Team Monolith and Smart Talent Development Institute Near Completion of 2026 AI Partnership Project
Translated from Korean and summarized by DistantNews. Read the original for the full story.
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- A Korean data and AI education program for middle and high school students is nearing completion after 997 students joined from 70 schools.
- Students worked through six stages, from choosing Sustainable Development Goals topics and collecting data to training AI models and producing final projects.
- Middle school students built a heat-island solutions webpage, while high school students developed diabetes-risk web applications and prevention games.
A youth AI education project in South Korea has entered its final stage with more students taking part than organizers initially planned. Team Monolith and the Smart Talent Development Institute said 997 students from 76 clubs at 70 schools participated, exceeding the target of 960.
The 16-session program forms part of the 2026 AI Partnership Project, hosted by the Korea Foundation for the Advancement of Science and Creativity. It asks students to define problems from everyday life and seek solutions using data and artificial intelligence.
The curriculum follows six stages: selecting a Sustainable Development Goal topic, collecting data, preprocessing it, visualizing the results, training an AI model and producing a final project.
Middle school students measured and analyzed temperature and humidity at their schools with micro:bit sensors. They then used Entry-based AI training to create a webpage proposing solutions to the urban heat-island effect.
High school students analyzed diabetes-related data and built Python-based regression and classification models to provide disease-risk guidance. Their projects also included a web application and a game presenting diabetes-prevention guidelines.
About this summary
Originally published by Dong-A Ilbo in Korean. Translated, summarized, and contextualized automatically by DistantNews, with a note on how the source frames the story. Not individually reviewed before publishing. How this works.
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