• Title/Summary/Keyword: AI Curriculum

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A Study on the Composition of Factors in Teaching Competence Using Artificial Intelligence of Pre-service Early Childhood Teachers (예비 유아 교사들의 인공지능 활용 교육역량 요인 구성 연구)

  • Eunchul Lee
    • Journal of Christian Education in Korea
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    • v.72
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    • pp.183-203
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    • 2022
  • The purpose of this study is to construct factors of AI education utilization competency. AI education utilization competency is used as basic data for education to enhance the AI education competency of pre-service early childhood teachers. To this end, 7 studies related to competency factors and models were selected by searching for previous studies. Seven preceding studies were analyzed. As a result, 18 competency factors were extracted, including understanding of artificial intelligence. The extracted competency elements were divided into six areas, which are divided into understanding subject knowledge through coding, class preparation, class management, class result feedback, class guidance, and self-development. And 15 factors were constructed. The draft formed through coding was improved through review by three early childhood education experts. Factors improved through expert review were structured by classifying them into knowledge, skills, and attitudes to organize the curriculum. The validity of the structured competency factor was verified through expert Delphi. As a result of the Delphi verification, all factors were converged in the first survey. Through this, 6 competency areas, 11 competency factors, and 19 competency factors were composed of knowledge, 10 skills, and 5 attitudes. The implication is that the competency factors presented as a result of this study can be used as basic data for organizing a curriculum to improve the ability of pre-service early childhood teachers to use artificial intelligence education.

Analysis of Teacher Perceptions on Establishing Information Subjects in Elementary Schools (초등학교의 정보 교과 신설에 관한 교사 인식 분석)

  • Lee, Jaeho;Hur, Kyeong;Sohn, Wonsung;Kim, Kapsu;Kim, ChongWoo;Kim, Hongrae;Ma, DaiSung;Park, SunJu;Ann, SungHun
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.227-237
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    • 2021
  • In this thesis, a survey was conducted on elementary school teachers about the establishment of information subjects in elementary schools. As a result, the opinion that information subjects should be newly established for ICT literacy education and SW/AI education in elementary schools was very high. In addition, if it is difficult to establish a new information subject, opinions in favor of the organization of the information subject as an autonomous subject using the discretionary time of the principal were high. In light of the results of this analysis, it is judged that it is necessary to establish a new information subject for ICT literacy education and SW/AI education in the next elementary school curriculum. However, if it is difficult to establish a new information course, it is necessary to come up with a plan that can be operated in the form of autonomous subject for students wishing to learn SW/AI. And it is judged that the number of class hours should be secured for at least 1 hour or 2 hours per week in the 3rd grade and above.

Development of Test Tool of Attitude toward Artificial Intelligence for Middle School Students (중학생의 인공지능에 대한 태도 검사 도구 개발)

  • Kim, Seong-Won;Lee, Youngjun
    • The Journal of Korean Association of Computer Education
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    • v.23 no.3
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    • pp.17-30
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    • 2020
  • Although the importance of Artificial Intelligence(AI) education is increasing, research on the development of test tools has not been conducted in AI education research in Korea has not been conducted. Accordingly, there is a limit to designing AI curriculum and analyzing the effect of the educational program. So, in this study, Test tool was developed that to measure the attitude toward artificial intelligence of middle school students. For the development of test tools, the objectives, components, factors, and test tools were developed through the discussion of AI education experts. The test tool was finally developed by item analysis, exploratory factor analysis and confirmatory factor analysis. Finally, the criteria of the developed test tool were analyzed. Future research is needed to analyze the effects of educational programs and to analyze factors affecting attitudes toward artificial intelligence in middle school students using developed test tools.

Development and application of supervised learning-centered machine learning education program using micro:bit (마이크로비트를 활용한 지도학습 중심의 머신러닝 교육 프로그램의 개발과 적용)

  • Lee, Hyunguk;Yoo, Inhwan
    • Journal of The Korean Association of Information Education
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    • v.25 no.6
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    • pp.995-1003
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    • 2021
  • As the need for artificial intelligence (AI) education, which will become the core of the upcoming intelligent information society rises, the national level is also focusing attention by including artificial intelligence-related content in the curriculum. In this study, the PASPA education program was presented to enhance students' creative problem-solving ability in the process of solving problems in daily life through supervised machine learning. And Micro:bit, a physical computing tool, was used to enhance the learning effect. The teaching and learning process applied to the PASPA education program consists of five steps: Problem Recoginition, Argument, Setting data standard, Programming, Application and evaluation. As a result of applying this educational program to students, it was confirmed that the creative problem-solving ability improved, and it was confirmed that there was a significant difference in knowledge and thinking in specific areas and critical and logical thinking in detailed areas.

