• Title/Summary/Keyword: 초등학교 인공지능 교육

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An Analysis of Gender Differences in Primary, Middle and High School Students' Artificial Intelligence Ethics Awareness (초·중·고등학생의 인공지능 윤리의식의 성차 분석)

  • Kim, Gwisik;Shin, Youngjoon
    • Journal of Science Education
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    • v.45 no.1
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    • pp.105-117
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    • 2021
  • The purpose of this study is to analyze the gender differences of elementary, junior high, and high school students in the artificial intelligence ethics awareness (hereinafter referred to as AIEA). This is a study to investigate whether there is a gender difference in the AIEA, and if so, when the gender difference will occur. This study was conducted with 198 elementary school students (98 female students, 100 male students), 265 middle school students (166 female students, 99 male students), and 114 high school students (58 female students and 56 male students) in I Metropolitan City. The results are as follows: First, a gender difference in the AIEA between all boys and girls was confirmed. Second, the gender difference in the AIEA tended to be solidified as the school age increased from elementary school to middle school and high school. Third, female students at all stages of elementary school, junior high school, and high school are not yet very reliable in artificial intelligence, and there is a greater concern about non-discrimination than boys. It turns out that they have a negative position on permission to enter the territory. Fourth, the interaction effects of school age and gender have been identified in 'stability and reliability,' and in 'permit and limit' categories. Taken together, these results show that an educational strategy that approaches the gender equality perspective of the educational program is necessary so that there will be no gender difference in the AIEA during artificial intelligence education activities.

Development and application of artificial intelligence education program for mathematics convergence using robots (로봇을 활용한 수학 융합 인공지능 프로그램 개발 및 적용: 4학년 '각도'와 '사각형' 단원을 중심으로)

  • Choi, Sun Young;Chang, Hyewon
    • Education of Primary School Mathematics
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    • v.27 no.1
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    • pp.19-38
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    • 2024
  • This study aims to analyze the characteristics of students' understanding of artificial intelligence and mathematical concepts by developing and applying an artificial intelligence education program for mathematics convergence using robots. To this end, we analyzed the content standards of elementary artificial intelligence education to extract conceptual elements of artificial intelligence and identified mathematics achievement standards that can effectively integrate them. In particular, a five-session (15 classes in total) program was developed by selecting the units 'angle' and 'quadrilateral' suitable for utilizing the robot's movement and reorganizing the lesson to integrate the mathematics achievement standard with the artificial intelligence content elements. As a result of applying this to 22 fourth grade elementary school students over five months and analyzing the students' understanding revealed by topic of artificial intelligence content, the artificial intelligence education program for mathematics convergence using robots was helpful in students' understanding artificial intelligence principles and mathematical concepts. In addition, the use of robots was confirmed to improve students' understanding of artificial intelligence and mathematics as well as their participation in class by making them visually check a series of performing procedures.

Development of AI Education Program for Prediction System Based on Linear Regression for Elementary School Students (선형회귀모델 기반의 초등학생용 인공지능 예측 시스템 교육 프로그램의 개발)

  • Lee, Soo Jeong;Moon, Gyo Sik
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.51-57
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    • 2021
  • Quite a few elementary school teachers began to utilize AI technology in order to provide students with customized, intelligent information services in recent years. However, learning principles of AI may be as important as utilizing AI in everyday life because understanding principles of AI can empower them to buildup adaptability to changes in highly technological world. In the paper, 'Linear Regression Algorithm' is selected for teaching AI-based prediction system to solve real world problems suitable for elementary students. A simulation program written in Scratch was developed so that students can find a solution of linear regression model using the program. The paper shows that students have learned analyzing data as well as comparing the accuracy of the prediction model. Also, they have shown the ability to solve real world problems by finding suitable prediction models.

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Development of Design thinking-based AI education program (디자인 씽킹 기반 인공지능 교육 프로그램 개발)

  • Lee, Jaeho;Lee, Seunghoon
    • Journal of The Korean Association of Information Education
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    • v.25 no.5
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    • pp.723-731
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    • 2021
  • In this study, the AI education program for elementary school students was developed and applied by introducing the design thinking process, which is attracting attention as a creative problem solving process. A design thinking-based AI education program was developed in the stages of Understanding AI, Identifying sympathetic problems, Problem definition, Ideate, Prototype, Test and sharing, and the development program was applied to elementary school students in 4th-6th grade. As a result of pre- and post-testing of students' computational thinking skills to confirm the effectiveness of the program, computational thinking skills increased by grade level, and students experienced a process of collaboration for creative problem solving based on insights gained from sympathetic problem finding. In addition, it was possible to get a glimpse of the attitude of using AI technology to solve problems, and it was confirmed that ideas were generated in the prototype stage and developed through communication between team members. Through this, the design thinking-based AI education program as one of the AI education for elementary school students guarantees the continuity of learning and confirms the possibility of providing an experience of the creative problem-solving process.

