• Title/Summary/Keyword: 유아 다중지능

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The Development and Validation of a Children's Play Disposition Scale (아동 놀이성향척도 개발 및 타당화 연구)

  • Sung, Jihyun;Byun, Hye-weon;Nam, Ji-hae
    • The Journal of the Korea Contents Association
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    • v.17 no.4
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    • pp.606-620
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    • 2017
  • The purpose of this study was to develop and validate a Children's Play Disposition Scale(CPDS) which could be used to evaluate children's play patterns and preferences. The participants of this study were parents of 437 5-7-year-old children (age range from 51months to 106months). Preliminary items were developed through a review of relevant research, multiple intelligence theory and scales, confirmation of item adequacy and content validity. After the content validity was confirmed by experts, these items were edited down to a final list of 27 items representing 6 factors identified by exploratory factor analysis. The 6 factors of the scale consists of initiative, linguistic activity, logical-mathematical activity, art and craft, physical activity, and sensitivity respectively. Concurrent validity was established by using correlations between each factor of the CPDS and sub-factors and the total scores of Multiple Intelligence Checklist for preschoolers (Multiple Intelligence Institute Co., Ltd, 2008) and Multiple Intelligence Checklist for elementary schoolers (Multiple Intelligence Institute Co., Ltd, 2007). In addition, the reliability of each factor, as measured by Cronbach's ${\alpha}$, ranged from .53 to .79. The CPDS provides the developmental and educational information for strengthening children's developmental forte and for supporting children's developmental weakness. This scale can be used on developing children's play contents and guiding play methods in the future.

The relationship between children's creativity, playfulness and multiple intelligence (유아의 창의성과 놀이성, 다중지능과의 관계)

  • Lim, Young-Ok;Yee, Young-Hwan;Oh, Ka-Young
    • Korean Journal of Human Ecology
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    • v.9 no.1
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    • pp.15-24
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    • 2006
  • The early childhood is a pivotal period for the development of creativity since creative imaginary is rich at the age from 4 to 4.5 years old, The purpose of this study is to examine the relationships between children's creativity, playfulness and multiple intelligence. 91 children(41 boy, 50 girls) attending preschool in jeon-ju city were participated in this research, The age of children was 6 years(average 73.7 months), After collecting the data to find the connections between children's creativity, playfulness and multiple intelligence from the subjects' data using the SPSS WIN 10.0 program, along with t-test, ANOVA and Pearson's correlation in this paper. 1. There was significant correlation between children's playfulness and creativity. Intelligence spontaneousness the element of the playfulness has a correlation with Creativity strengths, Elaboration. In addition, Resistance to Premature Closure has a correlation with social spontaneity, And Originality has a correlation with the Expression of Pleasure the element of the playfulness, 2. There was a significant positive correlation between children's multiple intelligence(MI) and creativity, Fluency the element of creativity has a correlation with Interpersonal intelligence the element of multiple intelligence: And Originality has a correlation with Bodily-kinesthetic intelligence, Intrapersonal intelligence the element of MI. In addition, Abstraction of Titles has a correlation with Intrapersonal intelligence. 3. There was a little correlation between children's MI and playfulness. The Expression of Pleasure has a correlation with bodily-kinesthetic intelligence, Based on the current study, the relationships between creativity, playfulness, and multiple intelligence could be identified. Especially, creativity was significantly correlated with playfulness and multiple intelligence of early childhood. Therefore, it was found that creativity of toddler might be essential factor for the development of toddler's cognitivity.

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The Study of the System Development on the Safe Environment of Children's Smartphone Use and Contents Recommendations (유아들의 안전한 스마트폰 사용 환경 및 콘텐츠 추천 시스템 개발)

  • Lee, Kyung-A;Park, Eun-Young
    • Journal of Digital Contents Society
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    • v.19 no.5
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    • pp.845-852
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    • 2018
  • This study has developed a preventive launcher from smartphone addiction for the digital generation and the contents recommendation based on machine learning which used multiple and collective intelligence. This could provide convenient digital nurturing experience for the parents who fear their children's over use of digital devices and also suggest individually adaptive digital learning methods that enhance the learning efficiency and pleasurable and safe learning environment for the children. Suggested application is a kind of gamification launcher that protects children from harmful contents and from smartphone addiction with time limit settings. For parents who find difficulty choosing from various kinds of contents and applications for education, this suggested system could provide a learning analytic report based on big data after collecting and analyzing the data of their children's learning and activities and recommend contents necessary for their kids using recommended algorithm by collective intelligence.

A Study on a Mask R-CNN-Based Diagnostic System Measuring DDH Angles on Ultrasound Scans (다중 트레이닝 기법을 이용한 MASK R-CNN의 초음파 DDH 각도 측정 진단 시스템 연구)

  • Hwang, Seok-Min;Lee, Si-Wook;Lee, Jong-Ha
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.4
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    • pp.183-194
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    • 2020
  • Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room