Toru Sugihara, Soichiro Aihara, S. Hirokawa, Takashi Nara
{"title":"An Analysis of Characteristics of Student-Athletes from Questionnaire by SVM","authors":"Toru Sugihara, Soichiro Aihara, S. Hirokawa, Takashi Nara","doi":"10.1109/IIAI-AAI.2017.215","DOIUrl":null,"url":null,"abstract":"What sort of care should a university take for student-athletes? To answer the question and to consider the future educational strategy are one of big issues for many universities. The authors created a questionnaire which consists of 77 questions with multiple choice form. We collected the responses from 100 student-athletes and 141 other students. The present paper analyzed the characteristic features of student-athletes. We considered 312 kinds of combination of question items and the response choices as words and the questionnaire record of a student as a document written in those words. Then we applied the text mining method SVM (support vector machine) and feature selection. As the result, we confirmed that we can distinguish student-athletes from other students with 90% accuracy based on 16 characteristic features such as (a) they spend much time on athlete club and not on study, (b) they want to work for economically rich life, (c) they think that it is advantageous to job hunting or graduate school if they have good grades and (d) they have less interests on international perspective in campus life.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2017.215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
What sort of care should a university take for student-athletes? To answer the question and to consider the future educational strategy are one of big issues for many universities. The authors created a questionnaire which consists of 77 questions with multiple choice form. We collected the responses from 100 student-athletes and 141 other students. The present paper analyzed the characteristic features of student-athletes. We considered 312 kinds of combination of question items and the response choices as words and the questionnaire record of a student as a document written in those words. Then we applied the text mining method SVM (support vector machine) and feature selection. As the result, we confirmed that we can distinguish student-athletes from other students with 90% accuracy based on 16 characteristic features such as (a) they spend much time on athlete club and not on study, (b) they want to work for economically rich life, (c) they think that it is advantageous to job hunting or graduate school if they have good grades and (d) they have less interests on international perspective in campus life.