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우미라 학습자중심교과교육학회 2006 학습자중심교과교육연구 Vol.6 No.1
본 연구는 뇌 기반 초등문학교육의 원리를 바탕으로 초등문학교육에 적용할 교육연극 방법의 준거를 제시하고, 준거에 따른 방법을 소개하는 데 그 목적이 있다. 먼저 뇌의 학습 기제와 초등문학교육의 원리를 살펴보고, 초등문학교육에 적용할 교육연극 방법을 제시하였다. 교육연극 방법의 준거로 풍부한 경험을 통한 총체적 인식력의 제고, 다양한 체험을 통한 의미 구성력 신장, 발달 특성에 따른 자발적 참여 확대, 허용적 분위기를 통한 내적 동기 유발, 의미 협상을 통한 문학적 체험 공유를 제시하였으며, 구체적인 방법은 놀이, 즉흥극, 역할극으로 범주화하였다. 이 방법들은 배타적이 아니라 서로 겹치거나 포괄적으로 활용될 수 있으며, 교사의 창의적인 생각에 따라 개발될 수 있다. 앞으로 많은 교육연극 방법들이 개발되어 수업에 적용되기를 기대한다. This study purposed to suggest grounds for educational drama methods to be applied to elementary literature education based on the principle of brain‐based elementary literature education, and explain approaches according to the ground. To begin with, we examined the brain‐based learning mechanism and the principles of elementary literature education, and suggested educational drama methods to be applied to elementary literature education. As grounds for educational drama methods, we suggested the improvement of holistic cognitive power for rich experience, the enhancement of meaning composition ability through various experiences, the expansion of voluntary participation according to developmental characteristics, the induction of internal motives through permissive atmosphere, and the sharing of cultural experiences through the negotiation of meanings. In addition, specific methods were categorized into play, improvisation and role play. These methods are not exclusive to one another, but can be used in an overlapped or comprehensive way and developed from the teacher’s creative idea. The author expects that many educational drama methods are developed and applied to teaching in school.
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신체활동을 통한 수학프로그램이 유아의 수학적 문제해결력에 미치는 영향
우미지 ( Mi Ji Woo ),신인숙 ( In Sook Shin ) 미래유아교육학회 2010 미래유아교육학회지 Vol.17 No.1
이 연구의 목적은 신체활동을 통한 수학프로그램이 유아의 수학적 문제해결력에 미치는 영향을 조사하는 것이었다. 이들 능력에 대한 연구는 분류, 패턴, 수, 측정, 도형 및 통계의 여섯 가지 영역에 근거하였다. 이 연구에서 실험집단으로서 대구시에 소재하는 J어린이집 만 4세 유아 24명이 9주 동안 한 주에 30분간 2회에 걸쳐 신체활동을 통한 수확프로그램을 실시하였다. 동시에 비교집단으로 대구시에 소재한 K어린이집의 만 4세 유아 24명은 표준보육과정에 근거한 정규수업을 하였다. 두 집단은 위에서 기술한 여섯 가지 영역에 대한 그들의 수학적 능력을 조사하기 위해 사전, 사후 검사를 받았다. 이 자료를 공분산분석 하였다. 그 결과로서, 실험집단의 여섯 영역의 합한 성적은 비교집단의 성적보다 유의미하게 높았다. 구체적으로 두 집단 간에 분류, 패턴, 수, 도형 및 통계의 점수에서 유의미한 차이가 있었다. 그러나 두 집단 간 측정 점수에서는 유의미한 차이가 없었다. 따라서 이들 결과는 이 수학프로그램이 유아들의 다섯 가지 영역의 수학해결력을 발전시키는데 유용하다는 것을 시사한다. The purpose of this study was to investigate how mathematical programs using physical activities affect children`s mathematical problem-solving abilities. This study was based on the six categories of classification, pattern, number, measurement, shape, and statistics. In this study, 24 four-year-old children in a child care center in Daegu as an experimental group were trained two times a week for 30 minutes over a nine week period by mathematical activities using physical activities. At the same time 24 four-year-old children in another child care center in Daegu as a comparison group had only regular classes. Both group were given a pre-test and post-test to check their abilities in the six categories listed above. Data of the tests were analyzed by ANCOVA. The results showed that the total score of the six categories for the experimental group was significantly higher than that for the comparison group. In detail, there were significant differences in the scores of classification, pattern, number, shape and statistics between the two groups. However, there was no significant difference in the score of measurement between the two groups. Therefore, these results indicate that the mathematical programs are useful in developing children`s mathematical problem-solving abilities of the five categories.
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빅데이터를 활용한 도시 브랜드 이미지 분석과 응용 해석
우미나 한국IT서비스학회 2018 한국IT서비스학회지 Vol.17 No.1
The city image is considered one of important symbolic and important factors in selecting the travel destination. Many cities are trying to be an attractive and popular city to tourists through the construction of a good brand image by utilizing their representative characteristics. This study measures the city brand image by applying a big data analytic method. In addition, the big data measurement results were rearranged and analyzed to identify further detailed city images by utilizing several previous interpretation methods. Our study has chosen Dubai since this city has the diverse images due to its regional as well as economic characteristics. In particular, nowadays Dubai has been recognized as one of the most important touristic places in the Middle East region for its modern and innovative images in spite of the limitations of location, weather, religion, and even political issues of neighbor countries. Founded on a big data analysis rather than a questionnaire-based survey, the presented interpretation methods are evaluated to improve the understanding of Dubai’s diverse city images. In addition, based on the results of this research, it is expected to have a practical impact on establishing the effective marketing strategies to build and implement the valuable city brand image.
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우미나(Mi na Woo) 한국IT서비스학회 2018 한국IT서비스학회지 Vol.17 No.3
There exist a number of studies pertaining to the determinants of customer satisfaction between low-cost and full-service carriers in the airline industry. Most studies measured service quality using SERVQUAL based on a survey method. This study offers a new perspective by employing a big data analytic approach using SNS data, which reflects the immediate response of customers as well as trends in real time. This study chose eight factors from TripAdvisor’s customer review site as determinants of customer satisfaction and compared the differences between low-cost and full-service airlines. The factors analyzed were seat comfort, customer service, cleanliness, food and beverage, legroom, entertainment, value for money, and check-in and boarding. Additionally, ratings from domestic and foreign customers were compared. The findings show that customer service and value for money are significant factors in satisfaction with low-cost airlines while all variables except legroom and entertainment are significant for full-service airlines. The results show that SNS-based data and analysis of big data are important for improving decision-making effectiveness and increasing customer satisfaction in the airline industry.
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