Maryli F. Rosas, Shaneth C. Ambat, Melvin A. Ballera
{"title":"Data Mining of Students' Response on the University Services using Chi-square Automatic Interaction Detector (CHAID) Algorithm","authors":"Maryli F. Rosas, Shaneth C. Ambat, Melvin A. Ballera","doi":"10.1109/ICKII.2018.8569209","DOIUrl":null,"url":null,"abstract":"Students' insights are very vital in the continuous quality improvement of a university. Students are the primary consumers in higher education institution services [1].One way to measure the quality of education is through the satisfaction level of the students based on students' overall university experience. Implementation of logistic regression and CHAID Algorithm was used to create the recommendation plan.Text analytics was integrated to extract key phrases and compute sentiment score to classify the comments according to satisfaction level.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICKII.2018.8569209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Students' insights are very vital in the continuous quality improvement of a university. Students are the primary consumers in higher education institution services [1].One way to measure the quality of education is through the satisfaction level of the students based on students' overall university experience. Implementation of logistic regression and CHAID Algorithm was used to create the recommendation plan.Text analytics was integrated to extract key phrases and compute sentiment score to classify the comments according to satisfaction level.