Abstract
Objectives: The study has been carried out to present the sentiment analysis model for improving the quality of teaching in academic institutions, particularly at universities. The purpose of this study is to explore the different machine learning techniques to identify its importance as well as to raise interest in this research area. In this regard, the student feedback dataset has been collected at the end of the semester Fall-2018 from both Public and Private sector universities of Karachi, through the Google Survey Forms. The dataset contains valuable information about the quality of teaching and learning. Methods/Statistical Analysis: The model used the Multinomial Naive Bayes, Stochastic Gradient Decent, Support Vector Machine, Random Forest and Multilayer Perceptron Classifier. The result was analyzed through the evaluation metrics i.e. Confusion Matrix, Precision, Recall and F-score. Findings: It is found that the performance of MNB and MLP remained effective as compared to other approaches. It is recommended that MNB and MLP should be used in the research context for the classification of the text. It has great significance for future researchers in sentences and text classification. Application/Improvements: The study helps for improving the quality of teaching in education system. And moreover, it will be upgrade by increasing the data samples of neutral comments in dataset. Keywords: Course Evaluation, Machine Learning, Opinion Mining, Sentiment Analysis, Student Feedback
Highlights
The field of Sentiment Analysis emerged a most important field in academic research in the area of Natural Language Processing (NLP) and Machine Learning during the last decade
The performance of learning models is assessed through the following metrics: Accuracy: Accuracy is defined as the ratio between the number of correct predictions made by the model and the number of rows in the dataset
Student feedback dataset is collected at the end of semester fall 2018 from different universities located in Karachi, Sindh
Summary
The field of Sentiment Analysis emerged a most important field in academic research in the area of Natural Language Processing (NLP) and Machine Learning during the last decade. Which identifies and extracts subjective information in the source material and helping a business to understand the social sentiment of their brand, The most common practice in Educational Institutions is to get feedback from students to analyze their sentiments towards subject teacher in order to improve the performance of the teachers. This approach of assessment through such feedbacks is usually commenced at the end of the semester with the use of survey forms. Evaluate the performances of each subject techniques and perform the comparison analysis with accuracy
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