Uncovering Insights from Teacher Feedback: A Sentiment Analysis Study at Cronasia Foundation College, Inc

The unprecedented integration of Information and Communication Technology (ICT) in education to improve information management, learning activities, and data-based decision making is an essential in the digital age. Using sentiment analysis, this study analyzes teacher feedback from Cronasia Foundation College, Inc. in the hope of unveiling emotional trends and critical institutional issues. Textual feedback was classified as having positive, neutral, or negative sentiment using natural language processing (NLP) and machine learning algorithms and analyzed for common themes. Results show more positive reactions associated with the instrumentality of advising and curriculum, as well as continued concerns over workload, student engagement, and administrative support. These findings provide practical insights for institutional planning and illustrate the power of sentiment analysis in crafting responsive, data-informed policies in higher education.

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Publication Details

Journal
International journal of research and scientific innovation
Published
2025-01-01
DOI
https://doi.org/10.51244/ijrsi.2025.12060017
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
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article

Uncovering Insights from Teacher Feedback: A Sentiment Analysis Study at Cronasia Foundation College, Inc

Rosso Cuyos
1 citations
International journal of research and scientific innovation
Online Learning and Analytics
1.69
article

Uncovering Insights from Teacher Feedback: A Sentiment Analysis Study at Cronasia Foundation College, Inc

Rosso Cuyos
article en
1 citations

Abstract

The unprecedented integration of Information and Communication Technology (ICT) in education to improve information management, learning activities, and data-based decision making is an essential in the digital age. Using sentiment analysis, this study analyzes teacher feedback from Cronasia Foundation College, Inc. in the hope of unveiling emotional trends and critical institutional issues. Textual feedback was classified as having positive, neutral, or negative sentiment using natural language processing (NLP) and machine learning algorithms and analyzed for common themes. Results show more positive reactions associated with the instrumentality of advising and curriculum, as well as continued concerns over workload, student engagement, and administrative support. These findings provide practical insights for institutional planning and illustrate the power of sentiment analysis in crafting responsive, data-informed policies in higher education.

International journal of research and scientific innovationVol. XII(VI)
Openalex Percentile: Top 12%
Online Learning and Analytics
1.69
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Uncovering Insights from Teacher Feedback: A Sentiment Analysis Study at Cronasia Foundation College, Inc — Rosso Cuyos · International journal of research and scientific innovation (2025) | TGRS Research Map | TGRS