• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.4057-4071
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• 2018

The software centered world following the fourth industrial revolution is rapidly approaching us. Countries around the world attach importance to software's ability as one of the key elements for training future human resources. In order to train software centered human resources, each university has designated Software Education as an essential curriculum for not only major but also non-majors. In the past Software Education was an education for a major, but recent Software Education was changed to the essential education that is necessary for all living in the software centered world. In the past the curriculum was focused on software development and implementation-oriented education, but recent curriculum emphasizes sequential arranging and thinking of problem solving. In order to reflect trends in recent Software Education in detail, we integrate Software Education with major concept of Computational Thinking. In this paper, we analyzed the effect of the main concept of Computational Thinking on Software Education for non-majored learners who received Software Education based on Computational Thinking (here refers to learners who major in humanities, social sciences and arts). In addition, research models of satisfaction, self-efficacy, and occupational change was established as the elements of Software Education, and it was found that there was a relation between Computational Thinking and Software Education.

• Proceedings of the ESK Conference
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• 1992.10a
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• pp.84-89
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• 1992

This study is to develop a cognitive paradigm including a new model of common cause human behavior error domain and to analyze their causal factors and their properties of common cause huamn error characteristics in software engineering.l A laboratory study was performed to analyze the common causes of human behavior domain error in software develoment and to indentify software design factors contributing to the common cause effects in common cause failure redundancy. The results and analytical paradigm developed in this resuarch can be applied to reliability improvement and cost reduction in software development for many applications. Results are also expected to provide training guideliness for software engineers and for more effective design of ultra-high reliabile software packages.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.1-10
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• 2019

In this study, we analyzed the differences of SW education teaching efficacy(SE-TE) according to variables such as gender, region, training experience, and attitude toward SW education. As a result, there was no difference according to the region, but there was statistically significant difference in the other variables. The correlation analysis and the regression analysis showed that the training experience and the attitude toward the SW education had the most correlation and explanatory power to the SE-TE. These results suggest that the training should be designed in order to enhance the teachers' SE-TE, to increase the opportunities of training, to provide continuous training, to operate the training hours efficiently, and to improve the teachers' personal SW education teaching efficacy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.1021-1031
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• 2020

This study aims to invest in empirical relationships in a model that becomes the process of Team-Performance due to participation in practical training through causality between Training Effectiveness variables, soft-skill competence, Employee-Creativity, and team performance. This study uses a quantitative approach. The analytical tool used is structural equation modeling (SEM) using AMOS version 23 software. Accidental sampling technique is used to collect the sample. As many as 202 respondents filled up a survey questionnaire with complete and valid answers. This study's results significantly contribute to fill the gap of inadequate empirical evidence that can answer critical questions about the missing link between training and employee-performance, more specifically between training-effectiveness and team-performance. The results showed that practical training would encourage employees' soft-skill competence, improve Employee-Creativity, and improve Team-Performance. Furthermore, training-effectiveness also plays a significant role in enhancing employee-creativity and helping in optimal team-performance. This study also found that the relationship between employee-creativity and team-performance did not show positive and significant results; therefore, empirically, it did not support the hypothesis built in this study. Practical training targeted towards increasing soft-skills and creativity is a fundamental reason which not only aims to contribute toward organizational performance but also provides personal feedback for self-development.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.169-175
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• 2017

In this paper, we propose the elementary school teacher's training direction for effective SW education. In an effort to better understand the efficient SW training contents and methods for teachers, 200 of elementary teachers had been selected from different places in South Korea. The results showed that 1)it should be operated by focusing on the training of female teachers, especially, strengthening the contents of SW ethics. 2)It will need to actively operate the teacher training program to foster the necessary computational thinking and programing for elementary school teacher who work in big cities. 3)It need to create a training program for expanding the SW studying groups. 4)In order to improve the effectiveness of training courses in the development of in-service training programs, the SW ethics contents need to be coordinated with the link the computational thinking and programing. These results are expected to provide the efficient methods to design the future SW training programs.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.449-457
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• 2021

Ministry of education recently announced to implement AI curriculum in elementary, middle school and highschool from 2025 which will include programing, basic AI principal and AI Ethics, and the media is releasing articles that have reservations on it. This study is focused on analyzing the perspective of elementary teachers - who are going to be in charge of AI education - on the implementation of AI education in elementary schools and the teachers are divided into two groups of 'software-experienced' and 'software-inexperienced' in relation to software training background. The results showed that 100% of the 'software-experienced' teachers agreed on implementing AI education and 80% of 'software-inexperienced' teachers also showed positive perspective on it. Among the reasons that 20% of 'software-inexperienced' teachers had negative perspective on AI education, it was highly rated that existing home economics subject covers fulfilling amount of software education. Both 'software-experienced' and 'software-inexperienced' teachers chose grade 5 and 6 as the most appropriate age for software education and considered one class per a week as the most appropriate amount of AI class. In terms of the subject format, 75% of the 'software-experienced' teachers chose the idea that software education has to be an independent school subject which will include AI education. Also, 54% of the 'software-inexperienced' teachers chose the ideas either AI education should be an independent subject or software education should be an independent subject which will include AI education. The preference of the content of AI education appeared in order of basic AI programing, principles of AI and AI Ethics.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.239-246
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• 2019

In this paper, we propose an effective software education donation model for the social care class. The types of software education for elementary, middle, and high school for the social care class are in the order of after school classes, club activities, creative experiences, and regular classes. In elementary school students, it is effective to precede visual programming education based on block coding and to conduct curriculum convergence with SW and HW at the beginning, and high school students are carrying out text programming education like Python. Software education for social care class The contribution activity model can be classified into five types such as geographically difficult area, multicultural family areas, orphanage, reformatory, and basic livelihood security recipient. In addition, the survey results show that the students' interest in software education and their satisfaction are all very high at 96%. Effective software education for the social care class In the donation model, the lecturers consist of responsible professors, lecturers, and assistant instructors. Software training for the social care class is effective on a year-by-year basis, so that students can feel authenticity and trust. Software education contents focus on visual programming and physical computing education in elementary or middle school, and text programming and physical computing education in high school. It is necessary to construct a software education donor matching system that helps efficient management of software education donations by efficiently matching schools (consumers: elementary, middle, high school) and software education donors(suppliers).

• Journal of the Ergonomics Society of Korea
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• v.11 no.2
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• pp.35-45
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• 1992

This study is to define a congitive paradigm including a new model of common cause human behavior error domain and to analyze their causal factors and their properties of common cause human error characteristics in software engineering. A laboratory study was performed to analyze the common causes of human behavior domain error in software development and to identify software design factors contributing to the common cause effects in common cause failure redundancy. The results and analytical paradigm developed in this research can be applied to reliabbility improvement and cost reduction in software development for many applications. Results are also expected to provide training guidelines for software engineers and for more effective design of ultra-high reliable software packages.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2253-2272
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• 2018

We propose a deep learning method for multi-focus image fusion. Unlike most existing pixel-level fusion methods, either in spatial domain or in transform domain, our method directly learns an end-to-end fully convolutional two-stream network. The framework maps a pair of different focus images to a clean version, with a chain of convolutional layers, fusion layer and deconvolutional layers. Our deep fusion model has advantages of efficiency and robustness, yet demonstrates state-of-art fusion quality. We explore different parameter settings to achieve trade-offs between performance and speed. Moreover, the experiment results on our training dataset show that our network can achieve good performance with subjective visual perception and objective assessment metrics.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.