Methods to Use AI Programing in Environmental Education for Elementary School Curriculum (초등 환경교육에서 인공지능 프로그래밍 활용 방법)

  • Yong-Bae Lee
    • Journal of The Korean Association of Information Education
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    • v.26 no.5
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    • pp.407-416
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    • 2022
  • Although environmental education has been more important due to global extreme weather and natural desasters, environmental topics are covered by several other subjects because it is not an independent subject in elementary school and they need to distribute more class hours to cover proper amount of environmental content. This study is performed to develop method to integrate environmental education and software education in elementary school. This method helps students to learn topics about recycling by using Artificial Intelligence programming and Artificial Intelligence also helps students to practice recycling in virtual reality. A new teaching and learning module(Problem Recognition→Machine Learning↔Use of AI→Collaboration) is adopted for the learning procedure and more than 80 % of the students replied positively to the survey about the interest on integrated learning, understanding of environmental education, understanding of Artificial Intelligence, further learning on Artificial Intelligence programming.

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 the Use of Artificial Intelligence in a Problem-Based Learning Program for the Prevention of School Violence (학교폭력 예방을 위한 가정과 AI 기반 문제중심학습 수업 사례연구)

  • Jae Young Shim;Saeeun Choi
    • Human Ecology Research
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    • v.61 no.1
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    • pp.15-28
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    • 2023
  • The aim of this study was to develop, implement, and evaluate the use of Artificial Intelligence in the prevention of violence among middle-school students. The sample for this study consisted of 20 first-year middle-school students who participated in theme selection activities in a free semester program as part of their home economics studies. The data for the study consisted of nine class observation logs, four group activity outputs, 30 class results, an online survey, and in-depth interviews with three students. A program called "R.U.OK" was developed by setting problematic situation for school violence prevention linked to the contents of the Home Economics Education(HEE) curriculum. After the program was implemented, the survey on the students' class satisfaction content elements, with AI-based learning activities and PBL and interest, displayed high points, with an average of 4.0 or higher. Our qualitative analysis produced four significant results. First, students' concerns about school violence had increased and they showed a change in attitude, having more empathy with friends and more interest in their surroundings. Second, digital and AI literacy had improved, and students' interest in digital media learning had increased. Third, there had been an improvement in problem-solving ability in terms of being able to think more critically and independently. Fourth, the results also demonstrated that there had been a positive effect on self-direction and an improved capacity for teamwork. This study was significant in demonstrating the effectiveness of a program for the prevention of school violence based on the use of digital technology in the educational environment.

Trend of ICT Education in Korea and Analysis of Overseas Cases (국내 ICT 교육 동향 및 해외 사례 분석)

  • Woo, Seokjun;Koo, Dukhoi
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.261-267
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    • 2021
  • This study examines the purpose and goals of ICT education, compares them with current software and artificial intelligence-oriented information curriculum, analyzes foreign SW curriculum, extracts learning topics and elements, and analyzes whether the current information curriculum is presented effectively. As a result of the analysis, the number of information-related courses in Korea is currently lower than in other countries, which has reduced the number of basic computer applications and underlying software applications such as presentations and spreadsheets covered in ICT training in the past. In addition, compared to Korea's curriculum where information education begins in the fifth grade of elementary school, other countries are introducing information education from the first grade to the third grade of elementary school. Therefore, active discussions on the expansion of the number of information education, the timing of introduction of information education, and the utilization of basic computers are needed.

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Analyzes the Changes in the Curricula of Computer and Software-Related Majors in Line with the Fourth Industrial Revolution, Comparing the Periods Before and After the COVID-19 Pandemic in KOREA. (코로나19 펜데믹 전후 컴퓨터 및 소프트웨어 관련 전공의 제4차 산업혁명중심 교과과정 변화 분석)

  • Jin-Il Choi;Chul-Jae Choi
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.3
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    • pp.625-632
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    • 2024
  • This paper analyzed the changes in the curriculum of computer and software-related majors that educate the core ICT technologies needed for the 4th Industrial Revolution, before and after the COVID-19 pandemic. According to the standard classification of university education units, 172 majors classified into Applied Software Engineering, Computer Science·Computer Engineering, and Artificial Intelligence Engineering were targeted, and the curricula of 2023 and 2019 were compared and analyzed. As a result of the analysis, the introduction of the related curriculum for each curriculum group increased by about 2.6%p before and after the COVID-19 pandemic (2023 84.2%, 2019 81.6%). and the 4th Industrial Revolution response index increased by 9.5 points (37.0 in 2023, 27.5 in 2019)

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.