• Korean Journal of General Education
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• v.4 no.1
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• pp.237-254
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• 2010

For years, poor research and working conditions in the field of science and engineering in Korea led to the migration of gifted students to seek a better academic environment. The primary reason for such a phenomenon is the lack of a coherent education system for gifted students. With the support from the Ministry of Education, Science and Technology and the Korea Foundation for the Advancement of Science & Creativity, Hanyang University launched an exploring project to introduce an Honors Program, aiming to provide specialized and systematic learning opportunities as well as supporting greater academic achievements for gifted students at university-level. Students admitted to this program were selected not by conventional standards but by competency-based selection process, assessed through an in-depth interview. The specific goal of this program is to prepare gifted and talented students not only for an academic pioneer with the highest caliber in the field of science, but also for a global leader equipped with a creative view as well as integrity and a convergent mind. Distinctive features of this program include emphasis on fundamental science and consilience, problem solving skills, first-hand education, interpersonal skills, and global communication skills as well as individualization of the learning experience, among many others. This paper provides a short glimpse of the focus and methodology Honors Program in Hanyang University offers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.383-384
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• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• Korean small business review
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• v.39 no.3
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• pp.57-76
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• 2017

While the unemployment rate is rising rapidly due to recent economic recession at home and abroad, university students' reluctance to apply for jobs in Small and Medium Enterprises (SME's) causes instability in manpower supply and demand and social unrest. To provide insights for solving the problem, this study explores how beliefs and attitudes of university students influence their intention to apply for jobs in SME's using Theory of Planned Behavior proposed by Icek Ajzen. This study followed the 2-stage survey methodology suggested by Ajzen. In the first stage of pilot study, a small sample of university students was used to illicit readily accessible behavioral outcomes, normative referents, and control factors. In the second stage of main study, the standard questionnaire was designed and administered and data were collected and analysed using the PLS Structural Equation Modeling (SEM) technique. PLS-SEM was used instead of Covariance Based (CB)- SEM considering the exploratory nature of this study. In overall, the results showed that TPB is very effective in explaining and predicting the university student's intention to apply for jobs in SEM's. Gender turned out to be a significant moderator variable in the relations between intention and its influence factors. Student's scholastic performance showed a negative correlation with intention. More research efforts need to be exerted to better understand university student's job seeking behavior.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.505-512
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• 2022

The purpose of this study is to synthesize effects of the living lab-based education through meta-analysis. Seven primary studies reporting the effect of living lab-based education were carefully selected for data analysis. Research questions are as follows. First, what is the overall effect size of the living lab-based education? The overall effect size refers to the effect on the cognitive and affective domains. Second, what is the effect size of the living lab-based education according to categorical variables? Categorical variables are outcome characteristics, study characteristics, and design characteristics. Results are summarized as follows. First, the overall effect size of living lab-based education was 0.347. Second, the effect size according to the cognitive domain was 1.244 for information process, 0.593 for communication, 0.261 for problem solving, and 0.26 for creativity. Third, the effect size according to subject area was shown in the order of electrical and electronic engineering 1.146, technology and home economics 0.489, artificial intelligence 0.379, and practical arts 0.168. Fourth, the effect size according to school level was 1.058 for high school, 0.312 for middle school, and 0.217 for elementary school. Fifth, the effect size by grade level was 0.295 when two or more grades were integrated and 0.294 for a single grade.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.583-594
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• 2023

This study aimed to develop an e-PBL program for high school students using COVID-19 related data and to investigate the impact of the developed program on students' science core competencies. For this, the e-PBL program was developed in consideration of the characteristics of learners and e-PBL, and a science core competency analysis framework. The program was applied to 26 general high school life science club students. Test for science department core competency was conducted before and after class by questionnaires and their conversation data during class was collected and analyzed by the framework. As a result of the study, the developed program was effective in improving five science core competencies. In the results of the analysis of the science core competency questionnaire, there were significant effects on scientific thinking ability, scientific inquiry ability and scientific problem solving ability. Unlike in the results of the questionnaires, the five sciences department core competencies appeared evenly in student discourse analysis. Among them, scientific communication ability and scientific participation and lifelong learning ability did not show significant results in the questionnaire, but in the discourse analysis results. Both abilities were the most evenly displayed competencies through the program stages. Through the study, we expect that the program is possibles to be useful instructional material to make high school students increase science core competencies.

• Korean Journal of Culture and Social Issue
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• v.11 no.2
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• pp.1-29
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• 2005

This research examined the effect of social anxiety on psychological adaptation. Higher the social anxiety, higher in neurotism & worry but lower in Psychological Well-Being and Satisfaction with Life. Among the sub-factors of social anxiety, negative adaptation was significantly predicted by personal anxiety. However positive adaption were predicted by personal anxiety, fairness anxiety and future anxiety. Among the sub-dimensions of social anxiety, negative and positive adaptation were significantly predicted only by anticipatory anxiety. And there were significant positive correlations between social anxiety and aggressive/give-up response. Particularly, personal anxiety was the predictor of aggressive response, but safe anxiety and political anxiety were the predictors of give-up response. The dimension predicted the aggressive/give-up response was anticipatory anxiety dimension. Finally, respondents used problem solving stress coping strategy most. But the respondents whose social anxiety level especially safe anxiety and political anxiety were high used wishful thinking strategy. Moreover higher the reactive anxiety level, more frequently used the avoidance coping strategy.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.291-298
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• 2023

