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

机译:SVM研究问卷的学生运动员特征分析

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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.
机译:大学应该为学生运动员提供什么样的护理?为了回答问题,并考虑未来的教育战略是许多大学的重要问题之一。作者创建了一个调查问卷,由77个问题组成,具有多种选择形式。我们收集了100名学生运动员和141名其他学生的回复。本文分析了学生运动员的特征。我们认为312种问题项目和响应选择作为学生作为文字的文字和调查表记录。然后我们应用了文本挖掘方法SVM(支持向量机)和特征选择。结果,我们确认我们可以将学生运动员与基于16个特征的特征(A)在运动员俱乐部(A)上花费很多时间而不是在学习中,(B)对于经济上丰富的生活,(c)他们认为,如果他们有良好的成绩和(d),他们对校园生活中的国际角度较低,他们有利于求职或毕业生。

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