North Korea's state newspaper Rodong Sinmun published an article on August 9 arguing that IT education must adapt to the age of artificial intelligence. The paper said schools should strengthen computational thinking instruction and extend hands-on training so students can build complex programs on their own.
The article explained that IT education now needs to cover AI and the foundational technologies that support it, including big data, data science, network security, cloud computing, the Internet of Things, bioinformatics, and project management for complex program development.
Computational thinking takes center stage
Rodong Sinmun said a key focus of recent IT education is building computational thinking skills - the process of breaking complex problems into smaller subproblems and devising methods to solve them.
The paper raised a concern: because generative AI and cloud computing can independently produce text, video, and programs, many people now believe there's no need to engage in computational thinking. It pointed out that globally, people aged 17 to 25 tend to believe that AI "only provides the correct answers" and therefore avoid the practice.
Rodong Sinmun argued that AI, cloud computing, and the Internet of Things are realized through complex computational processes, and there are still unresolved issues before these technologies reach a level of accuracy people can trust. That's why, it said, computational thinking education should be strengthened.
Practical training extends
The article also called for more hands-on training. Schools previously ran 4-5 weeks of practical training to improve IT students' skills. Now, students are sent to companies or research institutions for 20-25 weeks to design and implement complex programs on their own, developing abilities in algorithm design, data structures, programming, and project management.
Rodong Sinmun said this approach lets students begin their own projects immediately after graduation, without a separate training period.
Why this matters for educators
The core lesson for educators is that AI tools don't replace problem-solving skills - they make them more important. Even as generative AI produces answers instantly, students still need computational thinking to evaluate those outputs and build reliable systems.
Teachers should consider how their curricula balance AI-assisted work with independent problem-solving exercises. Educators can explore AI for Education resources and use the AI Learning Path for Teachers course to build these skills.
Your membership also unlocks:
