• Journal of Information Technology Services
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• v.22 no.6
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• pp.17-35
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• 2023

This study investigated how helpful the use of generative AI such as ChatGPT is in conducting engaged learning at each university. In this study, based on the experiences of users using generative AI technology, we analyzed the relationship between usability and ease in consideration of the characteristics of learners, and examined whether there is an intention to continue using generative AI technology in the future. In this study, in order to verify the factors affecting the intention to use ChatGPT technology in order to solve the problems given in the participating classes, we examined previous papers based on the Technology Acceptance Model (TAM) and the Information System Success Model (IS), extracted the factors affecting the intention of ChatGPT technology, and presented the research model and hypothesis. Empirical research on the continuous use of generative AI in participatory learning using ChatGPT was conducted to determine whether it is suitable for long-term and continuous use in the educational environment, and whether it is sustainable by examining the intention of learners to continue using it. First, user satisfaction was positively related to the intention to continue using generative AI technology. Second, if the user experience has a great influence on the intention to continue using ChatGPT technology, and users gain experiences such as usefulness, interest, and effective response in the process of using the technology, the evaluation of the technology is positively formed and the intention to continue using it is high. Third, the ease of use of the technology also showed that it was intended to be used continuously when an environment was provided in which users could easily and conveniently utilize generative AI technology.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.588-591
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• 2021

4차 산업혁명 시대가 도래하면서 세상이 빠른 속도로 변하고 있다. 특히 데이터·인공지능(AI, Artificial Intelligence)의 활용이 적극적으로 다양한 분야에서 적용되기 시작하고 있다. 하지만 산림수종을 분석하는 업무를 수행하는 과정은 수작업으로 진행하다 보니 오류가 다수 발생하고 있다. 따라서 본 논문에서는 수도권 항공사진을 이용하여 소나무, 낙엽송, 침엽수, 활엽수를 대상으로 자동으로 분석하는 AI 학습용 데이터 약 60,000장을 구축하고, 수종을 구분할 수 있는 AI 모델을 개발하였다. 이를 통해 산림변화탐지 및 산림 분야 주제도 제작 시 수종 분할 이미지를 기초자료로 활용함으로써 업무효율 증대를 기대할 수 있다.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.59-69
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• 2020

The purpose of this study is to design the framework of evaluation on learner's cognitive skill for artificial intelligence(AI) education through computational thinking. To design the rubric and framework for evaluating the change of leaner's intrinsic thinking, the evaluation process was consisted of a sequential stage with a) agency that cognitive learning assistance for data collection, b) abstraction that recognizes the pattern of data and performs the categorization process by decomposing the characteristics of collected data, and c) modeling that constructing algorithms based on refined data through abstraction. The evaluating framework was designed for not only the cognitive domain of learners' perceptions, learning, behaviors, and outcomes but also the areas of knowledge, competencies, and attitudes about the problem-solving process and results of learners to evaluate the changes of inherent cognitive learning about AI education. The results of the research are meaningful in that the evaluating framework for AI education was developed for the development of individualized evaluation tools according to the context of teaching and learning, and it could be used as a standard in various areas of AI education in the future.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.116-124
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• 2018

This study aimed to interpreting the view of current media by artificial intelligence(AI) with the case of a TV show Person of Interest, which was broadcasted until 2016 in US. In this study, we first attempted to find how AI reflects the three laws of robotics, which often appear in Science Fictions. In addition, we paid attention to how the society looks according to the change of the manipulator of the AI, and as a result we derived the distinguishes of the show from other content dealing with robots or AI in terms of narrative. Through this study, we classified the messages in accordance of AI into three categories- importance of data sovereignty, potential of intelligence explosion, and blind faith in high technology. This study suggested that the show emphasizes the consciousness and attitude that should be possessed as a citizen who meets the era of AI prior to raising issue of 'what artificial intelligence is should be developed for our convenience?'

