• Title/Summary/Keyword: AI education direction

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A Study on the Future Directions according to Analysis of Necessity of AI Education (AI교육의 필요성 분석에 따른 미래 방향 탐색)

  • Yoo, Inhwan;Kim, Wooyeol;Jeon, Jaecheon;Yu, Wonjin;Bae, Youngkwon
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.423-431
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    • 2020
  • As artificial intelligence(AI) technology is advanced based on recent technological advances such as machine learning, big data, and machine learning, it is actively used in various fields and is emerging as the core of the future industry. Accordingly, Korea is laying the groundwork for future AI technology development and environment establishment, such as announcing the national AI strategy, and is developing various policies to foster AI talent in the field of education. However, although many people agree on the importance or necessity of AI, it can be said that there is insufficient consensus on specific needs. Looking at related studies, there are many differences in the direction of AI education content and methodology, because awareness of necessity becomes a prerequisite for setting the direction, and accordingly, the direction such as educational content and method is determined. Therefore, this study aims to explore the direction of AI education by analyzing the difference in perceptions of the need for AI education between experts and the school field, and analyzing the perception of the need for AI education that everyone can relate to.

Domestic Research Trend of AI Education Program: A Scoping Review (국내 AI 교육 프로그램 연구동향 분석: 주제범위 문헌고찰 방법론을 적용하여)

  • Han, Jeongyun;Huh, Sun Young
    • Journal of The Korean Association of Information Education
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    • v.25 no.6
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    • pp.879-890
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    • 2021
  • AI education is being emphasized nationwide as a literacy education. At this point, it is necessary to identify critical issues and suggest the direction of future research by examining domestic AI education research trends. To this end, the study applied the scoping review method. A total of 29 AI educational studies from 2017 to 2020 in South Korea were analyzed. As a result, it was confirmed that the number of studies increased rapidly in 2020, and a large proportion of studies targeted elementary school students. In addition, the study found that AI principles were treated as contents at a high rate, both cognitive and affective aspects were frequently reported as a learning outcome, and various practice environments were used relatively evenly. Based on the results, the direction of future research was discussed and suggested.

Analysis of Domestic Research Trends in AI Ethics Education (인공지능윤리교육의 국내 연구 동향 분석)

  • Kim Kyeongju
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.4
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    • pp.29-44
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    • 2023
  • This study examined research trends in AI ethics education and attempted to suggest a direction for AI ethics education. As a result of the research, two studies were conducted in 2017. There are no studies in 2018 and 2019, and there are 6 studies in 2020. Since then, research has continued to increase, with 19 studies in 2021 and 18 studies in 2022. There were a total of 37 lead authors of the study. There were six lead authors who had published papers for more than two years, and two lead authors who had published papers for more than three years. In addition, to examine the details of AI ethics education, a total of 265 keywords that went through a refining process were divided into education-related, ethics-related, AI-related, and other-related. Although the necessity and importance of research on AI ethics education is expected to increase, there are not many researchers who continuously conduct research on AI ethics education. Accordingly, there is a need to find ways to continue research on AI ethics education. AI ethics education is being conducted under various names such as moral education, ethics education, liberal arts education, and AI education. Accordingly, research on AI ethics education at various levels and forms should be conducted, not just educational research on artificial intelligence ethics in terms of regular subjects.

Exploring the Operating and Supporting Direction of AI Curriculum by Analyzing A High School Case Study

  • Sungryong Ju;Seulgi Song;Seung-Bo Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.4
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    • pp.175-186
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    • 2023
  • This study was conducted to explore the necessary conditions and support for stable operation of an expanded AI curriculum in education. A high school that has implemented an AI curriculum since 2020 was targeted, and students and teachers were surveyed on their perceptions of the AI curriculum, implementation and support strategies. The survey items were categorized into 1) experience with AI education, 2) implementation direction of AI education, and 3) expected effects through AI education, and the results were derived focusing on frequency analysis to identify trends. The analysis resulted in three implications. First, it was suggested that the activation of AI education. Second, the need to develop a hands-on AI curriculum and incorporate AI throughout the entire curriculum was highlighted. Third, it was emphasized that efforts to enhance the capabilities of teachers to implement AI teaching and learning, along with the expansion of physical infrastructure for hands-on education, are necessary.

