This study examines the impact of computer resources on student enrollment growth in 36 Indian states and union territories (UTs), specifically comparing government and government-aided schools with private schools using Kendall’s tau rank correlation method. The states and UTs are ranked based on their enrollment growth rate and the growth rate of the number of schools with computers in the last five years, from 2019–20 till 2023–24 and then, their association is analyzed. K-means clustering is applied to categorize states into distinct groups based on these rankings within each school category. The study aims to perform a comparative analysis of government, government-aided and private schools on these parameters. Further, the states are divided into clusters based on these growth rates to understand whether all the states behave the same way. The findings indicate that in government schools, increased availability of personal computers has not led to a rise in student enrollment but there is some impact in the private schools. This suggests that availability of computers alone may not be sufficient to attract or retain students. Policy implications emphasize balancing ICT investments and utilizing the current available PCs across school types and regions to increase the enrollments.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Statistical Analysis of the Impact of Computer Resources on Enrollment Growth: A Comparative Study of Government and Private Schools in India

  • Rabia Kamra,
  • Shifa Soni,
  • Umesh Gupta

摘要

This study examines the impact of computer resources on student enrollment growth in 36 Indian states and union territories (UTs), specifically comparing government and government-aided schools with private schools using Kendall’s tau rank correlation method. The states and UTs are ranked based on their enrollment growth rate and the growth rate of the number of schools with computers in the last five years, from 2019–20 till 2023–24 and then, their association is analyzed. K-means clustering is applied to categorize states into distinct groups based on these rankings within each school category. The study aims to perform a comparative analysis of government, government-aided and private schools on these parameters. Further, the states are divided into clusters based on these growth rates to understand whether all the states behave the same way. The findings indicate that in government schools, increased availability of personal computers has not led to a rise in student enrollment but there is some impact in the private schools. This suggests that availability of computers alone may not be sufficient to attract or retain students. Policy implications emphasize balancing ICT investments and utilizing the current available PCs across school types and regions to increase the enrollments.