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.37-46
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• 2019

Humans have anxieties as well as expectations for artificial intelligence. This study attempted to identify the expectation and anxiety factors affecting the attitude toward artificial intelligence innovation and to ascertain how much influence they have on current artificial intelligence innovation. This study considered that attitudes toward artificial intelligence may be different for each generation sharing a similar technology change culture. Therefore, the researchers limited the research subjects to I generation, which is the main users of artificial intelligence in the future. As a main result, the factors of expectiation of 'performance gain', 'positive social impact', and the factor of anxiety of 'threat to human-oriented social value' were drawn, and these factors influenced weak and strong artificial intelligence respectively. The results of this study suggests that artificial intelligence should develop into a pleasant relationship with humankind.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.89-98
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• 2021

The Ministry of National Defense aims to create an environment in which transparent and reasonable defense policies can be implemented in real time by establishing the vision of smart defense innovation based on the Fourth Industrial Revolution and promoting innovation in technology-based defense operation systems. Artificial intelligence (AI) based defense technology is at the level of basic research worldwide, includes no domestic tasks, and involves classified military operation data and command control/decision information. Further, it is needed to secure independent technologies specialized for our military. In the army, military power continues to decline due to aging and declining population. In addition, it is expected that there will be more than 500,000 units should be managed simultaneously, to recognize the battle situation in real time on the future battlefields. Such a complex battlefield, command decisions will be limited by the experience and expertise of individual commanders. Accordingly, the study of AI core technologies supporting real-time combat command is actively pursued at home and abroad. It is necessary to strengthen future defense capabilities by identifying potential threats that commanders are likely to miss, improving the viability of the combat system, ensuring smart commanders always win conflicts and providing reasonable AI digital staff based on data science. This paper describes the recent research trends in AI military staff technology supporting commander decision-making, broken down into five key areas.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.7-12
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• 2024

The development of artificial intelligence technology changes the social structure and educational environment, and the importance of artificial intelligence capabilities continues to increase. This study was conducted with the purpose of developing a checklist of questions to measure AI capabilities of elementary school students. To achieve the purpose of the study, a Delphi survey was used to analyze literature and develop questions. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements consisted of understanding artificial intelligence (6 elements), artificial intelligence thinking (4 elements), artificial intelligence ethics (4 elements), and artificial intelligence social-emotion (3 elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 19 questions were developed. The developed questions were verified through the first Delphi survey, and 7 questions were revised according to the revision opinions. The validity of 19 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the measurement results of competency are raised to a reliable level.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.49-55
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• 2024

This study was conducted with the purpose of developing a checklist of questions to measure middle school students' AI capabilities. To achieve the goal of the study, literature analysis and question development Delphi survey were used. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements are understanding of artificial intelligence (5 elements), artificial intelligence thinking (5 elements), utilization of artificial intelligence (4 elements), artificial intelligence ethics (6 elements), and artificial intelligence social-emotion (6 elements). elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 31 questions were developed. The developed questions were verified through the first Delphi survey, and 10 questions were revised according to the revision opinions. The validity of 31 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the level of reliability of measurement results increases.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.37-50
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• 2024

This study explored the link between reproductive health knowledge, attitudes, and self-efficacy in young women from Uganda's Luwero district. A survey was conducted on 82 women in the Luwero region from May to July 2016, and the predictive power of knowledge and attitudes toward self-efficacy was evaluated through multiple linear regression analysis. Results showed positive correlations among these factors, with knowledge and attitude predicting self-efficacy. Specifically, understanding healthy puberty habits and valuing women's roles positively influenced self-efficacy for healthy behaviors. These findings emphasize the need to target these aspects in reproductive health education programs, crucial for addressing adolescent pregnancy and related issues in Uganda's rural areas.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.675-687
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• 2019

As interest in artificial intelligence increases, each university has been establishing a special graduate school with artificial intelligence major, and recently, the Korea government has established various support policies for artificial intelligence education. However, each university has a lot of difficulties because it has little experience in operating graduate education with the latest field of artificial intelligence and it is not easy to find experts. In this study, the response of graduate school students majoring in artificial intelligence was analyzed using IPA technique, and the direction of education of graduate school artificial intelligence major was searched. Among the 40 items surveyed by IPA, 12 items such as systematization of artificial intelligence curriculum, progress of class considering learning level, improvement of academic relations with guidance professors were extracted as items to be improved first. On the other hand, 8 items such as assistant capacity, and relationship with colleagues were overloaded, and twelve items such as instructor's lecture competency, appropriateness of educational contents, learner's artificial intelligence skills and knowledge, and attitude acquisition were to be maintained. In addition, eight items such as convergence education curriculum and diversity of education methods were all low in importance and performance. It is suggested that AI graduate school should be divided into two tracks(technical specialization, convergence expansion) by educational goal, and each track should be conducted by level-specific educational contents and methods suitable for student level. The curriculum should be elaborate and systematic to acquire AI knowledge, skills, and attitudes, and should have an individualized guidance system centered on excellent faculty members.