• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.497-507
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• 2012

This study aims to verify how the characteristics of organizational supporting unit affect the effectiveness of company-wide HRD Education & Training program. To achieve this objective, we performed an empirical analysis, with the characteristics of organizational supporting unit comprising supervisor's support, job support, and company support as independent variables, and with the level of reaction stage, learning stage, transfer stage, and result stage as dependent variables. Empirical data was collected during the period from August 16, 2011 to September 9, 2011 by sending out questionnaires to employees of 5 securities firms listed on KOSDAQ where online and offline education & training program is running year-round with headquarter in Seoul. A total of 340 questionnaires were sent out three times for the survey, and total of 164 questionnaires were sampled for the final analysis. According to the outcome of the analysis, regarding the first hypothesis that tries to reveal how the characteristics affect the level of reaction stage, it is verified that all of supervisor's support, job support and company support have positive impact on the level of reaction stage with p value less than 0.01. In regard to the second hypothesis that tries to see how the characteristics affect the level of learning stage, it is confirmed that supervisor's support, job support and company support have significant impact on the level of learning stage with p value less than 0.05 or 0.01, respectively. Concerning the third hypothesis that aims to investigate how the characteristics affect the level of transfer stage, it is appeared that all of supervisor's support, job support and company support have positive impact on the level of transfer stage. And lastly, as for the fourth hypothesis that tries to see how the characteristics affect the level of result stage, it is analyzed that supervisor's support, job support and company support have positive impact on the level of result stage with p value less than 0.01. This study reconfirm the outcomes of previous research, which is that the effectiveness of company-wide education & training program depends not only on the contents and quality of education & training program, but also more importantly on the role of organizational supporting unit, and the working environment where what is learned in classroom can be applied to real business. Companies or experts that run education & training program in real world should recognize that the performance of training is dependent more significantly on the characteristics of organizational supporting unit rather than the design or features of education & training program.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.111-111
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• 2020

하천환경과 기후의 변화로 인해 수질오염 과정의 메커니즘이 더욱 복잡해짐에 따라 다양한 요인을 고려한 불확실성 평가 연구가 요구되고 있다. 하천 수질 중에서도 부영양화 문제는 특히 개발로 인한 하천환경 변화 이후 사회 정치적 논점이 되어왔다. 본 연구에서는 지난 7년 동안의 수질 변화의 전반적인 양상을 조사하였으며, 클로로필-a(Chl-a, chlorophyll-a) 농도의 시공간적 의존성의 효과적으로 고려하기 위해 기계학습 기반 분류(classification) 접근법인 다변량 은닉 마코프 모형(MHMM, multivariate hidden Markov model)을 사용하였다. 월 단위 수질 및 수문 자료를 사용하여 Chl-a의 변동성을 군집화하여 수질 상태의 익월 천이확률을 효과적으로 추정하였다. Chl-a와 수질 및 수문기상 조건의 관계를 평가하였으며, 결과적으로 수질 상태의 시공간적 전이가 정확하게 식별되었고 이의 잠재적 원인에 대하여 논의하였다.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.203-210
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• 2017

In this paper, we propose an effective neural network model for image caption generation and model transfer. This model is a kind of multi-modal recurrent neural network models. It consists of five distinct layers: a convolution neural network layer for extracting visual information from images, an embedding layer for converting each word into a low dimensional feature, a recurrent neural network layer for learning caption sentence structure, and a multi-modal layer for combining visual and language information. In this model, the recurrent neural network layer is constructed by LSTM units, which are well known to be effective for learning and transferring sequence patterns. Moreover, this model has a unique structure in which the output of the convolution neural network layer is linked not only to the input of the initial state of the recurrent neural network layer but also to the input of the multimodal layer, in order to make use of visual information extracted from the image at each recurrent step for generating the corresponding textual caption. Through various comparative experiments using open data sets such as Flickr8k, Flickr30k, and MSCOCO, we demonstrated the proposed multimodal recurrent neural network model has high performance in terms of caption accuracy and model transfer effect.

