Performance Analysis on Student Feedback using Machine Learning Algorithms Abstract: It investigates opinion mining by means of supervised learning techniques to search out the emotion of the student input bolstered characterized choices of instructing and learning.

It investigates opinion mining by means of supervised learning techniques to search out the emotion of the student input bolstered characterized choices of instructing and learning.

Charts are provided by the system for simple student performance’s interpretation. From the reviews on these existing systems, useful techniques and features might be applied into the proposed system for a more

The study focuses on popular machine learning algorithms and evaluates their effectiveness in predicting student performance based on multiple criteria. The findings demonstrate that the proposed framework has better performance in comparison to those currently in use in terms of predictive power.

Jan 1, 2021 · The paper presents analyze of the results of a study conducted at the Trakia University of Stara Zagora. The study aims to identify the most significant features that affect student performance and to select the most efficient machine-learning algorithm to …

Sentiment analysis system using NLP and machine learning techniques to determine the polarity of the feedback obtained from students in order to improve teaching and learning.

Student Performance Analysis is used to predict the performance of a student based on various factors like marks, attendance, staff rating, ragging, social media usage, extra-curricular and stress factor using the following machine learning algorithms.

Performance Analysis on Student Feedback using Machine Learning Algorithms Abstract: It investigates opinion mining by means of supervised learning techniques to search out the emotion of the student input bolstered characterized choices of instructing and learning.

Abstract: Predicting student data to improve instructor and learner more efficiently in teaching and learning. It also strengthens contact between administrators, teachers and learners and helps monitor the behavior of students at multiple levels, such as class assignments, workshops, internal assessments and final exams.

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 …