• Title/Summary/Keyword: AI 교수설계

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Teaching and Learning Design for AI Value Judgment (인공지능 가치판단에 대한 교수학습 설계)

  • Jeong, Minhee;Shin, Seungki
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.233-237
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    • 2021
  • With the advent of the 4th industrial revolution, interest in artificial intelligence education is increasing in elementary schools. In order to nurture future talents with artificial intelligence capabilities, AI education should be actively conducted at school sites. Although basic software education is provided in the 2015 revised curriculum, there is a tendency to view the programming process that creates artificial intelligence only as a problem-solving process. However, when creating an artificial intelligence, the value of the developer who creates artificial intelligence is projected. Therefore, it is necessary to deal with the contents of artificial intelligence value judgment during SW education. This study has limitations due to the fact that Delphi research was conducted with a group of experts. In the future, it is judged that quantitative research should be conducted to supplement these limitations.

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AI-Based Educational Platform Analysis Supporting Personalized Mathematics Learning (개별화 맞춤형 수학 학습을 지원하는 AI 기반 플랫폼 분석)

  • Kim, Seyoung;Cho, Mi Kyung
    • Communications of Mathematical Education
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    • v.36 no.3
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    • pp.417-438
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    • 2022
  • The purpose of this study is to suggest implications for mathematics teaching and learning when using AI-based educational platforms that support personalized mathematics learning. To this end, we selected five platforms(Knock-knock! Math Expedition, knowre, Khan Academy, MATHia, CENTURY) and analyzed how the AI-based educational platforms for mathematics reflect the three elements(PLP, PLN, PLE) to support personalized learning. The results of this study showed that although the characteristics of PLP, PLN, and PLE implemented on each platform varied, they were designed to form PLEs that allow learners to make their autonomous decisions about learning based on PLP and PLN. The significance of this study can be found in that it has improved the understanding and practicability of personalized mathematics learning with the AI-based educational platforms.

Hybrid Learning-Based AI Education System Design Model (하이브리드 러닝 기반 AI 교육 시스템 구성)

  • Hong, Misun;Bae, JinAh;Park, Jung-Hwan;Cho, Jungwon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.188-190
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    • 2022
  • We propose how to configure the AI education system based on the purpose of hybrid learning and the teaching-learning principle. Based on the four components of hybrid learning, we have designed the system conceptual diagram and DB configuration diagram for on-line and offline learning environments for effective AI education. The proposed AI education system model in this paper is expected to be a foundation for maximizing the effectiveness of AI education according to the level and needs of learners and building a more effective learner-centered learning environment in cultivating computational thinking in AI education.

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A Trend Analysis of Computer Education based on SNS Data through Data Mining Analysis (텍스트마이닝 분석을 활용한 SNS 데이터 기반의 정보교육의 동향 분석 연구)

  • Kim, Kapsu;Chun, Seokju;Koo, Dukhoi;Shin, Seungki
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.289-300
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    • 2021
  • SNS data was collected and analyzed by topic modeling techniques to examine recent trends in information education. By deriving keywords and topics for SW education and AI education, we not only attempted to discover insights ahead of the next revised curriculum but also suggested directions. According to the SNS data analysis, the contents of human resource development for software and the instructional method in schools are indicated as a high requirement. Meanwhile, SW education should be conducted through a separate curriculum from elementary school, and this was consistent with the opinion that it is necessary to be organized as a required subject. There was an opinion to support the schools since AI education is newly introduced in next revised national curriculum. The trends in SW education and AI education which are observed through SNS data analysis could be concluded to conduct the substantial operation of information education and curriculum organization.

Study of Data-Driven Problem Solving SW Education Program using Micro:bit. (마이크로비트를 활용한 데이터 기반 문제해결 SW교육 방안 연구)

  • Oh, SeungTak;Yu, HeaJin;Kim, BongChul;Kim, JongHun
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.25-30
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    • 2021
  • With the introduction of AI education in the 2022 Revised Curriculum emphasizing the need for data related education, it is necessary to improve students' data based problem solving skills. This study seeks to study SW education methods to improve students' data based problem solving skills in accordance with these needs. Based on the ADDIE model, the demand analysis survey was conducted on teachers to analyze their needs. Based on the results of the demand analysis, we designed education programs under the theme of data based problem solving skills using microbit. In this study, we raise the importance of data based problem solving and the need for its capabilities. Subsequent studies need to reveal how data based problem solving SW education will demonstrate significant effects on problem solving skills.

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A case study of elementary school mathematics-integrated classes based on AI Big Ideas for fostering AI thinking (인공지능 사고 함양을 위한 인공지능 빅 아이디어 기반 초등학교 수학 융합 수업 사례연구)

  • Chohee Kim;Hyewon Chang
    • The Mathematical Education
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    • v.63 no.2
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    • pp.255-272
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    • 2024
  • This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.

Educational Model for Artificial Intelligence Convergence Education (예비 교사의 인공지능 융합 수업 전문성 함양을 위한 교육 모델 제안)

  • Seong-Won Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.229-231
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    • 2023
  • 테크놀로지의 발달에 따라 수업에서 테크놀로지의 도입이 증가하고 있다. 테크놀로지는 학교 현장에 도입되어서, 교수-학습 형태의 변화와 교육 환경의 혁신을 이끌고 있다. 이에 따라 수업에서 테크놀로지 중요성은 더욱 증가하였으며, 예비 교사의 교육 모델에서 테크놀로지 지식을 함양하기 위한 노력이 이어졌다. 이에 따라 Mishra and Koehler(2006)의 TPACK 모델을 활용한 교육이 활발하게 이루어지고 있다. 본 연구에서는 TPACK 모델을 활용하여 예비 교사의 인공지능 융합 수업 전문성을 함양하기 위한 교육 모델을 개발하였다. 개발한 교육 모델은 브레인스토밍, 협력, 탐색(TPACK, AI, 교육과정, 교육적 맥락, 수업 사례), 수업 설계, 마이크로티칭, 수업 비평, 수업 성찰을 포함하였다. 본 연구에서 개발한 인공지능 융합 TPACK 교육 모델을 바탕으로 예비 교사의 인공지능 융합 수업 전문성 변화를 분석하는 후속 연구가 필요하다.

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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.

Pattern recognition and AI education system design for improving achievement of non-face-to-face (e-learning) education (비대면(이러닝) 교육 성취도 향상을 위한 패턴인식 및 AI교육 시스템 설계)

  • Lee, Hae-in;Kim, Eui-Jeong;Chung, Jong-In;Kim, Chang Suk;Kang, Shin-Cheon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.329-332
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    • 2022
  • This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

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Pattern Recognition and AI Education System Design Proposal for Improving the Achievement of Non-face-to-face (E-Learning) Education (비대면(이러닝) 교육 성취도 향상을 위한 패턴인식 및 AI교육 시스템 설계 구축)

  • Lee, Hae-in;Kim, Eui-Jeong;Chung, Jong-In;Kim, Chang Suk;Kang, Shin-Cheon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.280-283
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    • 2022
  • This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

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