Sentiment Analysis of Student Evaluation for Teachers Using Valence-Aware Dictionary and Sentiment Reasoner

Authors

  • Kristel Anne B. Telmo Department of Information and Technology, Cavite State University, Cavite, Philippines
  • Kervie V. Alviola Department of Information and Technology, Cavite State University, Cavite, Philippines
  • Jazler Jhon S. Desamparado Department of Information and Technology, Cavite State University, Cavite, Philippines
  • John Nathaniel A. Cabigan Department of Information and Technology, Cavite State University, Cavite, Philippines
  • Cereneo S. Santiago Jr. Department of Information and Technology, Cavite State University, Cavite, Philippines
  • Richard Aries A. Shimada Department of Information and Technology, Cavite State University, Cavite, Philippines

DOI:

https://doi.org/10.69569/jip.2024.0328

Keywords:

Teaching effectiveness, Student Evaluation of Teaching (SET), Sentiment analysis, Feedback collection

Abstract

This paper analyzed the quality of teaching using the Student Evaluation of Teaching (SET). The Valence Aware Dictionary and Sentiment Reasoner (VADER) was utilized to assess textual comments, providing a comprehensive view of teaching effectiveness beyond numerical ratings. The objectives were to identify faculty strengths and areas for improvement based on student feedback, analyze sentiment toward teaching methods, and determine the optimal number of clusters within the dataset. The analysis included 28,222 student comments from three semesters, preprocessed through tokenization, stopword removal, part-of-speech tagging, and lemmatization. A word cloud visualized common terms, while K-means clustering and the Elbow method identified five as the optimal number of clusters. Results indicate that most comments are positive, emphasizing effective teaching methods' role in creating a positive educational experience. The findings suggest integrating machine learning with VADER and expanding the dataset for broader insights. Institutions should develop effective teaching strategies, prioritizing regular feedback collection and analysis.

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Published

2024-08-02

How to Cite

Telmo, K. A., Alviola, K., Desamparado, J. J., Cabigan, J. N., Santiago, C. J., & Shimada, R. A. (2024). Sentiment Analysis of Student Evaluation for Teachers Using Valence-Aware Dictionary and Sentiment Reasoner. Journal of Interdisciplinary Perspectives, 2(9), 160–169. https://doi.org/10.69569/jip.2024.0328

Issue

Vol. 2 No. 9 (2024): September 2024 Issue

Section

Articles

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