• Title/Summary/Keyword: Artificial Intelligence Gifted

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Analysis of Research Trends in Elementary Information Education in Korea using Topic Modeling (토픽 모델링을 활용한 국내 초등 정보교육 연구동향 분석)

  • Shim, Jaekwoun
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.347-354
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    • 2021
  • As interest in artificial intelligence education for elementary school students has recently increased, it is necessary to analyze the existing elementary information education research from a macroscopic point of view to understand the current situation and to provide implications for subsequent research. This study analyzed Journal of The Korean Association of Information Education for the purpose of looking at the research trend of elementary information education in Korea. For the data of the study, all papers published until 2020 in the first issue of the journal were selected, and 11 research topics were derived by modeling topics. As a result of the study, topic T1, the highest proportion, was analyzed to account for about 38%, and keywords such as education, research, analysis, elementary school, and information were derived according to the order of contribution to topic T1. As a result of regression analysis according to the year of the topic, it was found that the research trend is changing to computing thinking, software education, and artificial intelligence education. The significance of this study is that text data related to elementary information education is objectively clustered.

Exploring Data Categories and Algorithm Types for Elementary AI Education (초등 인공지능 교육을 위한 데이터 범주와 알고리즘 종류 탐색)

  • Shim, Jaekwoun
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.167-173
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    • 2021
  • The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.

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