• The Journal of Information Systems
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• v.32 no.4
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• pp.189-210
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• 2023

Purpose This study aims to investigate factors that positively influence the continuous Artificial Intelligence(AI) Learning Continuity of business major students. Design/methodology/approach To evaluate the impact of AI education, a survey was conducted among 119 business-related majors who completed a software/AI course. Frequency analysis was employed to examine the general characteristics of the sample. Furthermore, factor analysis using Varimax rotation was conducted to validate the derived variables from the survey items, and Cronbach's α coefficient was used to measure the reliability of the variables. Findings Positive correlations were observed between business major students' AI Learning Continuity and their AI Interest, AI Awareness, and Data Analysis Capability related to their majors. Additionally, the study identified that AI Project Awareness and AI Literacy Capability play pivotal roles as mediators in fostering AI Learning Continuity. Students who acquired problem-solving skills and related technologies through AI Projects Awareness showed increased motivation for AI Learning Continuity. Lastly, AI Self-Efficacy significantly influences students' AI Learning Continuity.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.97-104
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• 2018

The purpose of this study was to investigate the expectation toward medical artificial intelligence(AI) of students in majoring health, and to utilize it as a basic data for widespread use of medical AI for 500 students majoring in health science at Cheonan city. The awareness of AI was 18.6%, the reliability of AI was 24.8%, and agreement to use of medical AI was 38%. Also, the higher the awareness and reliability of AI were, the higher the expectation of AI was. As a result, education on medical AI in the major field should be a cornerstone for the development of an effective healthcare environment utilizing medical AI by raising awareness, reliability and expectation of AI.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.71-86
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• 2022

The purpose of this study is to develop and validate a scale to measure the ethical awareness of users who accept artificial intelligence technology or service. To this end, the constructs and properties of AI ethics were identified through literature analysis on AI ethics. Reliability and validity were assessed through a preliminary survey(N=273), after conducting an open-type survey to men and women(N=133) in 10s to 70s nationwide, extracting the first questions, and reviewing them by experts. The results of an online survey conducted on men and women(N=500) were refined by confirmatory factor analysis. Finally, an AI technology ethics scale was developed. The AI technology ethics awareness scale was developed with 16 questions in total of 4 factors (transparency, safety, fairness, accountability) so that general awareness of ethics related to AI technology can be measured by detailed factors. In addition, through follow-up research, it will be possible to reveal the relationship with measurement variables in various fields by using the ethical awareness scale of artificial intelligence technology.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.553-566
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• 2022

This study collects social data and academic research data from portal sites and RISS, and analyzes TF-IDF, N-Gram, semantic network analysis, and CONCOR analysis to analyze the social awareness and current aspects of 'AI Literacy' and 'AI Convergence Education'. Through this, we tried to understand the social awareness aspect and the current situation, and to suggest implications and directions. In the social data, the collection of 'AI Convergence Education' was more than twice that of 'AI Literacy', indicating that awareness of 'AI Literacy' was relatively low. In 'AI Literacy', the keyword 'human' in social data showed no cluster to which it belonged, indicating a lack of philosophical interest in and awareness of humanities and AI. In addition, the keyword 'Ministry of Education' showed high frequency, importance, and centrality of connection only in the social data of 'AI convergence education', confirming that 'AI convergence education' is closely related to government policy.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.90-98
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• 2022

On February 12, 2019, the U.S. Department of Defense newly established and announced the "Defense AI Strategy" to accelerate the use of artificial intelligence (AI) technology for military purposes. As China and Russia invested heavily in AI for military purposes, the U.S. was concerned that it could eventually lose its advantage in AI technology to China and Russia. In response, China and Russia, which are hostile countries, and especially China, are speeding up the development of new military theories related to the overall construction and operation of the Chinese military based on AI. With the rapid development of AI technology, major advanced countries such as the U.S. and China are actively researching the application of AI technology, but most existing studies do not address the special topic of defense. Fortunately, the "Future Defense 2030 Technology Strategy" classified AI technology fields from a defense perspective and analyzed advanced overseas cases to present a roadmap in detail, but it has limitations in comparing private technology-oriented benchmarking and AI technology's maturity level. Therefore, this study tried to overcome the limitations of the "Future Defense 2030 Technology Strategy" by comparing and analyzing Chinese and U.S. military research cases and evaluating the maturity level of military use of AI technology, not AI technology itself.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-202
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• 2023

