• Journal of the Korean Institute of Navigation
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• v.21 no.3
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• pp.19-38
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• 1997

It is one of the important study for improving education quality to investigate School climate, Campus Life and Academic Achievement in University. This study focuses on the of success / failure attribution in academic achievement and its internal-external attribution of Maritime college students. The main purpose of this study was investigate the relationship between the perception of college climate and attribution of success and failure about college life and cadet's academic performance. The subjects were 490 cadets of freshman, sophomore and junior of Korea Maritime University. The data was analysed by Pearson's correlation, one-way and simple factorial ANOV A, $x^2$, and t-test by using SPSSWIN Ver. 7.5 programme. The major results of this study were as follows : 1. Social relationship orientation was higher than the others on the perception of college climate, while the relationship between professor and collegian was lower. 2. The most collegian recognized on the attribution of failure about the college life and the relationship between professor and collegian. But most collegian recognized on the attribution of sucess about collegian's relationship. 3. The perception of college climate and attribution of success / failure was not influenced on the student's academic performance and academic adaptability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1608-1614
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• 2022

As competition between universities intensifies due to the recent decrease in the number of students, it is recognized as an essential task of universities to predict students who are underperforming at an early stage and to make various efforts to prevent dropouts. For this, a high-performance model that accurately predicts student performance is essential. This paper proposes a method to improve prediction performance by removing or amplifying abnormal data in a classification prediction model for identifying underperforming students. Existing anomaly data processing methods have mainly focused on deleting or ignoring data, but this paper presents a criterion to distinguish noise from change indicators, and contributes to improving the performance of predictive models by deleting or amplifying data. In an experiment using open learning performance data for verification of the proposed method, we found a number of cases in which the proposed method can improve classification performance compared to the existing method.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.1
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• pp.86-92
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• 2012

For the successful operation of IPP program which is a unique Korean Co-op education program designed and implemented by Korea Tech, it is very crucial to have both a reasonable performance evaluation system and a systematic feedback and upgrading system for the program. In this paper, we will provide the logic model for long-term performance evaluation of Korea Tech's IPP program. Since the critical success factors(CSF) and Key Performance Index(KPI) are very important for the IPP program implementation, they are also provided and discussed in detail. In addition, we will discuss and analyze about the student and the industry survey results for IPP program's sucess factors.