Institutional Perspectives on Personalized Education: A Topic Modeling Analysis of Korean News Media
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This study aims to examine trends in personalized education in South Korea by analyzing major keywords from big news data using topic modeling techniques. To achieve this objective, we analyzed 19,874 news articles published in South Korea between January 2018 and October 2023. The keywords were categorized into three distinct time periods: January 2018 to December 2019 (Period 1), January 2020 to December 2021 (Period 2), and January 2022 to October 2023 (Period 3). The results reveal distinct keyword trends across the three periods. In Period 1, keywords such as “university,” “junior college,” “Seoul,” and “Samsung Electronics” were prominent. In Period 2, “Corona,” “Seoul,” and “AI” emerged as significant terms. In Period 3, “government,” “AI,” “region,” “students,” and “youth” were identified. These findings indicate a focus on personalized education and competency development at various levels, including local, national, and institutional (universities and colleges). We can confirm the increasing prevalence of personalized education in response to the growing demand for digital and AI technologies, with numerous colleges nationwide promoting these initiatives at a national level. Additionally, the application of personalized education was observed as a measure to support underachieving students, addressing issues such as educational gaps and foundational education. This suggests a blend of both universal and specific approaches to personalized education. Based on these findings, the study recommends that to properly progress this idea, an elaborate theoretical framework that creates a balance between the pedagogical objective of satisfying the requirements of particular learners and adaptive learning technology would be needed.
Abstract
This study aims to examine trends in personalized education in South Korea by analyzing major keywords from big news data using topic modeling techniques. To achieve this objective, we analyzed 19,874 news articles published in South Korea between January 2018 and October 2023. The keywords were categorized into three distinct time periods: January 2018 to December 2019 (Period 1), January 2020 to December 2021 (Period 2), and January 2022 to October 2023 (Period 3). The results reveal distinct keyword trends across the three periods. In Period 1, keywords such as “university,” “junior college,” “Seoul,” and “Samsung Electronics” were prominent. In Period 2, “Corona,” “Seoul,” and “AI” emerged as significant terms. In Period 3, “government,” “AI,” “region,” “students,” and “youth” were identified. These findings indicate a focus on personalized education and competency development at various levels, including local, national, and institutional (universities and colleges). We can confirm the increasing prevalence of personalized education in response to the growing demand for digital and AI technologies, with numerous colleges nationwide promoting these initiatives at a national level. Additionally, the application of personalized education was observed as a measure to support underachieving students, addressing issues such as educational gaps and foundational education. This suggests a blend of both universal and specific approaches to personalized education. Based on these findings, the study recommends that to properly progress this idea, an elaborate theoretical framework that creates a balance between the pedagogical objective of satisfying the requirements of particular learners and adaptive learning technology would be needed.
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