Utilization Strategies of Generative AI Platforms for CG Education (CG 교육을 위한 생성형 인공지능 플랫폼 활용 방안)

  • Donghee Suh
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.357-364
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    • 2023
  • Due to the rapid advancement of AI technology, generative artificial intelligence platforms are experiencing innovative applications in various fields. In this paper, it examines research cases involving the utilization of AI in education, explore instances where generative AI platforms are applied in the realm of creative endeavors, and discuss the direction of utilizing generative AI in educational contexts. In the field of computer graphics, this study introduced generative AI platforms that are applicable for image creation, editing, and video editing. It also proposed platforms that can be utilized in the video editing production process. These generative AI platforms not only offer advantages in terms of efficiency, by reducing the efforts of creators and saving time in the production process, but they also present positive aspects in enhancing individual capabilities. It is advocated that their swift integration into education is necessary, considering these benefits. This study aims to provide direction for the expansion of creative education utilizing generative AI platforms.

Investigating learner perceptions for effective teaching of Generative AI - from a game development perspective -

  • Bu-ho Choi
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.11
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    • pp.137-144
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    • 2024
  • In this study, we aim to devise an effective generative AI education direction for those learning game development. In the past, artificial intelligence technology was used to create game content, but with the emergence and rapid development of generative AI, its role has expanded to a tool for game development. This is changing the entire game development process. However, these developments brought not only opportunities but also anxiety to those in demand for education. This class is designed to relieve these anxieties, allow educational consumers to create part of the game development process using generative AI rather than traditional game development methods, and change their perception of generative AI through this experience. A post-training survey was conducted to explore perceptions of generative AI and capture the skills needed to use generative AI smoothly and demand for additional training areas. Through this, we propose a method for effectively teaching generative AI technology and suggest implications for the future direction of generative AI education.

Analyzing Teachers' Educational Needs to Strengthen AI Convergence Education Capabilities (AI 융합교육 역량 강화를 위한 교사의 교육요구도 분석)

  • JaMee Kim;Yong Kim
    • Journal of Internet Computing and Services
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    • v.24 no.5
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    • pp.121-130
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    • 2023
  • In the school field, AI convergence education is recommended, which utilizes AI in education to change the paradigm of society. This study was conducted to define the terms of AI and AI convergence education to minimize the confusion of terms and to analyze the educational needs of teachers from the perspective of conducting AI convergence education. To achieve the purpose, 19 experts' opinions were collected, and a self-administered questionnaire was administered to 125 secondary school teachers enrolled in the AI convergence major at the Graduate School of Education. As a result of the analysis, the experts defined AI convergence education as a methodology for problem solving, not AI-based or utilization education. In the analysis of teachers' educational needs, "AI and big data" was ranked first, followed by "AI convergence education methodology" and "learning practice using AI". The significance of this study is that it defined the terminology by collecting the opinions of experts amidst the confusion of various terms related to AI, and presented the educational direction of AI convergence education for in-service teachers.

The Direction of AI Classes using AI Education Platform

  • Ryu, Mi-Young;Han, Seon-Kwan
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.5
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    • pp.69-76
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    • 2022
  • In this paper, we presented the contents and methods of AI classes using AI platforms. First, we extracted the content elements of each stage of the AI class using the AI education platform from experts. Classes using the AI education platform were divided into 5 stages and 25 class elements were selected. We also conducted a survey of 82 teachers and analyzed the factors that they acted importantly at each stage of the AI platform class. As a result of the analysis, teachers regarded the following contents as important factors for each stage that are AI model preparation stage (the learning stage of the AI model), problem recognition stage (identification of problems and AI solution potential), data processing stage (understanding the types of data), AI modelingstage (AI value and ethics), and problem solvingstage (AI utilization in real life).

Exploration of AI Curriculum Development for Graduate School of Education (교육대학원 AI교육과정 개발 탐색)

  • Bae, Youngkwon;Yoo, Inhwan;Jang, Junhyeok;Kim, Daeyu;Yu, Wonjin;Kim, Wooyeol
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.433-441
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    • 2020
  • The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

Direction for Designing a 3D Animation Curriculum Utilizing AI Technology

  • Jibong Jeon
    • Journal of Information Technology Applications and Management
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    • v.30 no.5
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    • pp.141-158
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    • 2023
  • In the field of animation, as technology advances, production technology, production methods, and production culture are also steadily developing. The demand for content is increasing rapidly around the OTT platform, and the demand for animation content and diversity is increasing. With these market changes, animation creation ability is becoming a more important animation education goal. There is also a need to innovate educational methods to provide students with the skills and knowledge required in the modern animation business. This paper investigated the composition of the educational curriculum of domestic and foreign animation universities education. It examines artificial intelligence (AI) technology that can be used in animation creation and explores the design and direction of the university animation curriculum using it. AI technology has already proven its potential in various areas, and it is integrated into the animation curriculum to present various development potentials. Using AI technology, students can focus on practical and essential animation education by preventing technical difficulties in animation creation, increase their experience in animation production, and experiment with planning and producing various contents. It is proposed to design an educational curriculum that further strengthens animation creation and production capabilities by forming smart animation classes to foster talents who can lead the future animation industry in a new direction.