• 아동학회지
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• 제32권1호
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• pp.87-101
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• 2011

This study employed a child-centered approach in the examination of patterns of preschooler's learning behaviors. A hierarchical cluster analysis was employed in order to discern a meaningful typology of such behavior. The subjects consisted of 232 children (117 boys, 106 girls) and their mothers from 6 kindergartens and 6 day care centers. The results of this study were as follows. The cluster analysis yielded five types of learning behaviors; the competent type, the average type, the low attention/persistence type, the low motivation -attitude type, and the deficient type. The most consistent level differences among these types appeared to lie in distinctions among the average Attention/Persistence scores. The composition of the cluster types, including both the age and gender of the children, was ascertained. Our results indicated that preschool learning behavior types could be seen to differentially relate to children's self-regulation, cognitive styles, problem behaviors, and the level of maternal involvement. It was revealed that a child's characteristics was more important than maternal involvement and beliefs. As there were more girls and older children in the learning type, this type was seen to be more competent.

• Human Ecology Research
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• 제55권5호
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• pp.527-538
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• 2017

This study examines the effects of university students' types of self-determination and academic emotions on their learning community participant competence. The subjects were 234 early-childhood preservice teachers attending a university or college in the Kyonggi and Incheon area of Korea. The first metric created by Bak et al. (2005) measured early-childhood preservice teachers' types of self-determination. The second metric developed by Kim & Kim (2016) measured their levels of learning community participant competence. The thirds metric, originally developed by Kim (2012) and So (2010), was modified by Chung (2015) to measure the academic emotions of subjects. The test results were analyzed by correlation and multi-regression techniques using SPSS 21 for Windows. The findings were as follows. First, there were significant relationships between the subjects' types of self-determination and the levels of learning community participant competence. Second, there were significant relationships between the subjects' academic positive and negative emotions and the levels of learning community participant competence. Third, the subjects' levels of learning community participant competence were perceived differently according to their academic emotions. Based on these results, implications pertaining to academic emotions on learning community participant competence are suggested.

• 한국수학사학회지
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• 제18권2호
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• pp.55-74
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• 2005

본 논문은 수학 교육방법 개선을 위한 노력의 하나로 학습 모델에 대하여 연구하였다. 그 중 특히 협동학습 유형을 역사적으로 종합 정리하고 협동학습의 이론적 배경과 소집단 협동학습의 필요성 그리고 협동학습과 전통 조별학습의 차이점 등을 조사하였다. 또한 협동학습에서 나타나는 특징과 다양한 협동학습의 유형을 제시하고 그 효과에 대하여 연구를 하였다. 본 연구에서는 역사적으로 수학교육학적 견지에서 의미 있는 협동학습 유형으로 팀보조개별학습(TAI: Team-Assisted Individualization), 직소우(JIGSAW) 협동 학습, 직소우II(JIGSAW II) 협동 학습, 직소우III(JIGSAW III) 협동 학습, STAD(Student Team-Achievement division) 협동학습, 팀경쟁 협동학습(TGT: Teams-Games-Tournament) 등을 집중적으로 연구하였다.

• Educational Technology International
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• 제19권1호
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• pp.35-60
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• 2018

The purpose of this study was to analyze the types of lesson and its effectiveness with digital textbook. To address those goals, we had observed five classes of the primary school, which designated as a research pilot school for digital textbook. Based on the result of observation, 3 types of lesson with digital textbook were categorized: Teacher-directed lecture (type 1), Blended learning (type 2), and Flipped learning (type 3). Depending on the type of lesson was analyzed the positive and negative effectiveness by means of matrix analysis method. As a result, in Teacher-directed lecture (type 1), there was found out the participation of the lesson in atmosphere of stable and comfortable as positive experience, also digital textbook operating immature and boring as negative experience. In Blended learning (type 2), there was found out the fun by sharing the product and peer feedback, and flow by learning transfer as positive experience, also digital textbook operating immature and understanding the difference between assignments as negative experience. In Flipped learning (type 3), there was shown the positive attitude and ownership in the lesson as positive experience, also distracting and boring in the lesson when learner was excluded in participation as negative experience. Based on the results, we suggested some strategies for improving positive experience and protecting negative experience in the lesson with using digital textbook.

• 대한원격탐사학회지
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• 제39권5_1호
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• pp.507-519
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• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• The Journal of Asian Finance, Economics and Business
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• 제6권1호
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• pp.205-215
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• 2019

Researchers have confirmed the relationship between ambidexterity learning and innovation performance, but according to the resource-based theory, the relationship between ambidexterity learning and innovation performance is also affected by the internal resources of the organization. Internal resources are an important factor affecting the transformation of learning outcomes into performance. In addition, few scholars have pointed out whether different types of learning have different effects on different types of innovation performance. This study collects data from 170 High-tech enterprises in Shandong, china, and discusses the effects of exploitative learning and explorative learning on management innovation performance and technological innovation performance. This study further examines the moderating role of slack resource on the relationship between ambidexterity learning and innovation performance. Results show that ambidexterity learning has positive effect on innovation performance. Compared with exploitative learning, explorative learning has a greater impact on management innovation performance; compared with explorative learning, exploitative learning has a greater impact on technological innovation performances. Slack resource has positive moderating role between the relationship of exploitative learning, explorative learning and technology innovation performance. But Slack resource has no moderating role between the relationship of exploitative learning, explorative learning and management innovation performance.

