• Title/Summary/Keyword: Software curriculum

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Artificial Intelligence(AI) Fundamental Education Design for Non-major Humanities (비전공자 인문계열을 위한 인공지능(AI) 보편적 교육 설계)

  • Baek, Su-Jin;Shin, Yoon-Hee
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.285-293
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    • 2021
  • With the advent of the 4th Industrial Revolution, AI utilization capabilities are being emphasized in various industries, but AI education design and curriculum research as universal education is currently lacking. This study offers a design for universal AI education to further cultivate its use in universities. For the AI basic education design, a questionnaire was conducted for experts three times, and the reliability of the derived design contents was verified by reflecting the results. As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived were data structure understanding and processing, visualization, word cloud, public data utilization, and machine learning concept understanding and utilization. The educational design content derived through this study is expected to increase the value of competency-centered AI universal education in the future.

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.

A Study on the Possibility of Block-based Programming Courses for Visual Impairments (시각장애 학생을 위한 블록 기반 프로그래밍 수업의 가능성 분석)

  • Eunbong Yang;Jamee Kim;Wongyu Lee
    • Journal of The Korean Association of Information Education
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    • v.26 no.5
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    • pp.361-374
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    • 2022
  • The National Institute of Special Education developed and distributed software textbooks for disabled students according to the necessity of practical course in elementary school and information in middle school in the 2015 revised curriculum. It is a textbook provided from the perspective of education opportunity equity but the content of programming education for visually impaired students was insufficient. Therefore this study was conducted for the purpose of confirming the effectiveness of programming education for visual impaired students and providing the direction of future programming education. In order to achieve the purpose, programming classes were conducted for blind students in the 6th grade of elementary school. As a result of a study using "Blocks4All", a block-based programming tool with robots, students participated in classes actively and efficacy, intrest, and usefulness of programming are high. This study is meaningful in that it confirmed the possibility of programming education for visually impaired students.

Development of AI Education Program for Image Recognition for Low Grade Elementary School Students (초등학교 저학년을 위한 이미지 인식 이해 AI 교육 프로그램 개발)

  • Jeong, Lansu;Ma, Daisung
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.269-274
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    • 2021
  • With the development of artificial intelligence, society is moving to a different world. As a result, amid growing interest in artificial intelligence education, research on how to teach artificial intelligence is also being conducted more actively in Korea. However, a lot of research is being conducted around the upper grades of elementary school, and curriculum and programs for the lower grades are insufficient. Therefore, this study developed an artificial intelligence program for lower grades. Among them, it was developed focusing on artificial intelligence image recognition. It compares image recognition methods of people, animals, and computers, identifies the characteristics of fallen leaves, and helps them understand the image recognition process of artificial intelligence by classifying them according to the characteristics of fallen leaves. I hope this program will help elementary school students understand the image recognition principle of artificial intelligence in the future.

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4D AI Convergence Education Model (4차원 인공지능 융합 교육 모형)

  • Kim, Kapsu
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.349-354
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    • 2021
  • In this study, a model that can converge with artificial intelligence in each subject as software and artificial intelligence education become mandatory in the curriculum revised in 2022 is proposed. The proposed AI convergence education model is based on the content of the subject (accomplishment standard + subject). The second axis is artificial intelligence tools, the third axis is artificial intelligence technology, and the fourth axis is data applied in daily life. In order to apply artificial intelligence to each subject, it is necessary to apply artificial intelligence tools, artificial intelligence technology, and data in daily life to the achievement standards and content of each subject. If the achievement standards and subject contents are structured in this way, it can be seen that the convergence with each subject is good. Therefore, when composing textbooks by achievement standards and topics, it is necessary to add artificial intelligence tools, artificial intelligence technology, and daily data.

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A Study on Development of Basic Data Science Education Contents for Artificial Intelligence Capability (인공지능 기반의 기초 데이터 과학 교육에 관한 연구)

  • Jo, Junghee
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.393-400
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    • 2021
  • Data science is a scientific discipline that defines problems while finding meaningful information from collected data to solve problems. Along with artificial intelligence technology, the field of data utilization is gradually expanding, and awareness of the importance of data science education is also increasing. Despite the rapid growth of the domestic data industry market, it has recently been predicted that the shortfall of data experts will reach 31.4% within the next 5 years according to an analysis of the current status of the data industry by the Korea Data Agency. In the field of elementary education, various studies have been conducted to introduce data science in order to improve students' computational thinking and creativity. This paper proposed the contents of data science lectures developed for the purpose of educating elementary school teachers, who are mostly non-majors in the computer field. The developed contents were applied to a group of elementary school teachers attending graduate school for artificial intelligence convergence education. Points for improvement were derived by identifying the contents that were difficult for learners to understand and analyzing the causes of difficulty.