This study aims to propose a framework for evaluating the impact of artificial intelligence (AI) services, based on the concept of AI service impact. It also suggests a model for evaluating this impact and identifies relevant factors and measurement approaches for each item of the model. The study classifies the impact of AI services into five categories: ethics, safety and reliability, compliance, user rights, and environmental friendliness. It discusses these five categories from a broad perspective and provides 21 detailed factors for evaluating each category. In terms of ethics, the study introduces three additional factors-accessibility, openness, and fairness-to the ten items initially developed by KISDI. In the safety and reliability category, the study excludes factors such as dependability, policy, compliance, and awareness improvement as they can be better addressed from a technical perspective. The compliance category includes factors such as human rights protection, privacy protection, non-infringement, publicness, accountability, safety, transparency, policy compliance, and explainability.For the user rights category, the study excludes factors such as publicness, data management, policy compliance, awareness improvement, recoverability, openness, and accuracy. The environmental friendliness category encompasses diversity, publicness, dependability, transparency, awareness improvement, recoverability, and openness.This study lays the foundation for further related research and contributes to the establishment of relevant policies by establishing a model for evaluating the impact of AI services. Future research is required to assess the validity of the developed indicators and provide specific evaluation items for practical use, based on expert evaluations.

• 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.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.72-86
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• 2023

Objectives: The medical field is rapidly evolving with AI and digital technologies like AI-based X-ray analysis and digital therapeutics gaining approval. Telemedicine is becoming prominent, and medical schools are adapting by integrating AI education. Pusan National University leads a talent training project for AI in health. Korean Medicine is incorporating AI with diagnostic systems and chatbots. However, there's a lack of research on education awareness in Korean Medicine Colleges. The study aims to assess opinions on integrating AI, digital therapeutics, and DNA test into the Korean medicine college curriculum for improved education. Methods: We selected appropriate four specific areas: artificial intelligence in medicine, digital therapeutics, DNA test, and telemedicine. The questionnaire developed for this study underwent expert evaluation and was subsequently administered to registered KMDs of the Association of Korean Medicine, as well as students from 12 Korean Medicine universities. The survey was designed to analyze the awareness and perceived importance of the 4 areas. Results: Both KMDs and Korean medicine students exhibited comparable awareness levels across the four objectives. Notably, both groups identified a high educational necessity and importance of artificial intelligence in medicine for clinical settings. Statistically significant differences were observed between KMDs and students in their perspectives on the importance of telemedicine and DNA test in the Korean medicine field, the educational necessity of DNA test within Korean medicine universities, and the need for comprehension of regulations related to digital therapeutics. Conclusion: The survey of Korean medicine professionals and students underscores a strong understanding of key areas such as Telemedicine, medical AI, DNA test, and digital therapeutics. Medical AI is identified as crucial for future education. There's a consensus on the need for curriculum changes in Korean medicine schools, particularly in adapting to evolving healthcare trends. The focus should be on practical clinical application, with a call for additional research to better integrate student and practitioner perspectives in future curriculum reform discussions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2361-2368
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• 2009

Recently AI(Artificial Intelligence) is one of the issues in the on-line game, a research that a game character seems to be realistic and is progressing using AI technique. Especially NPC is an important part of the AI researches of on-line game, and it is concerned by a game player and an architect. We proposed an intelligent agent framework to implement the NPC technique after studying the NPC technique using context awareness that reacts to the PC(Player Character) actively. Also, it can be developed gradually, and apply to various application because it has the capability to of adding an agent or deleting an agent easily.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.4
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• pp.371-380
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• 2023

Purpose: The purpose of this study is to determine the relationship between nursing students' biomedical and artificial intelligence (AI) ethical awareness, ethical values, professional self-concept, and ethical decision-making confidence, and to then identify factors that can influence their ethical decision-making confidence. Methods: This study employed a descriptive research method and was conducted from June 8 to 12, 2023, with 204 students from three nursing colleges in Korea. The collected data were analyzed by frequency and percentage, independent t-test, Pearson's correlation coefficient, and multiple regression using IBM SPSS 23.0. Results: The results of the multiple regression analysis showed that the regression model was significant (F=18.88, p<.001) and that professional self-concept (β=.46, p<.001), ethics education (β=.23, p<.001), AI ethical awareness (β=.16, p=.020), and relativistic ethical values (β=.14, p=.035) explained 34.6% of the nursing students' ethical decision-making confidence. Conclusion: It is necessary to include professional self-concept, AI ethical awareness, and ethical values contents when constructing the curriculums of educational programs in order to improve nursing students' ethical decision-making confidence.