• Journal of Engineering Education Research
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• v.12 no.4
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• pp.115-125
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• 2009

The purpose of this study was to suggest efficient method for development of learner's self-directed learning ability through literature review on self-directed learning, component of self-directed learning, development of self-directed learning ability, design education steps adopting problem based learning and project based learning. This study was conducted through literature review on self-directed learning and development of self-directed learning, design education. Design education and project based learning process and problem based learning to extract the items that are common to bring out five steps, and differences in levels of learners based on self-learning led to Grow(1991) model to connect the lessons of 9 steps present the design education steps, that is, the learners ready for learning, the definition of problem and recognition of necessity, team building, related data collection, team learning about real problem with the teacher, select optimal solution, student-centered discussion, models and product creation, testing and evaluation, complement.

• The Journal of Korean Association of Computer Education
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• v.20 no.6
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• pp.61-69
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• 2017

The Goal of SW education is to improve computational thinking. Especially, non computer majors need to apply computational thinking to their problem solving in their fields after computational thinking class. In this paper, we verified what factors affect the improvement of computational thinking through mixed research method after teaching computational thinking to non major students. Also, we analysed the characteristics of initial learning transfer of computational thinking, and establish the reason about he validity and justification for non major in SW education. The result shows learning satisfaction, learning transfer motivation, and self-CT efficacy affect the perception about improvement of computational thinking. Also, we found that there is application of computational thinking was coming up with problem solving process because the initial learning transfer process of computational thinking has characteristics about concepts and practices of it in programming steps. The effectiveness and learning transfer process of computational thinking for non majors will give the validity and justification to teach SW education for all students.

• School Mathematics
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• v.18 no.3
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• pp.441-455
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• 2016

The position as saying that the math learning needs to begin from what diversely presents concrete object or familiar situation is well known as a name dubbed CSA(Concrete-Semiconcrete-Abstract). Compared to this, a recent research by Kaminski, et al. asserts that learning an abstract concept first may be more effective in the aspect of knowledge transfer than learning a mathematical concept with concrete object of having various contexts. The purpose of this study was to analyze a class, which differently applied a guidance sequence of concrete object, semi-concrete object, and abstract concept in consideration of this conflicting perspective, and to confirm its educational implication. As a result of research, a class with the application of a concept starting from the concrete object showed what made it have positive attitude toward mathematics, but wasn't continued its effect, and didn't indicate significant difference even in achievement. Even a case of showing error was observed rather owing to the excessive concreteness that the concrete object has. This error wasn't found in a class that adopted a concept as semi-concrete object. This suggests that the semi-concrete object, which was thought a non-essential element, can be efficiently used in learning an abstract concept.

• Korean Journal of Cognitive Science
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• v.13 no.4
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• pp.9-21
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• 2002

Four experiments were conducted to examine whether maintaining the same conceptual context across study and test would affect performance on a perceptual implicit memory task. The sense-specific theory of priming (Lewandowsky et al., 1989) predicts greater priming from a match in conceptual context across study and test compared with a condition in which the conceptual context is mismatched, whereas the transfer-appropriate-processing view (e.g., Blaxton, 1989) predicts no difference. In experiment 1 and 2, little or no effect of varying context was observed on a implicit task. In experiment 3 and 4, a process-dissociation procedure (proposed by Jacoby, 1991) was used to separate automatic influences from consciously controlled influence in implicit memory, which was measured by Korean word completion task. The results showed that conceptual context effect was observed in consciously controlled parts of implicit memory. These results suggest that only consciously controlled processing parts of implicit memory is sensitive to conceptual context.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.83-83
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• 2017

