SENTIMENT ANALYSIS ON STUDENTS’ PERSPECTIVE TOWARD ENGLISH ONLINE LEARNING USING WORD FREQUENCY ANALYSIS

Abstract

The post-pandemic situation has triggered a seismic shift in the education landscape, forcing educational institutions worldwide to transition to online learning platforms. Understanding students' perspectives towards this abrupt transformation is crucial for improving the quality of online education. This study employs sentiment analysis techniques, specifically Word Frequency Analysis, to gain insights into students' sentiments and opinions concerning online learning. Using a dataset of student responses collected through surveys and open-ended questions, the researchers conducted a comprehensive analysis of the words and phrases frequently used by students when describing their experiences with online learning. Through the systematic identification of prominent words and their frequencies, this research provides a valuable overview of the prevailing sentiments, concerns, and areas of satisfaction among students. The findings reveal a nuanced picture of students' attitudes. While positive sentiments such as “nyaman”, “baik”, and “responsif" are prevalent, there are also concerns and challenges highlighted, including 'isolation,' 'technical issues,' and 'communication difficulties.' Furthermore, the analysis uncovers variations in sentiment based on demographic factors, course types, and prior experience with online education. This research contributes to a deeper understanding of students' sentiments towards online learning, offering educators and policymakers valuable insights for enhancing the online learning experience. The Word Frequency Analysis methodology employed in this study proves to be a powerful tool for efficiently distilling the sentiments expressed in large datasets of qualitative responses, providing a foundation for further qualitative and quantitative investigations in the field of online education.