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Gwangju Education Superintendent Candidate Park Hyeja: "Customized Classes Needed Using 'Big Data'"

Gwangju Education Superintendent Candidate Park Hyeja: "Customized Classes Needed Using 'Big Data'"

[Asia Economy Honam Reporting Headquarters Reporter Yoon Jamin] Park Hyeja, a preliminary candidate for Superintendent of Education of Gwangju Metropolitan City, emphasized the need for customized classes using big data and learning history management to improve regional academic achievement.


Candidate Park explained, "Offline-centered classroom instruction has had limitations in managing individual students' learning," adding, "Due to differences in students' learning abilities, it was difficult to provide personalized instruction in the same space."


As an alternative, she proposed AI-based customized remote education. Students can learn without constraints or burdens through AI based on big data, and teachers can increase work concentration by utilizing artificial intelligence.


The learning data acquired this way will be managed using big data. Quantitative and qualitative evaluation results accumulated from elementary to high school will be used for character education and career guidance, and continuous accumulation of data will enable effective student management.


Until now, existing NEIS data was not linked when students advanced to higher-level schools, so it was not utilized by those schools. However, with the new NEIS system and the establishment of the Future Education Institute, big data history management will allow for detailed guidance for students.


Candidate Park said, "I will lead innovation in Gwangju education by restoring the declining academic achievement of Gwangju students through personalized learning and big data history management, and by strengthening character education through changes in the educational environment."


Meanwhile, on the 29th of last month, Candidate Park held a policy press conference for the recovery of academic achievement in Gwangju. Subsequently, she proposed measures such as a demand-centered high school assignment system, big data-based personalized education, and a gradual reduction in class sizes starting from first grade in elementary school from the 2023 academic year.


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