• Journal of Engineering Education Research
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• v.24 no.2
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• pp.29-40
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• 2021

This research aims to examine the relationship between major satisfaction and psychological well-being of female engineering students. To achieve this goal, first, differences in major satisfaction and psychological well-being among engineering students were examined. Second, differences in major satisfaction and psychological well-being among female undergraduate students were investigated. In addition, the effects of psychological well-being, as perceived by undergraduate students by gender and major, on major satisfaction were explored. A total of three hundred and forty-nine (349) undergraduate students from two universities in Korea responded to survey based on a two-variables scale. The findings were that, firstly, male engineering students scored higher in two variables including their most sub-factors, and that gender differences in relation satisfaction as well as positive relationship with others, autonomy, and environmental mastery were statistically significant. Secondly, female engineering students scored higher in major satisfaction and several sub-factors of two variables, and that major differences in major satisfaction (total), social perception satisfaction, and autonomy - a sub-factor of psychological well-being - were statistically significant. Thirdly, a positive correlation among major satisfaction and psychological well-being was identified. Finally, psychological well-being could explain about 19% of major satisfaction. The practical implications of these findings are discussed herein, with attention on education for promotion of major satisfaction.

• Journal of Engineering Education Research
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• v.26 no.3
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• pp.20-34
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• 2023

This research aims to explore the factors affecting engineering students' major persistence and career decision. To achieve this goal, the experiences and perceptions of engineering students and other stakeholders regarding the factors influencing engineering students' major persistence and career decision were analyzed through online focus group interviews (FGI). The analysis of the interviews resulted in the identification of seven categories, which include meeting with older alumni, team project experiences, and internship experiences as factors influencing major persistence. Additionally, engineering interest, engineering self-efficacy, employment rates, economic factors, and limitations in women engineers' career development were identified as factors affecting career decision. Based on these findings, it is expected that engineering education will develop plans that focus on supporting the major persistence and career development of engineering students, thereby contributing to the future direction of engineering education.

• Journal of Engineering Education Research
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• v.27 no.1
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• pp.41-49
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• 2024

The purpose of this study is to explore ways to improve major satisfaction that can be applied by universities through the analysis of factors influencing major satisfaction of engineering college students. To this end, Korea-National Survey of Student Engagement(K-NSSE) data involving 814 students from T University were used, and logistic regression analysis and t-test were applied. The main results obtained through this are as follows. First, engineering college students' major satisfaction factors include major-career relevance, college immersion, and positive academic sentiment. Second, depending on the grade, it was confirmed that the factor of major-career relevance in the lower grades, and the factors of meaningful learning experience and college immersion in addition to major-career relevance in the upper grades had a significant influence. Third, the higher the meaningful learning experience, positive academic sentiment, and college immersion, including the major-career relevance, the higher the major satisfaction was found in the middle-class group with a score of BO or higher. This study is meaningful in that it revealed differences in influence by individual characteristics as well as major satisfaction influencing factors that can be practiced in universities such as learning experiences.

• Journal of Engineering Education Research
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• v.19 no.6
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• pp.10-19
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• 2016

This study was conducted to explore the major adjustment factors in undergraduates by investigating the characteristics of group which doesn't correspond to Holland's congruence assumption. For this study, 313 sophomore year undergraduates in engineering were surveyed. The results of this study showed as follows. First, the group which doesn't correspond to Holland's congruence assumption represented 16.6% of all. Second, there were significant differences of basic psychological needs among four groups by interest-major congruence and major adjustment. These findings imply that major selection in congruence with interest is not critical and we should also consider basic psychological needs(autonomy, competence, relatedness) for engineering major adjustment.

• Journal of Engineering Education Research
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• v.26 no.4
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• pp.3-10
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• 2023

The underrepresentation of women in engineering has received considerable attention. A series of policies and practices have been developed to promote gender-balanced participation in engineering. This study focuses on gender disparities in reasons for the choice of engineering majors and regret of that choice. The regression results show that compared to their male counterparts, women are found to select an engineering major primarily based on their high school GPA or CSAT scores rather than their aptitudes and interests. Accordingly, women regret their major choice more than men due to mismatched expectations and abilities or unsatisfactory postgraduate labor market outcomes. The findings provide policy insights to improve gender equity in engineering by further enhancing career education in secondary schools.

• Journal of Engineering Education Research
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• v.22 no.4
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• pp.32-42
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• 2019

This study is aim to the effects of job satisfaction on the major satisfaction of science and engineering college students and also analyzed the mediating effects of future outlook of job and major relevance in career choice. To do this, structural equation modeling(SEM) and multi-group SEM were applied to data from 2016 Graduate Occupational Mobility Survey(GOMS). In the results of this study, the major satisfaction, future outlook of job and major relevance were positive effects on job satisfaction and the mediating effects of future outlook of job and major relevance were verified. And results of analysis according to gender difference, the coefficient of woman was smaller than man. Among major satisfaction had a positive effect on job satisfaction, job satisfaction fell for women who value their relevance to the major when choosing a job. Based on such results, universities need to further strengthen their role in helping them enhance their expertise through skills and learning about their majors.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.727-728
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• 2006

This paper is proposed robust control based on the vector controlled induction motor drive with adaptive fuzzy learning control(AFLC). The fuzzy logic principle is first utilized for the control rotor speed. AFLC scheme is then proposed in which the adaptation mechanism is executed using fuzzy logic. Also, this paper is proposed estimation of speed of induction motor using ANN Controller. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. This paper is proposed the analysis results to verify the effectiveness of the new method.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.737-738
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• 2006

This paper is proposed hybrid artificial intelligent controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.729-730
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive fuzzy neural network(A-FNN) controller and artificial neural network(ANN). For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled A-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the A-FNN and ANN controller.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.761-762
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.