COMPARATIVE ANALYSIS OF REGRESSION ALGORITHMS FOR PREDICTING STUDENTS' OVERALL RATINGS
DOI:
https://doi.org/10.53555/f3ymeg32Abstract
In the rapidly evolving landscape of education, the integration of Artificial Intelligence (AI) has revolutionized the way we assess students. This research study focuses on the development and evaluation of a modern Machine Learning (ML) model designed to allocate comprehensive ratings to a diverse group of 10 students. The model's objective is to assess students not merely on their academic achievements but also on a holistic scale, taking into account a wide array of parameters, as detailed below.
Various factors were systematically analyzed and integrated, including academic performance, extracurricular activities, study routines, and personal attributes, among others. This comprehensive approach seeks to provide a more nuanced and equitable representation of a student's overall capabilities and potential.
To determine the most effective ML regression algorithm for predicting these holistic ratings, a rigorous comparative analysis was conducted, evaluating the performance of multiple algorithms. The study considered factors such as prediction accuracy, model interpretability, and computational efficiency.
The findings of this research shed light on which ML regression algorithm best predicts the overall ratings for the students in question, offering insights into the potential for AI-driven holistic assessment in educational settings. By embracing AI technologies, educators and institutions can enhance their understanding of students, ultimately contributing to more tailored and equitable educational experiences. This research carries implications not only for educational practitioners but also for policymakers and technologists seeking to leverage AI for educational improvement.
The detailed methodology, results, and practical implications of this study are discussed in the full research paper. It contributes to the ongoing dialogue on the integration of AI in education and its potential to create more inclusive and effective learning environments.
References
Text
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Journal of Advance Research in Computer Science & Engineering (ISSN 2456-3552)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Terms & Condition
Submission -
Author can submit the manuscript through our online submission process or email us at the designated email id in contact details.
The other mode of submission not accepted than online and email.
Before submission please read the submission guidelines.
NN Publication accepts only article submitted in pdf/doc/docx/rtf file format. Another format except given file formats will no be considered .
Author will be responsible for the error mistakes in the submission files. The minor changes can be done without any cost after publication. But for major changes NN Publication may charges you the editing charges.
Publication (Online) -
The online publication is scheduled on last date of every month, but it can be delayed by 24 to 48 hours due to editorial process if huge number of articles comes to publish in single issue.
Automatic notificatation email will be sent to the all users on publication of an issue, so its author’s duty to check their email inbox or SPAM folder to get this notification.
After publication of article author can not withdraw their article.
If editor’s found any issue after publication of article then the NN Publication have the authority to remove the article from online website.
No refund will be provided after online publication of article.
Publication (Print) -
The print copy publication are sent as per the author’s request after 2 weeks of online publication of that issue.
NN Publication will ship the article by India Post and provide the consignment number on dispatch of print copy.
NN Publication follows all the guidelines of delivery provided by IndiaPost and hence not responsible for delay in delivery due to any kind of reasons.
Refund of hard copy will not be provided after dispatch or print of the journal.
NN Publication will be responsible for raise a complain if there is any issue occurs in delivery, but still will not be responsible for providing the refund.
NN Publication will be responsible to resend the print copy only and only if the print copy is lost or print copy is damaged in delivery / or there is delay more than 6 months.
According to India Post the delivery should be completed with in 1-3 weeks after dispatch of articles.
Privacy Policy-
NN Publicationl uses the email ids of authors and editors and readers for sending editorial or publication notification only, we do not reveal or sell the email ids to any other website or company.