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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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An Analysis of Artificial Intelligence Education Research Trends Based on Topic Modeling

  • You-Jung Ko
    • 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.

Suggestion of Computational Thinking-Scientific Inquiry (CT-SI) Model through the Exploration of the Relationship Between Scientific Problem Solving Process and Computational Thinking (과학적 문제해결과정과 컴퓨팅 사고의 관련성 탐색을 통한 컴퓨팅 사고 기반 과학 탐구(CT-SI) 모형의 제안)

  • Hwang, Yohan;Mun, Kongju
    • Journal of Science Education
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    • v.44 no.1
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    • pp.92-111
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    • 2020
  • The 2015 revised science curriculum and NGSS (Next Generation Science Standard) suggest computational thinking as an inquiry skill or competency. Particularly, concern in computational thinking has increased since the Ministry of Education has required software education since 2014. However, there is still insufficient discussion on how to integrate computational thinking in science education. Therefore, this study aims to prepare a way to integrate computational thinking elements into scientific inquiry by analyzing the related literature. In order to achieve this goal, we summarized various definitions of the elements of computational thinking and analyzed general problem solving process and scientific inquiry process to develop and suggest the model. We also considered integrated problem solving cases from the computer science field and summarized the elements of the Computational Thinking-Scientific Inquiry (CT-SI) model. We asked scientists to explain their research process based on the elements. Based on these explanations from the scientists, we developed 'Problem-finding' CT-SI model and 'Problem solving' CT-SI model. These two models were reviewed by scientists. 'Problem-finding' model is relevant for selecting information and analyzing problems in the theoretical research. 'Problem solving' is suitable for engineering problem solving process using a general research process and engineering design. In addition, two teachers evaluated whether these models could be used in the secondary school curriculum. The models we developed in this study linked with the scientific inquiry and this will help enhance the practices of 'collecting, analyzing and interpreting data,' 'use of mathematical thinking and computer' suggested in the 2015 revised curriculum.

Research Trend Analysis of Publications in the Journal of Home Economics Education Association Using Network Text Analysis (네트워크 텍스트 분석을 이용한 한국가정과교육학회지 논문의 연구 동향 분석)

  • Lee, Yoon-Jung;Kim, Eun Jeung;Kim, Ji sun
    • Journal of Korean Home Economics Education Association
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    • v.31 no.4
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    • pp.1-18
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    • 2019
  • The purpose of this study was to analyze the research trend in home economics education using network text analysis method. The 586 research articles published in the Journal of Home Economics Education Association between July, 2003 and December 2018 were examined using Neckinger 4, a social network analysis software. The frequency and centrality measures(degree centrality, closeness centrality, and betweenness centrality) were calculated for the words appeared throughout the whole period, and the centrality analysis and LAD(Latent Dirichlet Allocation) were conducted for the four sub-periods. The results are as follows: first, the most frequently appeared words are parents, culture, unit, health, career, consumption, practicality, etc. The words such as parents and management scored high in degree centrality; parents and male students in closeness centrality; and male students and units in betweenness centrality. Second, when divided into four periods, the words such as education, family, purpose, class, middle school, and school appeared most frequently across the periods; but some words such as 'purpose' (in period 3 and 4), or 'process' (in period 4) were salient only in certain periods. Third, the words with high centrality were consistent regardless of the types of centrality within each period. Fourth, the topic analysis using LAD showed that curriculum, textbook, family healthiness, teaching-learning, evaluation, dietary life, appearance management, and consumption were the topics consistently appeared across all periods. The topics have become diversified and deepened. New topics such as teacher training and safety appeared in later periods, possibly due to the curriculum and national policy changes, and housing as a less represented topic is suggested as an area that needs further research attention. This study has implication in that it allows researchers to identify the major research interests and the trends in research by researchers in home economic education.