Student Analysis and Prediction of performance using Machine learning
M.S.B Gayatri , M. Mounika, Y. ROHILA REDDY
The main aim of analyzing student performance is to find users opinions, identity the sentiments they express, and classify their polarity into positive, negative, and neutral categories because sentiments and opinions expressed by students and teachers are a valuable source of information not only for analyzing students’ behavior towards a course, topic, or teachers and student’s performance but also for reforming policies and institutions for their improvement. For this we are Trying out Machine learning techniques using sentiment analysis and graphical analysis and performing student and teacher performance analysis using the feedbacks given by them. Education data mining is very vast field. Our proposed system will mainly focus on student performance, student retention, Teaching effectiveness and student progression. So, our proposed system will analyze the feedback comments, to find the student view on professors base and also teachers comments on students’ performance on various parameter. By considering additional data like attendance, unit and semester grades and academic history will also help us to find extract reason behind the student’s comment. The use of additional data will also help us to find students at risk and prediction of end semester result.
Article Details
Unique Paper ID: 157045

Publication Volume & Issue: Volume 9, Issue 5

Page(s): 790 - 792
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