research-article

Analysis and Prediction of QS World University Rankings based on Data Mining Technology

Authors:

Xianglan HanAuthors Info & Claims

ICEMT '22: Proceedings of the 6th International Conference on Education and Multimedia Technology

Pages 60 - 64

https://doi.org/10.1145/3551708.3556207

Published: 18 November 2022 Publication History

Abstract

University rankings are increasingly important as a means of evaluating the quality of higher education institutions. They are significant not only in the recruitment of students but also in the allocation of government funds for higher education. The Quacquarelli Symonds (QS) ranking system is currently one of the most well-known world university rankings. We provide insights into the QS world university rankings 2022, which is based on six simple indicators to represent university performance. This study consists of two parts. In the first part, the geographical coverage of the ranking list is analyzed. Then, the histogram and kernel density estimation are utilized to detect the distribution of each indicator. Next, a heat map based on Pearson Correlation Coefficient is plotted to display the correlations between indicators. In the second part, three regression models, namely linear regression, random forest regression, and XGBoost, are used to identify which technique is more appropriate to predict the performance of a university. In order to access their accuracy, the MAE (Mean Absolute Error), MSE (Mean Squared Error), and RMSE (Root Mean Squared Error) of the three models are compared. The results of the experiments demonstrate that XGBoost has the best performance in predicting university rankings. This research provides a better understanding of the QS ranking system.

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Digital Library

Cited By

Tóth BMotahari-Nezhad HHorseman NBerek LKovács LHölgyesi ÁPéntek MMirjalili SGulácsi LZrubka Z(2024)Ranking resilience: assessing the impact of scientific performance and the expansion of the Times Higher Education Word University Rankings on the position of Czech, Hungarian, Polish, and Slovak universitiesScientometrics10.1007/s11192-023-04920-1129:3(1739-1770)Online publication date: 6-Feb-2024
https://dl.acm.org/doi/10.1007/s11192-023-04920-1
Tangprasert SSonthana RNilsiam YNuchitprasitchai SBhumpenpein N(2023)Data-Driven Heart Disease Risk Prediction with Machine Learning on Healthcare Datasets2023 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)10.1109/RI2C60382.2023.10355977(220-223)Online publication date: 24-Aug-2023
https://doi.org/10.1109/RI2C60382.2023.10355977
Gilmour P(2023)Enhancing research collaboration within a large university departmentInnovations in Education and Teaching International10.1080/14703297.2023.220906461:4(622-635)Online publication date: 4-May-2023
https://doi.org/10.1080/14703297.2023.2209064

Index Terms

Analysis and Prediction of QS World University Rankings based on Data Mining Technology
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Student assessment

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ICEMT '22: Proceedings of the 6th International Conference on Education and Multimedia Technology

July 2022

482 pages

ISBN:9781450396455

DOI:10.1145/3551708

Copyright © 2022 ACM.

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Publication History

Published: 18 November 2022

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General Scientific Research Projects of Zhejiang Education Department
the Zhejiang Provincial Natural Science Foundation of China
Ningbo Natural Science Foundation of China
Ningbo Science and Technology Special Projects of China
Zhejiang Province First-class Course Construction Project
School-level Teaching and Research Project

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ICEMT 2022

ICEMT 2022: 2022 6th International Conference on Education and Multimedia Technology

July 13 - 15, 2022

Guangzhou, China

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Cited By

Tóth BMotahari-Nezhad HHorseman NBerek LKovács LHölgyesi ÁPéntek MMirjalili SGulácsi LZrubka Z(2024)Ranking resilience: assessing the impact of scientific performance and the expansion of the Times Higher Education Word University Rankings on the position of Czech, Hungarian, Polish, and Slovak universitiesScientometrics10.1007/s11192-023-04920-1129:3(1739-1770)Online publication date: 6-Feb-2024
https://dl.acm.org/doi/10.1007/s11192-023-04920-1
Tangprasert SSonthana RNilsiam YNuchitprasitchai SBhumpenpein N(2023)Data-Driven Heart Disease Risk Prediction with Machine Learning on Healthcare Datasets2023 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)10.1109/RI2C60382.2023.10355977(220-223)Online publication date: 24-Aug-2023
https://doi.org/10.1109/RI2C60382.2023.10355977
Gilmour P(2023)Enhancing research collaboration within a large university departmentInnovations in Education and Teaching International10.1080/14703297.2023.220906461:4(622-635)Online publication date: 4-May-2023
https://doi.org/10.1080/14703297.2023.2209064

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