Issue |
SHS Web Conf.
Volume 156, 2023
International Conference on Teaching and Learning – Digital Transformation of Education and Employability (ICTL 2022)
|
|
---|---|---|
Article Number | 04001 | |
Number of page(s) | 4 | |
Section | T&L Intelligence and Analytics | |
DOI | https://doi.org/10.1051/shsconf/202315604001 | |
Published online | 13 January 2023 |
Predicting Global Ranking of Universities Across the World Using Machine Learning Regression Technique
1
Middle East College, Muscat, Sultanate of Oman
2
Middle East College, Muscat, Sultanate of Oman
3
Srinivasa University Managalore, India
4
Middle East College, Muscat, Sultanate of Oman
prakash@mec.edu.om www.mec.edu.om
vishal@mec.edu.om www.mec.edu.om
nethrakumar.ccis@srinivasuniversity.edu.in www.srinivasuniversity.edu.in
jitendra@mec.edu.om www.mec.edu.om
Digital transformation in the field of education plays a significant role especially when used for analysis of various teaching and learning parameters to predict global ranking index of the universities across the world. Machine learning is a subset of computer science facilitates machine to learn the data using various algorithms and predict the results. This research explores the Quacquarelli Symonds approach for evaluating global university rankings and develop machine learning models for predicting global rankings. The research uses exploratory data analysis for analysing the dataset and then evaluate machine learning algorithms using regression techniques for predicting the global rankings. The research also addresses the future scope towards evaluating machine learning algorithms for predicting outcomes using classification and clustering techniques.
Key words: Digital Transformation / Teaching and Learning / Machine Learning / Regression / Classification / Clustering
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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