• The Journal of Korean Association of Computer Education
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• v.21 no.1
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• pp.43-50
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• 2018

The 2015 Revised National Curriculum emphasizes software education to develop creative and convergent talents in preparation of the Fourth Industrial Revolution. Accordingly, it is necessary to develop competency-based training programs for informatics teachers in a rapidly changing educational environment. In this background, this study selects a framework to analyze the content of in-service training for informatics teachers through review of previous studies. By analyzing the current training programs to strengthen competencies required for informatics teachers in secondary schools, the study aims to develop implications for future in-service training programs. To this end, the study conducted a questionnaire survey of experts who participated in the development of in-service training textbooks and consulted them, then analyzed the elements of competency-based training program content and the relative importance of each competency element using the analytical hierarchy process (AHP). According to the results of the analysis, the content was relatively concentrated on the competency of "Understanding and Reconstructing the National Curriculum" required for general and informatics teachers as well, which accounted for 47% of all, or 7 hours out of the total 15 hours. In contrast, the content structure lacked the competency of highly relative importance by competency element "Establishing and Using Teaching-Learning Strategies for Informatics," which took up the highest portion of 27%. These findings will be used as basic data for understanding and reflecting the areas that fall short of the development of in-service training programs for informatics teachers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.537-544
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• 2016

National Competency Standards (NCS) need to be introduced to train newly hired staff and to gradually improve employees' work performance in the information security industry. In particular, the introduction of a new NCS curriculum for new hires is important in order to retain and efficiently manage professionals in the information security field. However, the legacy NCS is not clearly designed for the information security field. So a formal curriculum has been suggested for institutions training the information security workforce. Therefore, this study establishes a competency unit based on the types of personnel, their duties, and required knowledge. To select the competency unit, this study reviewed prior research to understand the required skills and work knowledge, and reviewed recruitment-based NCS that public agencies and public and private companies have carried out, including them in the study. The selected competency unit was classified into a required competency unit and an elective competency unit based on the importance of the duties and the demands of training. Through a verification process for the new, licensed career path model in the NCS information and communications field, this study suggests updated NCS competency units and required courses to provide an appropriate NCS curriculum for newly hired employees in the information security industry.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.201-207
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• 2021

As artificial intelligence gradually expands into jobs, iIt is necessary to nurture talents with AI literacy capabilities required for non-majors. Therefore, in this study, based on the necessity and current status of AI education, AI literacy competency improvement education was conducted for non-majors so that AI learning could be sustainable in relation to future majors. For non-majors at University D, problem-solving solutions through project-based data analysis and visualization were applied over 15 weeks, and the AI ability improvement and effectiveness of learners before and after education were analyzed and verified. As a result, it was possible to confirm a statistically significant level of positive change in the learners' data analysis and utilization ability, AI literacy ability, and AI self-efficacy. In particular, it not only improved the learners' ability to directly utilize public data to analyze and visualize it, but also improved their self-efficacy to solve problems by linking this with the use of AI.

• Journal of Science Education
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• v.44 no.2
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• pp.183-196
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• 2020

This study explores the effects of STEAM program using Arduino on preservice science teachers toward their STEAM core competencies. The STEAM program using Arduino consists of four stages: presentation of situation, creative design, emotional touch, and evaluation. The preservice science teachers learned the theoretical backgrounds of STEAM and Arduino. Then, they were given the chance to think about an environmental issue, which is fine dust. The preservice teachers designed an air cleaner and a fine dust measuring instrument using Arduino. The preservice science teachers also produced the air cleaner and the measuring instrument using Arduino. They measured the level of fine dust in the classroom before and after the use of the air cleaner. That is, the preservice teachers experienced each stage of STEAM: seriousness of fine dust, design and production of the measuring instrument of fine dust and air cleaner, and evaluation of the effectiveness of air cleaner. Further, they reflected on their experiences of STEAM program using Arduino. The results indicate that these preservice science teachers statistically improved communication competency, problem-solving competency, gathering information competency, logical analytical thinking competency, and creativity competency. However, there were no statistical improvements on teamwork competency and self-development competency. This study suggests that experiencing STEAM program using Arduino is valuable for the preservice science teachers to develop STEAM core competencies and further implement STEAM program their science classes in the future.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.91-98
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• 2015

