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Good practice Imported

Thailand's Equitable Education Fund — From SIM-Card Access to AI-Driven Learning Pathways for At-Risk Students

Thailand · Bangkok · See the Thailand profile · See the Bangkok profile

Evidence: Observational / pre–post Top 43% 53/100 · Ask Evidence Copilot about this practice

After free SIM-cards reached 400,000+ Thai students but only 18,000 used them for learning, the Equitable Education Fund is building AI systems using risk profiles and community data to recommend personalised pathways for disadvantaged students, EdTech Hub and EEF report.

400,000+ students
Students reached by free-data SIM cards (SIM 2 Learn programme)
113,000 students
Students who registered for the service (SIM 2 Learn programme)
18,000 students
Students who actively used the service for learning (SIM 2 Learn programme)

Details

Maturity
Pilot
Promoter
Equitable Education Fund (EEF) Thailand, with EdTech Hub and the Sirindhorn Anthropology Centre
Period
2024–2026 (SIM 2 Learn since 2024; AI pathway system described March 2026)
Keywords
education equity, digital inclusion, AI-driven personalisation, social protection

Context

Thailand's Equitable Education Fund (EEF), a government-linked body established under the 2018 Equitable Education Act, has spent several years tackling the digital divide facing poor and rural students, identified during the COVID-19 pandemic as up to ten times more disadvantaged than their peers in access to devices and connectivity.

Objectives

The 'SIM 2 Learn' programme, run with the National Broadcasting and Telecommunications Commission and telecom partner Infinite Sim, aimed to give free-data SIM cards to Grade 6–9 students, alongside a LINE-based support channel ('@sim2learn') offering career guidance, mental-health support and scholarship information.

Activities

EEF is now developing AI systems that draw on individual student risk profiles, community-level socio-economic data from Thailand's Sirindhorn Anthropology Centre, and scholarship-opportunity data to generate personalised learning-pathway recommendations for disadvantaged students, aiming to convert access into sustained engagement.

Results

Distribution of the SIM cards reached more than 400,000 eligible students nationwide, but only 113,000 registered for the service and just 18,000 went on to actively use it for learning — evidence, EEF's Research Director said, that 'even when we remove the financial barriers to internet access, other invisible barriers remain,' including digital literacy gaps and low motivation.

Conclusions

The AI pathway-recommendation system is newly described and has not yet been independently evaluated; the only rigorously quantified figures available concern the prior SIM-card programme's usage funnel, which itself shows a programme still finding its footing rather than a proven success.

Implementation

Indicative cost
Medium (€50k–€500k) — National SIM-card distribution to 400,000+ students plus a new AI recommendation layer; no public cost figures disclosed — conservative medium estimate pending curator review.
Time to results
Medium (1–3 years) — SIM 2 Learn has run since roughly 2024; the AI pathway-recommendation system was newly described as of a March 2026 webinar — conservative medium-timeline estimate pending curator review.
Staffing & skills
Equitable Education Fund (EEF), National Broadcasting and Telecommunications Commission, Infinite Sim (telecom partner), Sirindhorn Anthropology Centre (community-level data)

Conditions for success

  • LINE-based support channel ('@sim2learn') offering career guidance, mental-health support and scholarship information alongside connectivity
  • Use of community-level socio-economic data to target the new AI pathway system
  • Existing national distribution channel via SIM 2 Learn to build on

Common failure modes

  • Of 400,000+ students reached with free SIM cards, only 113,000 registered and just 18,000 actively used the service for learning
  • EEF's own Research Director says removing financial barriers alone does not address digital-literacy gaps and low motivation
  • The newer AI pathway-recommendation system is not yet independently evaluated

Where it fits

Governance type
government-linked national fund
Scale
national

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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