The Analysis of Illustrations in Elementary School Artificial Intelligence Textbooks in Korea (국내 초등 인공지능 교재 내 삽화 분석)

  • Hwang, Ji-Yeon;Kim, Seong-Won;Lee, Youngjun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.217-218
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    • 2022
  • 인공지능(Artificial Intelligence, 이하, AI) 기술의 발달로 각계각층에서 급진적인 변화를 대비하고 있다. 이에 교육부에서도 2022 개정 교육과정 주요사항에 AI 소양을 새로운 기초 소양으로 제시하였다. 이에 초등학생에게 AI 개념 및 원리를 전달하려는 교재가 많이 개발되고 있다. 교재 및 교과서는 교수·학습 과정에서 필수적인 역할을 수행한다. 그리고 교과서의 내용 요소 중 핵심적인 내용을 함축하는 삽화는 글보다 지식 전달에 효율적이다. 보다 일차원적이고 직관적인 삽화를 통하여 초등학생에게 인공지능 지식을 쉽게 전달하기 위하여 기존 교재에 제시된 삽화의 분석이 필수적이라고 판단하였다. 따라서 교육부와 한국과학창의재단에서 출판된 '학교에서 만나는 인공지능 수업(초등학생용)' 2권에 제시된 삽화를 종류 및 역할별로 분류하였다. 삽화의 종류 중 그림과 사진의 비중이 컸고, 자료제공을 하는 과정에서 삽화가 다수 사용되었다. 본 논문을 통하여 인공지능 교재의 삽화에 대한 보충적인 연구가 이루어지길 기대한다.

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Analysis of research status on domestic AI education (국내 인공지능 교육에 대한 연구 현황 분석)

  • Park, Mingyu;Han, Kyujung;Sin, Subeom
    • Journal of The Korean Association of Information Education
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    • v.25 no.5
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    • pp.683-690
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    • 2021
  • The purpose of this study is to identify research trends on artificial intelligence education. We analyzed 164 domestic journal papers related to AI education published since 2016. The criteria for papers analysis are number of publications by year, journal name, research topic, research type, data collection method, research subject, and subject. The main research areas and areas that require further research are reviewed. The method of the study was analyzed based on the topic and summary of the selected papers, but the text was checked if it was unclear. As a result of the study, research on 'artificial intelligence education' started in earnest after 2017, and has been rapidly increasing in recent years. As a result of the analysis, there were many studies on artificial intelligence education programs and content development, and artificial intelligence perception and image. As for the type of research, there were many quantitative studies, and the development research method was used a lot as a data collection method. In the study subjects, elementary school had a high proportion, and in subject, it was found that there were many practicial subject(technology) dealing with artificial intelligence contents.

Analysis of research status on domestic AI education (국내 인공지능 교육에 대한 연구 현황 분석)

  • Park, Mingyu;Han, Kyujung;Sin, Subeom
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.69-76
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    • 2021
  • The purpose of this study is to identify research trends on artificial intelligence education. We analyzed 164 domestic journal papers related to AI education published since 2016. The criteria for thesis analysis are number of publications by year, journal name, research topic, research type, data collection method, research subject, and subject. The main research areas and areas that require further research are reviewed. The method of the study was analyzed based on the topic and summary of the selected thesis, but the text was checked if it was unclear. As a result of the study, research on 'artificial intelligence education' started in earnest after 2017, and has been rapidly increasing in recent years. As a result of the analysis, there were many studies on artificial intelligence education programs and content development, and artificial intelligence perception and image. As for the type of research, there were many quantitative studies, and the development research method was used a lot as a data collection method. In the study subjects, elementary school had a high proportion, and in subject, it was found that there were many practicial subject(technology) dealing with artificial intelligence contents.

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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.

An analysis of perceptions of elementary teachers and secondary mathematics teachers on the use of artificial intelligence (AI) in mathematics education (수학교육에서 인공지능 활용에 대한 초등 교사와 중등 수학 교사의 인식 분석)

  • JeongWon Kim
    • The Mathematical Education
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    • v.63 no.2
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    • pp.351-368
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    • 2024
  • One of the important factors for the effective implementation of artificial intelligence (AI) in mathematics education is the perceptions of the teachers who adopt it. This study surveyed 161 elementary school teachers and 157 secondary mathematics teachers on their perceptions of using AI in mathematics education, grouped into four categories: attitude toward using AI, AI for teaching mathematics, AI for learning mathematics, and AI for assessing mathematics. The findings showed that teachers were most positive about using AI for teaching and learning mathematics, whereas their attitudes towards using AI were less favorable. In addition, elementary school teachers demonstrated a higher positive response rate across all categories compared to secondary mathematics teachers, who exhibited more neutral perceptions. Based on the results, we discussed the pedagogical implications for teachers to effectively use AI in mathematics education.

Design of Machine Learning Education Program for Elementary School Students Based on Sound Data (소리 데이터를 활용한 블록 기반의 초등 머신러닝 교육 프로그램 설계)

  • Ko, Seunghwan;Lee, Junho;Moon, Woojong;Kim, Jonghoon
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.7-11
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    • 2021
  • This study designs block-based machine learning education program using sound data that can be easily applied in elementary schools. The education program designed its goals and directions based on the results of a demand analysis conducted on 70 elementary school teachers in advance according to the ADDIE model. Scratch in Machine Learning for Kids was used for block-based programming, and the education program was designed to discover regularity of data values using sound data, learn the principles of artificial intelligence, and improve computational thinking in the programming process. In a later study, the education program needs to verify what changes there are in attitudes and computational thinking about artificial intelligence.

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