In this paper, we introduce PMS's main function and main effect which implemented medium and large scale software development project site, and we propose importance and improvement nacessity of PMS implementation. PMS's main functions are developed based on best practices which CMMI model and PMBOK. Also, each PMS has specialized unique function according to it's target industry area or related I.T solutions which has infra dependency. The effectiveness of PMS implementation on project site is seperated two types, one is qualitative effect, the other quantitative effect. Representative qualitative effects are improvement of enterprise's image and competency. Also representative quantitative effect is reduction of project management cost as a financial effect. As far as project size is increase, PMS's needs and necessariness will be increase, so we need to improve PMS;s function according to project management's global trend and software customer's requisition.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.101-102
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• 2018

본 논문에서는 교과개정 개편으로 저학년부터 코딩교육의 의무화가 됨에 따라 현시점에서 코딩교육의 대표적인 교육사이트에 대한 현황 및 장단점을 살펴보고, 교육을 받은 S/W 인재들이 대학교에 진학하여 배우는 S/W 교육에 대해 살펴보고자 했다. 현재 미래 창조과학부에서 운영하는 S/W 중심대학에 관하여 적절한 운영 방향에 따라 각 대학교가 운영되고 있는지 조사해보고 이에 따른 개선 방향을 제시하고자 하고 대학교별로 K-ICT(Korea-Information&Communication Techonology) 전략에 부합하는 목표성을 가졌는지 그룹핑해서 나열하고 이에 따른 문제점을 분석하여 S/W 교육 추진 방향과 정책설계를 통한 미래 발전 방안을 K-ICT 중심의 목표와 S/W 중심학교가 NCS(National Competency Standards)에 부합하는 시스템 개발을 위한 연구의 필요성을 제시한다.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.451-459
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• 2019

Various policies have been implemented for human resources development in preparation for future society. Among the policies, STEAM education, SMART education and SW education are representative examples. In order for these policies to be implemented effectively in the school setting, teachers' positive perception and teaching competency are required. In consideration of the importance of pre-service teacher education, this study analyzed the current status of elementary pre-service teachers' perception and teaching readiness on STEAM education, SMART education and SW education, and sought implications that can be reflected in pre-service teacher education. The results of the study showed that the pre-service teachers' perception on the necessity of each policy was very high, and the understanding level of each policy was relatively high. Compared with this, it was found that pre-service teachers lacked training experience related to each policy, and the level of readiness for teaching was very low. As the most important task to be solved, many pre-service teachers selected the implementation of teacher education and seminars, and the distribution of instructional programs and materials. As the result of analyzing the difference according to pre-service teachers' individual characteristics, differences were found according to the level of their ICT utilization ability. Based on the results of this study, implications to be reflected in pre-service teacher training processes were suggested.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.225-238
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• 2022

Although the importance of literacy in Artificial Intelligence (AI) education is increasing, there is a lack of testing tools for measuring such competency. To address this gap, this study developed a testing tool that measures AI literacy among middle school students. This goal was achieved through the establishment of an expert group that was enlisted to determine the relevant factors and items covered by the proposed tool. To verify the reliability and validity of the developed tool, a field review, exploratory factor analysis, and confirmatory factor analysis were conducted. These procedures resulted in a testing tool comprising six domains that encompass 30 items. The domains are the social impact of AI (eight items), the understanding of AI (six items), AI execution plans (five items), problem solving with AI (five items), data literacy (four items), and AI ethics (two questions). The items are to be rated using a five-point Likert scale. The internal consistency of the tool was .970 (total), while that of the domains ranged from .861 to .939. This study can serve as reference for developing the analysis of AI literacy, teaching and learning, and evaluation in AI education.