• Title/Summary/Keyword: 모델링/시뮬레이션

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Establishment of the Room Acoustic Criteria for the Korean Traditional Music Halls Using Subjective Listening Tests (청감실험에 의한 국악당의 음향설계조건 설정)

  • Haan, Chan-Hoon;Shin, Jic-Su
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.7
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    • pp.343-352
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    • 2007
  • The present study aims to investigate the design standard for acoustic criteria of Korean traditional music which could be used for the design of Korean traditional music halls. In order to do this, subjective listening tests were undertaken to musicians using auralized sounds which were convolved with the impulse response of traditional instruments recorded in an anechoic chamber. 94 pairs of sound were made which have different value of acoustic parameters including RT, BR, Brilliance, G, C80, ITDG, IACC. A paired comparison method(PCM) was used to analyze the results from the subjective listening tests. The results show that the preference of acoustic criteria for the Korean traditional music is far different from those of western music. As a result, specific range of acoustic criteria were suggested for the appropriate acoustic conditions of Korean traditional music. Also, a guideline of the acoustic design of halls for performing the Korean traditional music was suggested which could be used as a basic reference in the future works.

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.