{"title":"Investigation on impact of reservation policy on student enrollment using data mining","authors":"Inderjeet Singh Bamrah, A. Girdhar","doi":"10.1109/ICCIC.2015.7435773","DOIUrl":null,"url":null,"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.","PeriodicalId":276894,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","volume":"526 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIC.2015.7435773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.