• Journal of Digital Convergence
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• v.15 no.5
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• pp.37-48
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• 2017

Recently, the importance of software education is growing because computational thinking of software education is recognized as a key means of future economic development. Also human resources who will lead the 4th industrial revolution need convergence and creativity, computational thinking based on critical thinking, communication, and collaborative learning is known to be effective in creativity education. Software education is also a time needed to reflect social issues such as collaboration with developers sharing interests and open source development methods. Github is a leading social coding site that facilitates collaborative work among developers and supports community activities in open software development. In this study, we apply operational cases of basic learning of social coding sites, learning for storage server with sources and outputs of lectures, and open collaborative learning by using Github. And we propose educational model consisted of four stages: Introduction to Github, Using Repository, Applying Social Coding, Making personal portfolio and Assessment. The proposal of this paper is very effective for software education by attracting interest and leading to pride in the student.

• Journal of The Korean Association of Information Education
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• v.22 no.5
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• pp.519-533
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• 2018

This study aims to classify the types of instructional expertise development activities of teachers who teach subjects related to software education in primary schools. To this end, the study analyzes their participation in expertise development activities over the recent three years, outcomes from these activities, and forms and characteristics of expertise development activities. In the questionnaire survey conducted for this study, 276 primary school teachers participated. According to the survey, the same largest proportion of them participated in collective job training (96%) and distant job training (96%), followed by consulting, instruction supervision, mentoring, and peer observation (82%), lectures, workshops, and seminars held by related government ministries and the provincial and municipal offices of education (69%), and teachers' study communities (66%). Among informal activities, reading accounted for the highest portion of the activities (88%), followed by the use of information on Websites including YouTude and GitHub (80%), and teachers' expertise development networks (76%). The reasons for their participation in the activities were mostly to improve their instructional expertise (80%). Their participation in the activities had an impact on usefulness to enhance instructional expertise, improvement of job competencies, application to current jobs, sense of instructional efficacy, and positive effect. These results of the study are expected to provide a foundation for preparing continued expertise development plans that can promote the educational value of primary school teachers' instructional expertise development activities for teaching subjects related to software education.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.11-19
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• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.43-65
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• 2021

With the advancement of information and communications technology, a means to recruit IT professional has fundamentally changed. Nowadays recruiters search for candidate information from the Web as well as traditional information sources such as résumés or interviews. Particularly, open-source software development (OSSD) platforms have become an opportunity for developers to demonstrate their IT capabilities, making it a way for recruiters to find the right candidates, whom they need. Therefore, this study aims to investigate the impact developers' profiles in an OSSD platform on their finding a job. This study examined four antecedents of developer information that can accelerate their job search: job-seeking status, personal-information posting, learning activities and knowledge contribution activities. For the empirical analysis, we developed a Web crawler and gathered a dataset on 4,005 developers from GitHub, which is a well-known OSSD platform. Proportional hazards regression was used for data analysis because shorter job-seeking period implies more successful result of job change. Our results indicate that developers, who explicitly posted their job-seeking status, had shorter job-seeking periods than those who did not. The other antecedents (i.e., personal-information posting, learning, and knowledge contribution activities) also contributed in reducing the job-seeking period. These findings imply values of OSSD platforms for recruiters to find proper candidates and for developers to successfully find a job.