A Sentiment Analysis of College Students’ Feedback on their Teacher’s Teaching Performance During Online Classes

This study aimed to unveil the sentiments of college students' feedback on their teacher's teaching performance during online classes. The research utilized a qualitative approach, explicitly employing text mining. Orange software determined the most frequently used words illustrating teachers' teaching performance during online courses. Moreover, Latent Semantic Indexing (LSI) was utilized to reveal how those frequently used words were structured. Meanwhile, the study showed that the words "teacher," "class," "us," "student," "online," "teaching," "happy," "learning," "understand," and "good" were most frequently used in college students' sentiments regarding their teacher's performance during online classes. The study also indicated that most students have positive feedback on their teachers' teaching performance in online courses. Therefore, the findings suggest that teachers have the abilities and knowledge to successfully impart lessons to their students despite the enormous dilemma the pandemic has brought about in every sector, especially in education.