• 대한수학교육학회지:학교수학
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• 제5권2호
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• pp.191-208
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• 2003

본 연구는 수학 및 과학 영재 아동과 일반 아동의 성격유형과 학습양식의 차이를 알아보는 것을 목적으로 하였다. 이를 위해 수학 및 과학 영재교육을 받고 있는 부산광역시 소재의 초등학교 5, 6학년 135명과 일반아동 66명을 대상으로 하여 MMTIC과 학습양식검사를 실시하였다. 성격유형의 분석은 선호지표와 기능별, 기질별 분포를 중심으로 하였고, 학습양식은 독립형, 의존형, 협동형, 경쟁형, 참여형, 회피형의 유형으로 분류되었다. 연구결과에 의하면, 수학 및 과학 영재 아동은 성격유형, 학습양식 그리고 성격유형에 따른 학습양식에서 큰 차이가 없었으나, 일반 아동과는 유의한 차이를 나타냈다. 또한 연구대상의 성격유형에 따라 선호하는 학습양식에는 차이가 있는 것으로 나타났다.

• 디지털융복합연구
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• 제16권10호
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• pp.205-212
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• 2018

고성능 CPU/GPU의 개발과 심층신경망 등의 인공지능 알고리즘, 그리고 다량의 데이터 확보를 통해 기계학습이 다양한 응용 분야로 확대 적용되고 있다. 특히, 사물인터넷, 사회관계망서비스, 웹페이지, 공공데이터로부터 수집된 다량의 데이터들이 기계학습의 활용에 가속화를 가하고 있다. 기계학습을 위한 학습 데이터세트는 응용 분야와 데이터 종류에 따라 다양한 형식으로 존재하고 있어 효과적으로 데이터를 처리하고 기계학습에 적용하기에 어려움이 따른다. 이에 본 논문은 표준화된 절차에 따라 기계학습을 위한 학습 데이터세트를 구축하기 위한 방안을 연구하였다. 먼저 학습 데이터세트가 갖추어야할 요구사항을 문제 유형과 데이터 유형별로 분석하였다. 이를 토대로 기계학습 활용을 위한 학습 데이터세트 구축에 관한 참조모델을 제안하였다. 또한 학습 데이터세트 구축 참조모델을 국제 표준으로 개발하기 위해 대상 표준화 기구의 선정 및 표준화 전략을 제시하였다.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제34권3호
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• pp.299-324
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• 2020

본 연구에서는 고등학생들의 수학 학습양식, 성격기질별 특징을 확인하고 각 성격기질별로 수학학습 전략을 제시하고자 하였다. 이를 위해, 375명의 고등학교 1학년 학생들을 대상으로 MBTI 성격유형 검사, 수학학습 선호도 조사를 실시하여 그 결과를 분석하였다. 이 연구의 결과는 다음과 같다. 첫째, 많은 학생들이 사교육의 효과를 높게 평가하고 교과서보다는 참고서를 활용한 수학학습을 더 선호하였다. 둘째, 학습 태도, 학습 습관(개념이해 집중도), 문제해결 전략(문제이해 노력, 다양한 전략 사용), 자기 관리(메타인지) 영역에서 성격기질에 따라 통계적으로 유의미한 차이가 확인되었다. 셋째, SJ형 학생들은 마인드맵 등의 학습 전략, SP형 학생들은 장,단기 학습목표를 꾸준히 실천하는 전략이 필요하다. NT형 학생들은 SRN(자기성찰노트)이나 수학일지를 활용한 학습 전략, NF형 학생들은 논리적 근거를 제시하는 수학학습 노트 쓰기 활동과 대수 학습에 더 많은 시간 투자가 필요하다.

• 컴퓨터교육학회논문지
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• 제16권6호
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• pp.71-81
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• 2013

본 연구는 온라인 학습에서 콘텐츠의 제시유형과 제시수준, 그리고 학습자의 메타인지가 학습에 미치는 영향을 살펴보고자 실시되었다. 이를 위해 온라인 학습 콘텐츠의 제시유형과 제시수준, 그리고 학습자의 메타인지에 따른 개념도 형성과 학습 과정을 살펴보았다. 온라인 학습 콘텐츠의 제시유형은 의미중심형과 맥락중심형으로, 제시수준은 기본형과 결핍형으로 구분하여 제공하였고, 학습자의 메타인지는 검사결과에 따라 상하 두 집단으로 구분하였다. 연구결과는 콘텐츠의 제시유형에서 의미중심형(M=45.00, SE=1.97)이 맥락중심형(M=34.71, SE=1.98)보다 더 높은 개념도 형성을 보였다. 콘텐츠의 제시수준별 집단간(F=.002, p>.05), 메타인지 상하 집단간에는 의의 있는 차이가 없었다. 그러나 제시수준과 메타인지 사이에 상호작용(F=6.225, p<.05) 효과가 있어 메타인지 상집단은 결핍형에서, 하집단은 기본형에서 보다 높은 개념도 형성을 보였다. 또한 온라인 학습 과정 분석을 통해 학습자의 메타인지가 콘텐츠의 결점과 결핍을 보완하여 학습을 실행하게 하는 중요요인임을 확인할 수 있었다.