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Good practice Imported

Project DUNONG — AI-Automated National Qualifying Exam for School Heads, Philippines

Philippines · Pasig City · See the Philippines profile

Evidence: Descriptive / self-reported Top 77% 40/100 · Ask Evidence Copilot about this practice

The Philippines' DepEd replaced outsourced manual scoring of its National Qualifying Exam for School Heads with an in-house AI dual-scoring system, now serving 24,000+ leadership vacancies nationwide; one outlet reports 4,410 passed and ~₱5m saved in 2025.

24,000+ vacancies
School-leadership vacancies served nationwide (2025-2026)
4,410 candidates
Aspiring principals who passed the 2025 NQESH (2025)
~5 million PHP
Reported savings from automated record consolidation (2025)
Project DUNONG — AI-Automated National Qualifying Exam for School Heads, Philippines

Details

Maturity
Scaling
Promoter
Department of Education (DepEd) – Education Center for AI Research (ECAIR)
Period
2025–2026
Keywords
education administration, HR credentialing, public sector AI

Context

DepEd's National Qualifying Examination for School Heads (NQESH) determines who becomes a school principal or head across the Philippines' public school system; it was historically processed through outsourced manual scoring that was slow and costly.

Activities

Developed by DepEd's Education Center for AI Research (ECAIR) under the Bureau of Human Resource and Organizational Development, Project DUNONG automates exam processing with an in-house AI dual-scoring system, cutting outsourcing costs, speeding up result releases, and adding dashboards that flag competency gaps among aspiring principals.

Results

GMA News and Manila Bulletin (September 2025) confirm the system now serves over 24,000 school-leadership vacancies nationwide. BusinessMirror/PNA (January 2026) additionally reported that 4,410 aspiring principals passed the 2025 NQESH and that DepEd achieved roughly ₱5 million in savings from automated record consolidation — figures reported by that outlet alone.

Conclusions

Independent press coverage confirms the programme's existence, national scale and the shift from outsourced to in-house scoring, but no independent audit of the AI scoring's accuracy or bias has been published, and the pass-count and savings figures are single-sourced.

Implementation
Indicative cost
Medium (€50k–€500k) — Reported ~₱5 million in savings from automated record consolidation in 2025 (BusinessMirror/PNA, single-sourced).
Time to results
Medium (1–3 years)
Staffing & skills
DepEd Education Center for AI Research (ECAIR), Bureau of Human Resource and Organizational Development

Conditions for success

  • Dashboards flag competency gaps among aspiring principals
  • In-house AI dual-scoring replacing outsourced vendor

Common failure modes

  • No independent audit of the AI scoring's accuracy or bias has been published
  • Pass-count and savings figures are single-sourced

Commonly funded by

National / regional programmes

Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.

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Data sources

Where this practice's information was retrieved from, and when.

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