Investigation on impact of reservation policy on student enrollment using data mining

Inderjeet Singh Bamrah, A. Girdhar
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引用次数: 3

Abstract

Indian education system has diversification in terms of reservation policy when it comes to student enrollment. This diversification leads to variability in the pattern of enrollment in the course and makes the related predictions quite difficult. The proposed work has focused on the reduction of the variability by associating student potential with the reservation policy to find its impact on the course. Linear regression analysis has been performed to find the dependency of sub-reservation and tertiary level reservation within a reservation policy. A hypothesis regarding average chance percentage for reserved and non-reserved category students has been tested and found to be in favor of reserved category students. Further, data mining tool on the enriched data set has been applied to disclose the hidden patterns and to perform enrollment related predictions.
基于数据挖掘的预约政策对招生的影响研究
在招生方面,印度教育体系在预留政策方面具有多样化。这种多样化导致了课程招生模式的变化,并使相关预测变得相当困难。建议的工作重点是通过将学生潜力与预订政策联系起来,以发现其对课程的影响,从而减少可变性。通过线性回归分析,找到了保留策略中子保留和三级保留的依赖关系。一个关于保留类和非保留类学生的平均机会百分比的假设已经被测试,并发现有利于保留类学生。进一步,在丰富的数据集上应用数据挖掘工具来揭示隐藏的模式,并进行与注册相关的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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