빅데이터를 이용한 사립 유치원 초임교사의 어려움에 대한 키워드 네트워크 분석

The Keyword Network Analysis of Challenges Faced by Novice Teachers in Private Kindergartens Using Big Data

Objective: This study aims to analyze the challenges encountered by novice teachers in private kindergartens through big data analysis, with a focus on identifying key themes and emotional responses. The findings will serve as foundational data for designing future support programs tailored to their needs. Methods: Data were collected from blogs, news articles, and online communities between March 1, 2021, and February 29, 2024, and analyzed using the Textom tool. Keywords were extracted using the TF-IDF(Term Frequency-Inverse Document Frequency) method, and their relationships were examined through CONCOR(CONvergence of iterated CORrelation) analysis. Additionally, sentiment analysis was conducted to evaluate the emotional responses of novice teachers. Results: The keyword analysis highlighted terms such as “school,” “education,” “children,” “teacher,” and “support” as central to the challenges faced by novice teachers. Sentiment analysis revealed a predominance of negative emotions, suggesting high levels of stress and dissatisfaction among this group. Conclusion/Implications: The findings offer valuable insights for improving teacher education programs and informing policy measures to better support novice teachers in private kindergartens