• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

• 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.

• Korean Journal of Childcare and Education
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• v.19 no.2
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• pp.43-59
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• 2023

Objective: This study investigated the differences in preschool children's perceptions of artificial intelligence (AI) and their distribution by latent profiles according to their experience with AI robots in daycare centers. Methods: The participants included 119 five-year-old children, 52 of whom had experience with AI robots in daycare centers and 67 of whom did not. Children's perceptions of AI were measured using the Godspeed scale from Bartneck et al.(2009). Data were analyzed using a t-test, latent profile analysis, and chi-square test. Results: The results showed that compared to the inexperienced group, the experienced group reported lower levels of animacy and perceived intelligence of AI robots, indicating higher levels of AI knowledge and understanding. In addition, the experienced group had a higher probability of belonging to the 'machine recognition' type than 'organism recognition' type, although the difference was not statistically significant. Conclusion/Implications: The findings suggest that experience with AI robots in daycare centers can improve children's AI knowledge and understanding. To further enhance this effect, it is necessary to increase the number of robots put into classrooms, and to consider various teaching media that reflect children's preferences.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.101-110
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• 2020

Devices that add emotion-specific services or various functions are appearing in AI speakers and related devices. To this end, this study performed topic modeling analysis on the topics of post-purchase texts written by AI speaker users, and compared them with the data collected via survey questionnaires. Furthermore, data on the emotional intelligence of AI speakers and relationship quality were collected from 600 users and analyzed using structural equation modeling. The findings of the study are as follows: First, the analysis results of topic modeling showed that most of the articles mainly mention the functional aspects of AI speakers. Second, emotional intelligence of AI speaker perceived by consumer affected relationship quality, and relationship quality had a positive effect on customer satisfaction. Therefore, this study expands the area of AI research by integrating the concept of emotional intelligence and relationship quality to provide new theoretical and practical implications.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.281-293
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• 2022

The necessity for introducing artificial intelligence(AI) into the public sector to form an intelligent government has been emerging. This study set 'Organizational Agility', 'Exploitation & Exploration Learning', and 'E-government Capability' as independent variables for the introduction of AI in central government. Dependent variables were set on whether AI was adopted in the central government organization 'Bu(mainly conducts policy planning)', and 'Cheong(mainly performs policy execution)'. Logistic regression analysis was performed on each of the two models. As a result, it was derived that ministry Bu adopted AI as organizational agility increased, and ministry Chung adopted AI as e-government capability increased. Particularly, it was identified that the effect of exploitation learning for Cheong organizations offset the influence of AI introduction according to e-government capabilities, while exploratory organizational learning facilitated the AI introduction. This study is meaningful for suggesting a strategy for adopting AI in government.

• Informatization Policy
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• v.30 no.2
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• pp.22-45
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• 2023

In research on the use of AI-based voice assistant services, problems related to the user's trust and privacy protection arising from the experience of service use are constantly being raised. The purpose of this study was to investigate empirically the effects of individual trust in AI and online privacy concerns on the continued use of AI-based voice assistants, specifically the impact of their interaction. In this study, question items were constructed based on previous studies, with an online survey conducted among 405 respondents. The effect of the user's trust in AI and privacy concerns on the adoption and continuous use intention of AI-based voice assistant services was analyzed using the Heckman selection model. As the main findings of the study, first, AI-based voice assistant service usage behavior was positively influenced by factors that promote technology acceptance, such as perceived usefulness, perceived ease of use, and social influence. Second, trust in AI had no statistically significant effect on AI-based voice assistant service usage behavior but had a positive effect on continuous use intention. Third, the privacy concern level was confirmed to have the effect of suppressing continuous use intention through interaction with trust in AI. These research results suggest the need to strengthen user experience through user opinion collection and action to improve trust in technology and alleviate users' concerns about privacy as governance for realizing digital government. When introducing artificial intelligence-based policy services, it is necessary to disclose transparently the scope of application of artificial intelligence technology through a public deliberation process, and the development of a system that can track and evaluate privacy issues ex-post and an algorithm that considers privacy protection is required.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.201-208
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• 2023

As the demand for AI education increases, AI education is actively conducted in the educational field, but it is difficult to internalize AI education due to securing time, difficulty in organizing class contents, and lack of curriculum. As a way to solve this problem, there is a school autonomous course. The school autonomous course allows schools to have autonomy and discretion throughout the curriculum, such as adjusting the number of hours in the subject group and restructuring the use of achievement standards. In this study, in order to enhance AI education, the effect was analyzed by developing and applying an AI education immersion course using a school autonomous curriculum. In the AI education immersion course, students continuously experience AI education in a dense manner within a limited time, so substantial AI education can be achieved. After the AI curriculum, it was found that students' overall AI literacy and self-determination learning motivation improved. It is expected that this study will be able to present a direction to internalize AI education using school autonomous curriculum.

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Environmental Mutagens and Carcinogens
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• v.22 no.4
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• pp.243-247
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• 2002

Prolonged exercise is known to increase steady-state serum high-density lipoprotein cholesterol (HDL-cholesterol) and apolipoprotein AI(apo AI) concentrations. We investigated the effect of adaptation to endurance exercise on the association of the genetic polymorphism in the apo AI gene with these biochemical parameters. 108 male subjects were randomly selected from a group of elite athletes, and 65 male samples used as sedentary control group from Korean general population. The genetic polymorphism in the apo AI gene locus was detected by polymerase chain reaction(PCR) and DNA digestion with Msp I restriction endonuclease. The genotype frequency for the Msp I RFLP was significantly different between the elite athletes and sedentary controls(P<0.05). There were, however, no significant associations between the Msp I RFLP of the apo AI gene and the biochemical parameters in elite athletic group. Therefore, our findings indicate that the Msp I RFLP of the apo AI gene was not associated with the serum apo AI and HDL-cholesterol concentrations in Korean male elite athletes.

• Journal of Engineering Education Research
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• v.26 no.3
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• pp.12-19
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• 2023

The purpose of this study is to develop the Artificial Intelligence thinking-based education program for improving AI literacy and verify its effectiveness for beginner. This program consists of 17 sessions, was designed according to the "ABCDE" model and is a project-based program. This program was conducted on 51 first-year middle school students and 36 respondents excluding missing values were analyzed in R language. The effect of this program on ethics, understanding, social competency, execution plan, data literacy, and problem solving of AI literacy is statistically significant and has very large practical significance. According to the result of this study, this program provided learners experiencing Artificial Intelligence education for the first time with Artificial Intelligence concepts and principles, collection and analysis of information, and problem-solving processes through application in real life, and served as an opportunity to enhance AI literacy. In addition, education program to enhance AI literacy should be designed based on AI thinking.