOTEScope and handoff record

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15 illustrative rows · 11 fields · CSV

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Illustrative rows show the format. Your quote confirms delivered records, fields and time coverage.

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Fields and record structure

Listed features

Resident-level · Longitudinal

  • completion date
  • qualification level
  • post-study employment outcome
  • enrolment history
  • qualification / completion
  • education transitions
  • household composition

Study question

Evaluation design

Can prior education and household histories predict which eligible school leavers enter higher education within 24 months of completing secondary school?

Define country-specific eligibility and qualifying enrolment; report calibration across completion cohorts and handle incomplete follow-up separately.

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Evidence you can inspect

Source & limitations

Review release-specific methods and published checks. Preview rows show format and scope; they do not certify a dataset.

Supporting references
NairobiEvidenceSamples
LagosEvidenceSamples
MethodsGenerationReproduce

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Licence & delivery

Free preview

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Purchased dataset

Your agreement defines the release, licensed organization, permitted uses and duration. Commercial model training, external applications and redistribution require explicit agreement.

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