An Analysis of Characteristics of Student-Athletes from Questionnaire by SVM

Toru Sugihara, Soichiro Aihara, S. Hirokawa, Takashi Nara
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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.
基于支持向量机的学生运动员问卷特征分析
大学应该对学生运动员采取什么样的照顾?如何回答这个问题,如何思考未来的教育战略,是许多高校面临的重大问题之一。作者制作了一份由77个选择题组成的问卷。我们收集了100名学生运动员和141名其他学生的回复。本文分析了大学生运动员的特点。我们将312种问题项和回答选项的组合作为单词,将学生的问卷记录作为用这些单词写成的文档。然后应用支持向量机(SVM)和特征选择方法进行文本挖掘。结果,我们证实,我们可以区分学生运动员与其他学生有90%的准确率基于16个特征,如(a)他们花了很多时间在运动员俱乐部,而不是在学习上,(b)他们想要为经济富裕的生活而工作,(c)他们认为如果他们有好的成绩,这对找工作或研究生院是有利的,(d)他们在校园生活中对国际视野的兴趣较少。
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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