수자원공학에서 일강수량 모의기법은 다양한 목적으로 활용되고 있지만, 일반적으로 홍수와 가뭄의 영향을 고려할 수 있는 수공구조물의 위험도 및 신뢰성 평가 및 수자원 계획을 수립하기 위한 입력 자료생성을 목적으로 활용된다. 유역 단위의 분석시 단일 지점에 대한 강수 모의 기법을 적용할 경우 각각의 지점에서 관측된 강수 자료의 시계열 및 통계치 특성이 효과적으로 재현되지만 공간적으로 발생하는 즉, 지점 간의 종속관계를 재현하지 못하는 문제가 발생한다. 이러한 이유로 공간적인 전이 특성이 있는 가뭄 분석 및 유역내 유출량의 공간적 변동 특성 분석에 단일지점별 모의 결과를 이용할 경우 관측 자료와 상반된 공간적 변동성으로 인하여 잘못된 가뭄 및 유출 분석 결과가 도출되는 문제점이 있다. 따라서, 실제적으로 발생하는 강수 특성을 반영한 유역 단위의 홍수 및 가뭄 등의 수문 분석을 위해서는 지점간의 종속성을 반영할 수 있는 다지점 강수 모의 모형의 적용이 필수적이다. 본 연구에서는 다지점 모의에 있어서, Wilks 모형의 지점별 시변동 특성과 공간상관성 재현 능력, HMM 모형이 갖는 강수 사상별로 분포된 양적 분포 패턴 재현 능력을 복합적으로 나타낼 수 있는 새로운 다지점 일강수량 모의 모형인 기계학습 기반 범주화 기법을 이용한 다지점 일강수량 모의 모형(ML-MRS)을 개발하였다. 또한, 지점별 강수량에 적용되는 확률분포모형은 Gamma 분포로 구성된 혼합모형을 적용하여 단일 확률 분포 모형의 자료 적합 문제를 개선하였다. 모의를 통한 일강수량 시계열 자료는 일 강수자료의 통계량을 효과적으로 모의하였으며, 다지점 모형의 모의 결과를 적용한 가뭄 모의 결과 관측 자료에서 나타나는 공간적 패턴이 재현되었다. 본 모형은 시 공간적 사상을 효과적으로 재현함으로서 지역의 변동특성을 반영한 가뭄, 홍수, 기상 현상 분석 등 활용도가 매우 높을 것으로 판단된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.217-218
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• 2023

인공지능은 디지털 대전환 시대의 핵심적인 기술로 사회 전반에 변화를 주도하였다. 우리나라는 인공지능을 이해하고 이를 활용하는 역량을 길러주기 위해 전 국민을 대상으로 교육을 진행하고 있다. 그러나 초등학생 대상 인공지능 교육 프로그램은 체험 및 놀이 실습으로 한정되어 교육적 효과에 한계가 있다. 그러므로 본 연구에서는 생산적 실패를 활용하여 인공지능에 대한 개념적 이해 및 실생활 전이를 촉진하는 교육 프로그램을 개발하였다. 연구 대상은 초등학교 5~6학년이며 2022 개정 교육과정에서 강조하는 자기 주도적 학습 역량과 실생활 연계 교육을 반영하여 설계한 6차시 분량의 프로그램이다. 본 연구에서 개발한 교육 프로그램은 향후 타당성 및 신뢰도 검증을 거쳐 현장에 적용하는 후속 연구로 이어질 것이다.

• Journal of The Korean Association For Science Education
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• v.24 no.5
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• pp.977-986
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• 2004

The purpose of this study was to investigate the general transfer effects of Thinking Science program on the problem solving with compensational reasoning of the elementary school students. For this study, 156 5th grade and 138 6th grade students were selected from four elementary schools. The students were tested with SRT(Science Reasoning Task) and compensational reasoning task. Statistically significant gains on the development of compensational reasoning were shown by the experimental group implemented with Thinking Science activities compared to the group implemented with compensation activity only. The achievement of the experimental group was higher than that of the compensation activity group in solving problem with compensational reasoning, specially for the boys and students in both the mature concrete and the concrete generalization stage. The results of this study implied that implementation of Thinking Science program related to several formal reasoning were effective for the development of reasoning ability as a general-transfer.