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Good practice Imported

Project SIGLA — AI Growth Screening for School-Feeding Targeting, Philippines DepEd

Philippines · Manila · See the Philippines profile · See the Manila profile

Evidence: Descriptive / self-reported Top 81% 33/100 · Ask Evidence Copilot about this practice

DepEd's ECAIR piloted an AI growth-screening tool in Metro Manila schools to speed identification of malnourished and stunted learners for feeding programmes, cutting teachers' annual anthropometric data-encoding time from 3.75 to 1.87 hours.

3.75 hours/year
Teacher annual anthropometric data-encoding time before pilot (2025)
1.87 hours/year
Teacher annual anthropometric data-encoding time under pilot (2025)
~50 %
Reduction in annual data-encoding time (2025)

Details

Maturity
Pilot
Promoter
Department of Education (DepEd) – Education Center for AI Research (ECAIR)
Period
2025 (pilot)
Keywords
school health administration, nutrition programme logistics, public sector AI

Context

The Philippines' national school-feeding programme depends on teachers manually measuring and recording each learner's height, weight and BMI to flag malnutrition and stunting — a slow process that delays interventions.

Activities

Project SIGLA, developed by DepEd's Education Center for AI Research (ECAIR), uses an AI-based growth-screening tool to automate anthropometric assessment, piloted in NCR (Metro Manila) schools starting in the second half of 2025.

Results

BusinessMirror/PNA (January 2026) reported that teachers' annual time spent encoding learners' anthropometric data fell from about 3.75 hours to 1.87 hours — roughly a 50% reduction — under the pilot. Manila Bulletin (September 2025) independently confirmed the tool's purpose and its NCR pilot status, without giving its own figures.

Conclusions

The pilot remains confined to NCR; no measurement-accuracy audit or nationwide rollout has yet been published, and the time-savings figure comes from a single outlet (BusinessMirror/PNA) rather than independently corroborated data.

Implementation
Indicative cost
Low (< €50k)
Time to results
Short (< 1 year)
Staffing & skills
DepEd Education Center for AI Research (ECAIR)

Common failure modes

  • No measurement-accuracy audit has been published
  • Time-savings figure is single-sourced (BusinessMirror/PNA)
  • Pilot confined to NCR with no nationwide rollout yet reported

Commonly funded by

National / regional programmes

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Data sources

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

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