evidoria

← Back to browse

Good practice Imported

ECCU Generative AI & Python Summer Camp — Eastern Caribbean Youth Build Chatbots Across Seven Islands

Saint Kitts and Nevis · Basseterre · See the Saint Kitts and Nevis profile · See the Basseterre profile

Evidence: Descriptive / self-reported Top 63% 47/100 · Ask Evidence Copilot about this practice

ECCB's annual Generative AI & Python Summer Camp trained close to 400 teens (13-18) across seven Eastern Caribbean islands in 2025, who built 21 working chatbots for real civic problems - funded jointly with Taiwan under the Bank's 'Big Push' digital-transformation strategy.

~400 students
Participants in the 2025 edition (2025)
21 projects
Chatbots built by teams (2025)
7 territories
ECCU territories participating (2025) (2025)
500 students
Target students for the 2026 edition (2026 target)

Details

Maturity
Scaling
Promoter
Eastern Caribbean Central Bank (ECCB), with the Republic of China (Taiwan)
Period
2024-2026 (annual; 3rd edition scheduled July 2026)
Keywords
digital transformation, youth education, fintech literacy, ICT skills

Context

The Eastern Caribbean Central Bank (ECCB) conceived the Generative AI and Python Summer Camp in 2024 as part of its 'Big Push' digital-transformation strategy, funded jointly with the Republic of China (Taiwan), for the eight ECCU member territories (Antigua and Barbuda, Dominica, Grenada, Montserrat, St Kitts and Nevis, Saint Lucia, St Vincent and the Grenadines, and Anguilla).

Activities

In the 2025 second edition, close to 400 participants aged 13 to 18 from seven of the eight ECCU territories spent four weeks learning Python programming, generative AI, data analytics, user-experience and multimedia design, building 21 working chatbots addressing real local problems such as financial education, crime mitigation and heritage tourism.

Results

Teams presented at a Closing Ceremony and Regional Showcase in Basseterre, St Kitts and Nevis (29 August 2025), where projects were judged live; St Kitts and Nevis team Vibe Tribe won the multimedia showcase, with Antigua and Barbuda's Wadadli Tech and Mystic Wolves placing second and third. A third edition is scheduled for July 2026, expanding to all eight ECCU territories (adding Anguilla) with a target of 500 students annually.

Conclusions

No independent, standardised learning-outcome assessment (e.g. pre/post skills testing) has been published; the public evidence to date is participation counts, working outputs and named competition results rather than measured learning gains.

Implementation
Indicative cost
Low (< €50k) — No specific budget figure is reported; the camp is funded jointly by ECCB and the Republic of China (Taiwan) under the Bank's 'Big Push' digital-transformation strategy.
Time to results
Medium (1–3 years) — Annual since 2024; second edition in 2025, third edition scheduled July 2026 expanding to all eight ECCU territories.
Staffing & skills
Eastern Caribbean Central Bank (ECCB) organises and hosts the camp, Republic of China (Taiwan) co-funds the programme, Camp facilitators and mentors deliver the curriculum (no formal teacher professional-development track is described)

Conditions for success

  • Four-week structured curriculum spanning Python, generative AI, data analytics, UX and multimedia design
  • Regional showcase/competition format with public judging to motivate youth teams
  • Recurring annual funding from ECCB and Taiwan enabling year-on-year growth

Common failure modes

  • No pre/post skills testing has been published, so learning gains are not independently measured
  • No structured teacher professional-development or certification track for ECCU educators is described

Where it fits

Governance type
regional central bank (ECCB) partnership with a bilateral funder (Taiwan), spanning eight small-island states
Scale
~400 students across 7-8 territories in 2025, targeting 500 in 2026
Income level
upper-middle-income (varies by territory)

Do you run this practice? Claim it — verified implementers get a public contact pathway and can propose corrections.

Data sources

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

Similar practices you may find useful