Student Trend Analysis for Foreign Education Employing Machine Learning: A Case Study from ‘Disha Consultants’, Gujarat, India

Manan Shah (), Ameya Kshirsagar and Tulasi Sushra
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Manan Shah: Pandit Deendayal Energy University
Ameya Kshirsagar: Symbiosis Institute of Technology
Tulasi Sushra: Pandit Deendayal Energy University

Annals of Data Science, 2024, vol. 11, issue 2, No 7, 588 pages

Abstract: Abstract For many years, there has been literature on study abroad, student mobility, and international student exchange; however, the scope & depth of this work has expanded dramatically in the recent two decades. Most of this research in comparative education studies is rarely published in its primary publications. This study report aims to give a complete overview of the trends and difficulties surrounding international student recruiting and assist institutional leaders & administrators in making informed choices and effectively setting priorities. We have performed EDA testing, a thorough analysis that helps discover data distribution. It is essential for all domains because it exposes trends, patterns, and relationships that are not immediately apparent. EDA is the most effective approach to finding outliers, but it might lead us wrong if not done correctly. We demonstrated that our research gives a suitable pragmatic answer for future International study patterns among students by conducting thorough trend analysis of varying detailed data obtained from various sources.

Keywords: Foreign education; Machine learning; Trend (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s40745-022-00431-7

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