• Journal of Digital Convergence
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• v.19 no.1
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• pp.141-149
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• 2021

Due to the rapid rise of artificial intelligence technology around the world, SW education conducted in elementary and secondary schools is expanding including AI education. Therefore, this study aims to present an AI education system based on 4P(Play, Problem Solving, Product Making, Project) that can be applied from kindergarten to high school. The AI education system presented in this study is designed to be applied in 4P-based Play, Problem Solving, Product Making, and Project 4 stages so that it can be applied by school age and step by step. The level was presented by dividing it into two areas: AI literacy and AI development. In order to verify the validity of the developed AI education system, the Delphi method was applied to 15 experts who had experience in SW education or AI education. The AI education system derived as a result of the verification will be able to contribute to the development of a content system for AI education at each school level in the future.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.157-162
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• 2022

In a society full of knowledge and information, digital literacy and artificial intelligence (AI) education that can utilize AI technology is needed to solve numerous everyday problems based on computational thinking. In this study, data-centered AI education was conducted while teaching computer programming to non-computer programming students at universities, and the correlation between major factors related to academic performance was analyzed in addition to student satisfaction surveys. The results indicated that there was a strong correlation between grades and problem-solving ability-based tasks, and learning satisfaction. Multiple regression analysis also showed a significant effect on grades (F=225.859, p<0.001), and student satisfaction was high. The non-computer programming students were also able to understand the importance of data and the concept of AI models, focusing on specific examples of project types, and confirmed that they could use AI smoothly in their fields of interest. If further cases of AI education are explored and students' AI education is activated, it will be possible to suggest its direction that can collaborate with experts through interest in AI technology.

• Korean Medical Education Review
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• v.22 no.2
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• pp.99-114
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• 2020

The rapid development of artificial intelligence (AI), including deep learning, has led to the development of technologies that may assist in the diagnosis and treatment of diseases, prediction of disease risk and prognosis, health index monitoring, drug development, and healthcare management and administration. However, in order for AI technology to improve the quality of medical care, technical problems and the efficacy of algorithms should be evaluated in real clinical environments rather than the environment in which algorithms are developed. Further consideration should be given to whether these models can improve the quality of medical care and clinical outcomes of patients. In addition, the development of regulatory systems to secure the safety of AI medical technology, the ethical and legal issues related to the proliferation of AI technology, and the impacts on the relationship with patients also need to be addressed. Systematic training of healthcare personnel is needed to enable adaption to the rapid changes in the healthcare environment. An overall review and revision of undergraduate medical curriculum is required to enable extraction of significant information from rapidly expanding medical information, data science literacy, empathy/compassion for patients, and communication among various healthcare providers. Specialized postgraduate AI education programs for each medical specialty are needed to develop proper utilization of AI models in clinical practice.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.197-209
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• 2024

This study aimed to analyze recent research trends in Artificial Intelligence (AI) education within South Korea with the overarching objective of exploring the future direction of AI education. For this purpose, an analysis of 697 papers related to AI education published in Research Information Sharing Service (RISS) from 2016 to November 2023 were analyzed using word cloud and Latent Dirichlet Allocation (LDA) topic modeling technique. As a result of the analysis, six major topics were identified: generative AI utilization education, AI ethics education, AI convergence education, teacher perceptions and roles in AI utilization, AI literacy development in university education, and AI-based education and research directions. Based on these findings, I proposed several suggestions, (1) including expanding the use of generative AI in various subjects, (2) establishing ethical guidelines for AI use, (3) evaluating the long-term impact of AI education, (4) enhancing teachers' ability to use AI in higher education, (5) diversifying the curriculum of AI education in universities, (6) analyzing the trend of AI research, and developing an educational platform.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.65-70
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• 2024

As the interest in AI education grows, researchers have made efforts to implement AI education programs. However, research targeting pre-service teachers has been limited thus far. Therefore, this study was conducted to develop an AI literacy education program for preservice secondary teachers. The research results revealed that the weekly topics included the definition and applications of AI, analysis of intelligent agents, the importance of data, understanding machine learning, hands-on exercises on prediction and classification, hands-on exercises on clustering and classification, hands-on exercises on unstructured data, understanding deep learning, application of deep learning algorithms, fairness, transparency, accountability, safety, and social integration. Through this research, it is hoped that AI literacy education programs for preservice teachers will be expanded. In the future, it is anticipated that follow-up studies will be conducted to implement relevant education in teacher training institutions and analyze its effectiveness.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.711-721
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• 2018

