• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.141-153
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• 2024

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.1-16
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• 2024

The purpose of this study is to develop a machine learning-based AI convergence class model and class design principles that can foster data literacy in high school students, and to develop detailed guidelines accordingly. We developed a machine learning-based teaching model, design principles, and detailed guidelines through research on prior literature, and applied them to 15 students at a specialized high school in Seoul. As a result of the study, students' data literacy improved statistically significantly (p<.001), so we confirmed that the model of this study has a positive effect on improving learners' data literacy, and it is expected that it will lead to related research in the future.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.121-130
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• 2023

In the school field, AI convergence education is recommended, which utilizes AI in education to change the paradigm of society. This study was conducted to define the terms of AI and AI convergence education to minimize the confusion of terms and to analyze the educational needs of teachers from the perspective of conducting AI convergence education. To achieve the purpose, 19 experts' opinions were collected, and a self-administered questionnaire was administered to 125 secondary school teachers enrolled in the AI convergence major at the Graduate School of Education. As a result of the analysis, the experts defined AI convergence education as a methodology for problem solving, not AI-based or utilization education. In the analysis of teachers' educational needs, "AI and big data" was ranked first, followed by "AI convergence education methodology" and "learning practice using AI". The significance of this study is that it defined the terminology by collecting the opinions of experts amidst the confusion of various terms related to AI, and presented the educational direction of AI convergence education for in-service teachers.

• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.88-95
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• 2021

Korea will face difficult social problems including population decline and climate change in the future. Artificial intelligence (AI)-powered ICT convergence services are expected to greatly help in overcoming these social challenges. Accordingly, we have derived key promising services (AI+x) in terms of individuals, industries, and countries and identified expectations and threats perceived by the general public. These findings provide policies and research directions for promising AI-based ICT convergence services for social goods.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.

• Smart Media Journal
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• v.11 no.2
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• pp.39-52
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• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.59-65
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• 2021

In this paper, we propose the AI certification standardization activities for systematic research and planning for the standardization of trustworthy artificial intelligence (AI). The activities will be in two-fold. In the stage 1, we investigate the scope and possibility of standardization through AI reliability technology research targeting international standards organizations. And we establish the AI reliability technology standard and AI reliability verification for the feasibility of the AI reliability technology/certification standards. In the stage 2, based on the standard technical specifications established in the previous stage, we establish AI reliability certification program for verification of products, systems and services. Along with the establishment of the AI reliability certification system, a global InterOp (Interoperability test) event, an AI reliability certification international standard meetings and seminars are to be held for the spread of AI reliability certification. Finally, TAIPP (Trustworthy AI Partnership Project) will be established through the participation of relevant standards organizations and industries to overall maintain and develop standards and certification programs to ensure the governance of AI reliability certification standards.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.182-184
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• 2022

As artificial intelligence (AI) is emphasized in elementary and secondary school education, interest in AI-applied class activities is increasing. Since AI is taught across various subjects in schools, teachers must plan lessons based on the principles of convergence education. In this paper, the concept of convergence education and matters to be considered for productive class activities were reviewed. Then, considerations for designing AI classes in schools are presented in the following aspects: characteristics of AI education in schools; educational goals for each school level in the general guidelines of the national curriculum; resources to be referenced when composing class content; perspectives on AI-applied software; and anticipated instructional procedures. As a suggestion, the following is presented. First, it is necessary to derive competencies that can be cultivated by AI education in school. Second, it is necessary to specify the design elements and procedures of AI classes based on the subject characteristics.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.483-490
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• 2021

In the era of the fourth industrial revolution, the importance of artificial intelligence(AI) is growing day by day, and there is no disagreement that AI education will bring great innovation in the future. Various attempts are being made to educate the topic of AI, but students who have no experience in AI education recognize AI only as a difficult target. Therefore, in this study, we analyze the changes in students' perception of AI by teaching them using AI. AI convergence education were conducted for 6th grade elementary school students, and pre and post tests were conducted in the form of AI awareness survey questionnaires which included questions such as interest in AI, changes brought by AI, and AI education. As a result, we confirm significant results that suggest the level of awareness of AI has improved through AI education in all factors. AI convergence education requires various AI convergence education programs as a form of education for social needs and future students, and hopefully a design based on this will help realize student centered education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.428-434
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• 2020

Recently, due to the development of ICT technology, changes to the convergence service platform of information systems are accelerating. Convergence services expanded to cyber systems with 5G communication, IoT, AI, and cloud are being reflected in the real world. However, the field of cybersecurity audit for responding to cyber attacks and security threats and strengthening security technology is insufficient. In this paper, we analyze the international standard analysis of information security management system, security audit analysis and security of related systems according to the expansion of 5G communication, IoT, AI, Cloud based information system security. In addition, we design and study cybersecurity audit checklists and contents for expanding security according to cyber attack and security threat of information system. This study will be used as the basic data for audit methods and audit contents for coping with cyber attacks and security threats by expanding convergence services of 5G, IoT, AI, and Cloud based systems.