• Electronics and Telecommunications Trends
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• v.35 no.7
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• pp.56-66
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• 2020

As the development of artificial intelligence (AI) technology spreads to various industrial sectors, diversity in AI utilization rapidly increases, creating rich user experience. In addition, AI is required to solve various social problems through the use of public data. The spread of AI utilization across all sectors will continue, covering such industrial and public demands. This article examines the domestic and international trends in AI utilization technologies and establishes the direction of research and development (R&D), which is highly consistent with Korea's AI policy. ETRI, which leads AI's national R&D, has used its experience to establish AI R&D implementation strategies as well as technology roadmaps for the utilization of AI to improve individual quality of life, continuous growth in society, industrial innovation, and the solutions to public societal problems. In addition, it has derived tasks and implementation strategies for developing AI utilization technologies in 10 major areas including medical services.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.285-293
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• 2021

With the advent of the 4th Industrial Revolution, AI utilization capabilities are being emphasized in various industries, but AI education design and curriculum research as universal education is currently lacking. This study offers a design for universal AI education to further cultivate its use in universities. For the AI basic education design, a questionnaire was conducted for experts three times, and the reliability of the derived design contents was verified by reflecting the results. As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived were data structure understanding and processing, visualization, word cloud, public data utilization, and machine learning concept understanding and utilization. The educational design content derived through this study is expected to increase the value of competency-centered AI universal education in the future.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.137-148
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• 2024

The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.99-110
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• 2023

In this study, in order to strengthen the AI utilization competency of pre-service secondary science teachers, a project activity in which pre-service teachers directly create an 'AI-based molecular structure customized learning support tool' by using Google's teachable machine was developed and applied. To this end, the program developed for 26 third-grade pre-service teachers enrolled in the Department of Chemistry Education at H University in Chungcheongbuk-do was applied for 14 sessions during extracurricular activities. Then, the perceptions of 'understanding how AI works', 'efficacy of using AI in science classes', and 'plans to utilize AI in science classes' were investigated. As a result of the study, it was found that the program developed in this study was effective in helping pre-service teachers understand the operating principle of AI technology for machine learning at a basic level and learning how to use it. In addition, the program developed in this study was found to be effective in increasing the efficacy of pre-service teachers for the use of AI in science classes. And it was also found that pre-service teachers recognized the aspect of using AI technology as a new teaching·learning strategy and tool that can help students understand science concepts. Accordingly, it was found that the program developed in this study had a positive impact on pre-service teachers' AI utilization competency reinforcement and perception improvement at the basic level. Implications of this were discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2867-2881
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• 2022

This study investigates fashion Artificial Intelligence (AI) curation services to expand sustainable consumption. We analyzed the factors that affect the AI fashion curation service experience of women in their 20s and 30s using their clothes. An online survey was conducted from March 29, 2021, to June 4, 2021, for women of the previously mentioned age groups residing in the metropolitan area. Before answering the questionnaire, they installed the "Style Bot" application on their phone, took five or more photos of their clothes according to the manual provided by the application, stored them in a virtual wardrobe on the application, and then responded to the questionnaire using the AI recommended coordinating function. The effect of the properties of fashion AI curation service application on the use of clothes was investigated. Among the attributes of the fashion AI curation service application, convenience, speed, and usefulness were found to have a positive effect on the use of clothes, and promptness had no effect. Second, regarding the impact of clothing utilization on environmental sustainability, clothing utilization was found to have a positive effect on environmental sustainability. Third, environmental sustainability was found to have a positive effect on satisfaction. Fourth, clothing utilization had a positive effect on satisfaction. Thus, fashion AI curation service would help promote service development so that clothes could be used actively through an in-depth understanding of the properties of these services. Finally, the results of this study would contribute to promoting environmental sustainability.

• Journal of Digital Convergence
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• v.22 no.1
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• pp.15-21
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• 2024

The purpose of this study is to analyze the use of generative AI and the perception of differences between user groups. This study explored the perceptions of different user groups regarding generative AI, aiming to derive implications for enhancing AI utilization capabilities for each group. Upon analysis, it was found that there were no significant differences in perceptions across age groups. However, notable differences were observed between professional backgrounds, particularly in the areas of generative AI application and ethical perspectives. Consequently, this study suggests the need for diversified AI solutions tailored to specific fields of expertise. It underscores the importance of customized education and training programs, as well as specialized education focused on ethical considerations. Additionally, this research contributes academically by proposing varied AI usage strategies for different age and professional groups. It also highlights the role of text mining techniques in developing and improving AI utilization skills.

