Media Article Text Analysis in the Context of Distance Education: Focusing on South Korea Cover Image

Media Article Text Analysis in the Context of Distance Education: Focusing on South Korea
Media Article Text Analysis in the Context of Distance Education: Focusing on South Korea

Author(s): Youngho Lee
Subject(s): Education and training, Distance learning / e-learning
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Distance learning; topic modeling analysis; semantic network analysis; sentiment analysis

Summary/Abstract: The impact of COVID-19 pandemic is far-reaching, encompassing the social, economic, and psychological aspects of the society. . In order to prevent the spread of COVID-19, various countries, including South Korea, have entered into long-term home care and distance learning systems. However, distance learning experiments conducted in many countries have raised whether face-to-face education can be replaced by distance learning. Therefore, this study analyzed public opinion, social perception, and field trends based on media reports on remote learning. For this purpose, 2,600 articles from 11 newspapers and four broadcasters related to remote learning were collected in this study. Based on this data, keyword trend analysis, topic modeling analysis, semantic network analysis, and emotion analysis were performed. This study provides valuable insights into the impacts and perceptions of remote learning during the COVID-19 pandemic. It highlights the complexities of remote education, from influencing educational policies to affecting students' and parents' emotional states. The findings underscore the potential of remote learning in driving educational innovation while also pointing out its role in widening educational disparities. This research offers essential perspectives for shaping future educational strategies in crisis situations, emphasizing a balanced approach to harness the benefits of remote learning while mitigating its challenges.

  • Issue Year: 13/2024
  • Issue No: 1
  • Page Range: 414-421
  • Page Count: 8
  • Language: English