汽车专业学生工作兴趣类型与学业成绩分析

Wan-Mook Choi, Jinyong Kim
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摘要

STRONGTM职业兴趣测试是职业兴趣测试的标准化工具,于2022学年第一学期的5月和2022学年第二学期的9月进行。分析工具采用SPSS 14.0软件,通过频率分析、均值分析、相关分析和方差分析,对GOT、BIS、PSS和学业成绩进行分析。首先,汽车专业学生的职业兴趣类型在第一种代码下的R值为86%,在第二种代码下的R值为46.8%,在第三种代码下的R值为36.4%,因此R类型的比例较高。其次,在GOT与基本兴趣量表(BIS)的相关分析中,分析发现在BIS的R和R量表中,机械领域的相关性最高(0.963)。这一结果表明,学生对与机器有关的工作和活动有很高的兴趣。第三,在GET与学业成绩的分析中,如前所述,我们将field类型分析为学业成绩最低的类型,并且每种类型的学习水平没有显著差异。在未来,学习成绩需要通过文科和专业来分析,除了兴趣之外,还需要考虑价值观、学习态度和学习方法来进行详细的分析。第四,在个人特征量表分析(PSS)中,他们倾向于独自工作,更喜欢实践资格,短期学习,并以参与式领导的方式执行他们所指示的事情。此外,分析认为,人们更喜欢挑战自己,而不是冒险,因此有必要设计课程,使他们能够在学校现场的课堂上展示或挑战自己,并参加证书,比赛和比赛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Job Interest Type and Academic Achievement of Automobile Major Students
This study was conducted to identify the suitability of majors and jobs through an analysis of the career interest types and academic achievements of automotive students in the engineering department of Y University, and to use them as basic data for learning guidance, career guidance, and curriculum development. The STRONGTM Occupational Interest Test, a standardization tool for occupational interest tests, was conducted in May of the 2022 academic year, the first semester, and in September of the 2022 academic year, the second semester. The analysis tool used SPSS 14.0 to analyze GOT, BIS, PSS, and academic achievement by performing frequency analysis, mean analysis, correlation analysis, and variance analysis. First, the type of career interest of automotive students is 86% R when examined with the 1st code, R is 46.8% when considering the 2nd code, and R is 36.4% when considering both 3rd codes, so the proportion of R type is high. Therefore, it is necessary to prepare a study guidance and career guidance plan at the department level that takes into account the characteristics of the field type presented in the previous research. Second, in the correlation analysis of GOT and the Basic Interest Scale (BIS), it was analyzed that among the BIS scales of R and R, the mechanical field had the highest correlation (0.963). This results suggest that students have a very high interest in jobs and activities that work with machines. Third, in the analysis of GET and academic achievement, as mentioned in the previous study, the field type was analyzed as having the lowest academic achievement, and there was no significant difference in learning level for each type. In the future, academic achievement needs to be analyzed by subjects of liberal arts and majors, and detailed analysis is required considering values, learning attitudes, and learning methods in addition to interests. Fourth, in the Analysis of the Personal Characteristics Scale (PSS), they tend to prefer to work alone, preferring practical qualifications, short-term learning, and carrying out what they are directed to do with participatory leadership. In addition, it is analyzed that people prefer to challenge themselves towards adventure, so it is necessary to design lessons so that they can present or challenge themselves in class at school sites, and participate in certificates, competitions, and competitions.
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