• The Journal of Industrial Distribution & Business
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• v.12 no.8
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• pp.21-32
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• 2021

Purpose: With the advent of the era of the 4th industrial revolution, called a new technological revolution, the necessity of fostering future talents equipped with AI utilization capabilities is emerging. However, there is a lack of research on AI education design and competency-based education curriculum as education for business major. The purpose of this study is to design AI education to cultivate competency-oriented AI literacy for business major in universities. Research design, data and methodology: For the design of AI basic education in business major, three expert Delphi surveys were conducted, and a demand analysis and specialization strategy were established, and the reliability of the derived design contents was verified by reflecting the results. Results: As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived from this were data structure understanding and processing, visualization, web scraping, web crawling, public data utilization, and concept of machine learning and application. Conclusions: The educational design content derived through this study is expected to help establish the direction of competency-centered AI education in the future and increase the necessity and value of AI education by utilizing it based on the major field.

• The Journal of Economics, Marketing and Management
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• v.11 no.6
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• pp.1-8
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• 2023

Purpose: In the era of the Fourth Industrial Revolution, individuals equipped with fundamental understanding and practical skills in artificial intelligence (AI) are essential. This study aimed to validate the effectiveness of AI education for enhancing AI literacy among business major student. Research design, data and methodology: Data for analyzing the effectiveness of the AI Fundamental Education Program for business major students were collected through surveys conducted at the beginning and end of the semester. Structural equation modeling was employed to perform basic statistical analyses regarding gender, grade, and prior software (SW) education duration. To validate the effectiveness of AI education, seven variables - AI interest, AI perception, data analysis/utilization, AI projects, AI literacy, AI self-efficacy, and AI learning persistence - were defined and derived. Results: All seven operationally defined variables showed statistically significant positive changes. The average differences were observed as follows: 0.47 for AI interest, 0.32 for AI perception, 0.37 for data analysis/utilization, 0.27 for AI projects, 0.25 for AI literacy, 0.39 for AI self-efficacy, and 0.41 for AI learning persistence. Statistically, AI interest exhibited the most substantial average difference. Conclusions: Through this study, the applied AI education was confirmed to enhance learners' overall competencies in AI, proving its utility and effectiveness in AI literacy education for business major students. Future research endeavors should build upon these results, focusing on ongoing studies related to AI education programs tailored to learners from diverse academic backgrounds and conducting continuous efficacy evaluations.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.317-325
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• 2021

In this paper, the degree of reflection of SW·AI elements and CT elements was investigated and analyzed for a total of 44 textbooks of Korean, social, moral, mathematics and science textbooks based on the 2015 revised curriculum. As a result of the analysis, most of the activities of data collection, data analysis, and data presentation, which are ICT elements, were not reflected, and algorithm and programming elements were not reflected among SW·AI content elements, and there were no abstraction, automation, and generalization elements among CT elements. Therefore, in order to effectively implement SW·AI convergence education in elementary school subjects, we will expand ICT utilization activities to SW·AI utilization activities. Training on the understanding of SW·AI convergence education and improvement of teaching and learning methods using SW·AI is needed for teachers. In addition, it is necessary to establish an information curriculum and secure separate class hours for substantial SW·AI education.

• Journal of Christian Education in Korea
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• v.77
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• pp.171-201
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• 2024

Purpose of Research : Since ChatGPT's 2022 release, the educational sector faces mixed reactions to generative AI, sparking innovation but raising concerns about student cognition and communication. While Christian colleges employ AI reflecting their values, secular institutions stress ethical usage. This study explores ethical AI use in these settings, aiming to integrate findings into educational practices. Research content and method : Analyzing AI use and ethics guidelines from 50 domestic and international universities, differences between Christian and secular institutions were explored. Data was categorized, conceptualized via open coding, and components were identified through axial coding. The importance of components for Christian colleges' AI guides was assessed based on the initial data and previous research, leading to the development of tailored AI utilization components for Christian universities. Conclusion : Studies revealed secular institutions have six AI guide components, while Christian colleges found seven in both utilization and ethics guides, focusing on truthfulness, responsibility, and diversity. Emphasizing the need for ethical AI use in Christian colleges, the findings advocate developing AI ethics guidelines to aid marginalized groups and establish a new educational paradigm through further research.