The development of artificial intelligence technology and the shift to a software-driven society are raising the need for digital literacy education on how to access, understand, use, create and share new open content in a variety of sustainable open content. At this point in time, this paper defines the digital literacy as the subliteracy concept for data, tools, and device elements. It is defined as a concept that includes cognitive and non-cognitive abilities and is stratified by computer literacy, ICT literacy, and information literacy. Open content is also defined as teaching-learning materials that can be used and shared freely by anyone, such as the Open Education Resource (OER) and the Open Access movement. Based on the two definitions, a three-step strategy for digital literacy education was developed to select open content in the digital environment, followed by a digital literacy education plan, and finally, an education frame to foster digital literacy capabilities.

• Trans-
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• v.12
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• pp.1-19
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• 2022

This study predicts and raises the changes that AI will bring to dance art when machine-based choreography began, and finds questions we can ask as human artists. Research suggests that one of the crises of dance in the era of machine creative arts is that artificial intelligence does not stay in the tool of human choreography but becomes the subject of choreography. It is based on the political discourse of choreography that artificial intelligence has the power to control and restrict human dancers. This comes from a sense of crisis that the AI takes over the area of choreography and the human choreographer remains an incompetent coordinator, and as a result, the dancer's dancing body can be reduced to a mechanical body controlled by AI. In order for these concerns not to become a reality, this study proposes three measures. First, choreographer and dancer should develop digital literacy to live in the age of AI art. Secondly, choreographer should acquire the ability to accurately distinguish the roles of human choreographer, dancer, and AI in creative work. Thirdly, various levels of discourse on AI dance should be formed by actively conducting mutual media research of dance and technology. Through these efforts, the human dancer will exist as a subject of art, not a passive agent in the new dance ecosystem brought by the innovation of artificial intelligence technology and will be able to face an era coexistence with artificial intelligence creativily and productively.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.281-288
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• 2023

This study aimed to develop an integrated arts education program for improving AI literacy among elementary school students. First, we developed two thematic programs that are research on the goals of the art, music, physical curriculum in the 2022 revised elementary school curriculum, and a matrix of goals and elements of integrated art education. The developed program was revised and supplemented through the first expert validity test, and the second revision was made based on the results of students' AI literacy pre/post-test and satisfaction survey with the program. Finally, the final program was developed through the third expert validity test. We hope that the developed program will be used as a convergence education program to cultivate AI literacy in elementary school students.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.274-281
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• 2021

In the field of artificial intelligence education, discussions on the direction of artificial intelligence education are actively underway, and it is necessary to establish a foundation for future information education. It is necessary to design a creative convergence teaching-learning and evaluation method. Although AI experience coding education has been applied, the evaluation stage is insufficient. In this paper, we propose an evaluation system that can verify the validity of the proposed education model to find a way to supplement the existing learning module. The core components of this proposed system are Assessment-Factor, Self-Diagnosis, Item Bank, and Evaluation Result modules, which are designed to enable system access according to the roles of administrator, instructors and learners. This system enables individualized learning through online and offline connection.

• The Mathematical Education
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• v.63 no.2
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• pp.387-392
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• 2024

The use of artificial intelligence (AI) in mathematics education has advanced as a means for promoting understanding of mathematical concepts, academic achievement, computational thinking, and problem-solving. From a total of 13 studies in this special issue, this editorial reveals threads of potential and future directions to advance mathematics education with the integration of AI. We generated five themes as follows: (1) using ChatGPT for learning mathematical content, (2) automated grading systems, (3) statistical literacy and computational thinking, (4) integration of AI and digital technology into mathematics lessons and resources, and (5) teachers' perceptions of AI education. These themes elaborate on the benefits and opportunities of integrating AI in teaching and learning mathematics. In addition, the themes suggest practical implementations of AI for developing students' computational thinking and teachers' expertise.