Author : Dr. Vijaykumar S. Bidve 1
Date of Publication :12th August 2021
Abstract: The study has been carried out to present the student feedback system analysis model for improving the quality of teaching in academics institution and universities. The system mainly presents a combination of machine learning algorithm and textual feedback. In this system has been routed towards student’s feedback analysis in the form of comments, opinion, and reviews regarding the performance of teachers. The textual feedback, provides useful insights to the overall teaching quality and suggests valuable ways for improving teaching methodology. The purpose of this study is to explore the different machine learning techniques to identify its importance. The various machine learning techniques involves SVM, Random Forest, Naïve Bayes algorithm and lexical analysis out of which SVM has the best accuracy but takes more time in training for the large dataset and it is used for regression and classification to classify the text. The dataset contains valuable information about the quality of teaching and learning. This work examine the textual comments present in the text document for classification of student’s feedback based on polarity that is positive, negative and neutral. The system helps to reduce the manual work and collects the feedback and stores them in a database which can be authorized person. The analysis of the feedback is provided to the teacher in the form of ratings and graphs so the data visualization becomes easier. This system is an efficient approach for providing qualitative feedback for teachers that improves the students learning.
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