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Costa Rica's National AI Guide for Teachers — 'Inteligencia Artificial en Clase'

Costa Rica · San José · See the Costa Rica profile

Costa Rica's Ministry of Public Education, with the UN, UNESCO and ULACIT, launched an ethics-and-safety guide for AI in classrooms (Feb–Mar 2026) for all 65,000 public-school teachers and ~1M students, built on explicit privacy, bias and accuracy criteria — rollout begins in the

Costa Rica's National AI Guide for Teachers — 'Inteligencia Artificial en Clase' Costa Rica's National AI Guide for Teachers — 'Inteligencia Artificial en Clase'

Details

Maturity
Pilot
Promoter
Ministerio de Educación Pública (MEP), Costa Rica — with UN Costa Rica, UNESCO and ULACIT
Period
2026–
Keywords
education policy, AI ethics, teacher training, data privacy

Context

Costa Rica's Ninth State of Education Report (2023) found only three in ten students reach expected learning competencies, with many secondary students reading and calculating at levels typical of much younger children. Generative AI was already reaching classrooms informally and unevenly when the Ministry of Public Education (MEP) began building a national response.

Objectives

In February-March 2026, MEP — working with the UN System in Costa Rica, UNESCO and the private Universidad Latinoamericana de Ciencia y Tecnología (ULACIT) — launched 'Inteligencia Artificial en Clase: guía para docentes', a seven-chapter national guide aimed at all 65,000 public-school teachers and around one million students, intended to keep teachers' professional judgement central rather than delegate decisions to AI.

Activities

The guide covers AI fundamentals, prompt design and classroom project design, and sets out explicit ethical and data criteria for tool selection: bias reduction, discrimination prevention, filtering of inappropriate automated content, privacy protection and data-accuracy checks.

Results

The guide was only just being rolled out as the 2026 school year began; the Ministry's headline claim of a projected 30% improvement in maths and science outcomes is a projection, not a measured result, and no independent measurement of learning impact, teacher uptake or actual classroom data-handling practice yet exists.

Conclusions

This is a governance and capacity-building intervention rather than a proven-impact one at this stage: its value lies in setting a national ethical and pedagogical baseline for AI use ahead of adoption, with outcome evidence still to come.

Implementation

Indicative cost
Medium (€50k–€500k) — National guide production and multi-partner (UN/UNESCO/ULACIT) development; distribution cost not stated.
Time to results
Medium (1–3 years) — Guide launched Feb-Mar 2026 for the start of the school year; rollout to full national uptake is ongoing.
Staffing & skills
Ministry of Public Education (MEP) staff, UN System in Costa Rica and UNESCO technical partners, ULACIT (private university) co-development team

Conditions for success

  • Explicit ethical/data criteria for tool selection (bias, privacy, accuracy)
  • Commitment to keep teachers' professional judgement central rather than delegating decisions to AI
  • National-scale distribution to all 65,000 public-school teachers

Common failure modes

  • No independent measurement yet of learning impact, teacher uptake, or actual classroom data-handling practice
  • Headline 30% improvement figure is a projection, not a measured outcome

Where it fits

Governance type
national ministry with UN/UNESCO and private-university partnership
Scale
national (65,000 teachers, ~1M students)
Income level
upper-middle income

Data sources

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

Attachments

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