In this paper, we study whether the programming questions of the Informatics·Computer recruitment tests were suitable for selecting teachers with required programming skills. The average points of the programming questions constituted 38%(20.8 points) of the total scores for the entire curriculum based on the results from analyzing the previous questions in the past 5 years. Moreover, the distribution of points for each evaluation criteria within programming and data structure, two exam subjects which have a high proportion of programming questions, demonstrated a large deviation ranging from 0% to 47% and 0% to 53% respectively. In this study, a questionnaire survey was conducted on 31 teachers to examine if the previous programming questions were suitable for measuring teachers' competency in programming abilities required in the actual teaching experience. Computational thinking ability was ranked the highest at 58% in response to the area that needs to be evaluated in the recruitment test. In response to the relevance of previous questions, problem solving ability was ranked the highest at 2.84 on a 5-point scale, but the overall appropriateness was deemed low. C language and Python were regarded as the computer languages suitable to be tested for programming questions with each ranked 55% and 45%. The finding confirms that teachers preferred Python and the incumbent C language to others. Based on the results of the questionnaire, we recommend changes in the programming questions to improve the selection criteria.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.517-544
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• 2023

This study presents the process and outcomes of developing mathematical-informatics linkage·convergence class materials, based on previous research findings that indicate a lack of such materials in high schools despite the increasing need for development of interdisciplinary linkage·convergence class materials In particular, this research provides insights into the discussions of six teachers who participated in the same professional learning community program, aiming to create materials that are suitable for linkage·convergence class materials and highly practical for classroom implementation. Following the material development process, a theme-based design model was applied to create the materials. In alignment with prior research and consensus among teacher learning community members, mathematics and informatics teachers developed instructional materials that can be utilized together during a 100-minute block lesson. The developed materials utilize societal issue contexts to establish links between the two subjects, enabling students to engage in problem-solving through mathematical modeling and coding. To increase the validity and practicality of the developed resources during their field application, CVR verification was conducted involving field teachers. Incorporating the results of the CVR verification, the finalized instructional materials were presented in the form of a teaching guide. Furthermore, we aimed to provide insights into the trial-and-error experiences and deliberations of the developers throughout the material development process, with the intention of offering valuable information that can serve as a foundation for conducting related research by field researchers. These research findings hold value as empirical evidence that can explore the applicability of teaching material development models in fields. The accumulation of such materials is expected to facilitate a cyclical relationship between theoretical teaching models and practical classroom applications.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.45-61
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• 2023

The start-up rate is increasing due to the government's start-up support policy, but it is true that the continuous survival rate and growth rate of companies are lower than that of the start-up rate. As part of increasing the survival and growth rate of startups, the importance of start-up mentoring has been highlighted, and companies selected for the Government's startup support project are increasingly having mentoring opportunities for corporate growth. In order to determine the relationship between start-up mentoring and entrepreneurial alertness as a way to generate management performance, this study examined how start-up mentoring affects entrepreneurial alertness and management performance. In addition, the government's support project was divided into companies with less than three years of start-up and companies with more than three years of experience, which are the criteria for early and leap companies, and analyzed whether each group has a moderating effect. As a result of the analysis, it was found that the mentoring problem-solving function had a significant effect on the ability to evaluate entrepreneurial alertness, and the motivation function of mentoring had a significant effect on all factors of entrepreneurial alertness. In addition, although mentoring functions did not have a moderating effect on entrepreneurial alertness depending on the work history between companies less than 3 years and companies for more than 3 years, there was a difference in factors affecting entrepreneurial alertness between groups with low and high work history. The implications of this study can contribute to the advancement of start-up mentoring programs by studying the impact of mentoring factors on entrepreneurial alertness when providing mentoring to start-up companies selected for the government's start-up support project.

• Information Systems Review
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• v.24 no.4
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• pp.97-118
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• 2022

As generative adversarial network (GAN) based oversampling techniques have achieved impressive results in class imbalance of unstructured dataset such as image, many studies have begun to apply it to solving the problem of imbalance in structured dataset. However, these studies have failed to reflect the characteristics of structured data due to changing the data structure into an unstructured data format. In order to overcome the limitation, this study adapted CycleGAN to reflect the characteristics of structured data, and proposed hybridization of synthetic minority oversampling technique (SMOTE) and the adapted CycleGAN. In particular, this study tried to overcome the limitations of existing studies by using a one-dimensional convolutional neural network unlike previous studies that used two-dimensional convolutional neural network. Oversampling based on the method proposed have been experimented using various datasets and compared the performance of the method with existing oversampling methods such as SMOTE and adaptive synthetic sampling (ADASYN). The results indicated the proposed hybrid oversampling method showed superior performance compared to the existing methods when data have more dimensions or higher degree of imbalance. This study implied that the classification performance of oversampling structured data can be improved using the proposed hybrid oversampling method that considers the characteristic of structured data.