• 공학교육연구
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• 제19권2호
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• pp.76-82
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• 2016

The purpose of this study is to identify core elements required of instruction consulting and to develop a systematic consulting procedure for successful Flipped Learning. The main contents of this study to achieve its purpose are as follows. First, core elements required of consulting are deduced by analyzing cases of instruction implemented with Flipped Learning. Second, consulting procedure is constructed based on core consulting elements of Flipped Learning. Based on the study results, the 3P process is suggested as the elements and procedure of instruction consulting for Flipped Learning. The 3P process has the following characteristics. The first stage Preparation involves guiding students to have an objective viewpoint about the lesson beginning with building a relationship with the instructor. Also, a lesson plan and source materials for lesson are selected and developed. The second stage Performance involves implementing lesson coaching oriented towards cooperative problem-solving to find better direction. The last stage Post-review involves introspection necessary for continuous quality improvement of lessons. The validity of the instruction consulting elements for Flipped Learning applied to deduce the aforementioned results has been verified after specialist review and field application.

• 한국보육지원학회지
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• 제17권1호
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• pp.1-18
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• 2021

Objective: The researchers aimed to explore the 'what' and the 'how' of childcare consulting. This study was focused on finding out how child care teachers perceived the process of implementing childcare consulting and their thoughts about the transformation of childcare consulting based on their participating experience. Methods: This study was based on the transverse-continuous design using qualitative research methodology. The participants were eight experienced childcare teachers that were childcare consulting in 2015 or 2020. The data were collected through in-depth interviews. Results: The main findings in exploring meanings and implications of childcare consulting were as follows. First, childcare consulting was recognized as a process of learning about changes through mutual relationships. Second, the different ways to practice childcare consulting, the formation of the learning culture of an organization to help experience collective intelligence, the process of finding various solutions through mutual communication, and the improvement of childcare teachers' professional capabilities while reflecting the current times and context were all investigated. Conclusion/Implications: Given the findings of the study, the importance of childcare consulting, and the ways to establish its systems were discussed.

• 교육심리연구
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• 제32권1호
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• pp.1-27
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• 2018

본 연구의 목적은 창의적 문제해결(CPS) 기반으로 대학생을 위한 학습컨설팅 모형을 개발하고 나아가 이의 실증적 효과를 검증하는 것이었다. 창의적 문제해결 기반 학습컨설팅 모형은 ADDIE 모형에 근거하여 개발하였다. 분석과정에서 컨설팅 과정과 내용 영역을 확인하여 구성요소를 추출하고, 설계과정에서는 모형의 목적에 적합한 컨설팅 과정과 세부내용을 구체화하였다. 개발과정에서는 구체화된 내용으로 창의적 문제해결 기반 학습컨설팅 주요과정과 세부과정 및 주요활동을 구조화하였다. 그리고 실행과정에서는 개발된 모형을 대학생 15명에게 적용하여 모형의 효과성을 확인하였다. 마지막으로 평가과정에서는 학습컨설팅전문가 4명을 포커스 그룹으로 구성하여 인터뷰 한 다음 모형 타당도 검증을 거쳐 최종모형을 개발하였다. 그리고 최종모형을 대학생 20명에게 적용한 결과 자기주도학습능력과 창의적 문제해결능력이 통제집단에 비해 향상되었음을 확인하였다. 이러한 결과를 토대로 창의적 문제해결 기반 학습컨설팅 모형 개발 및 활용에 대한 시사점과 제한점을 논의하였다.

• 산업경영시스템학회지
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• 제45권4호
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• pp.86-98
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• 2022

Recently, many studies have been conducted to improve quality by applying machine learning models to semiconductor manufacturing process data. However, in the semiconductor manufacturing process, the ratio of good products is much higher than that of defective products, so the problem of data imbalance is serious in terms of machine learning. In addition, since the number of features of data used in machine learning is very large, it is very important to perform machine learning by extracting only important features from among them to increase accuracy and utilization. This study proposes an anomaly detection methodology that can learn excellently despite data imbalance and high-dimensional characteristics of semiconductor process data. The anomaly detection methodology applies the LIME algorithm after applying the SMOTE method and the RFECV method. The proposed methodology analyzes the classification result of the anomaly classification model, detects the cause of the anomaly, and derives a semiconductor process requiring action. The proposed methodology confirmed applicability and feasibility through application of cases.

• 한국보육지원학회지
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• 제17권2호
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• pp.29-46
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• 2021

Objective: The purpose of this study is to examine young children's social experiences during COVID-19. In this study, social experiences are defined as children's social interactions and relationships, their educational experiences, and their daily life experiences in child care centers. Methods: Participants include nine child care teachers and fifteen young children. Data were collected through semi-structured interviews with individual teachers, interviews with young children, and small group storytelling activities with young children. Results: The main findings in exploring meanings and implications of childcare consulting were as follows. First, childcare consulting was recognized as a process of learning about changes through mutual relationships. Second, the different ways to practice childcare consulting, the formation of the learning culture of an organization to help experience collective intelligence, the process of finding various solutions through mutual communication, and the improvement of childcare teachers' professional capabilities while reflecting the current times and context were all investigated. Conclusion/Implications: Given the findings of the study, the importance of childcare consulting, and the ways to establish its systems were discussed.

• 산업경영시스템학회지
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• 제36권2호
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• pp.49-55
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• 2013

When developing a product, ensuring the quality and reliability is essential. Reliability process is always underestimated compared to its importance, especially in the field of domestic medical devices. In this paper, reliability process developed for near-infrared solid microscope, based on a variety of existing practices and other product process. The following findings were obtained as research progressed. First, learning about the medical equipment needed to assure the quality and reliability standards. Second, reliability process established to design a product in the field of medical devices.

• Industrial Engineering and Management Systems
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• 제2권1호
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• pp.45-54
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• 2003

Enterprise Resource Planning(ERP) systems offer pervasive business functionality the applications encompass virtually all aspects of the business. Understanding and managing this pervasiveness will result in a successful and productive business application platform. Because of this pervasiveness, implementations have ranged from great successes to complete failures. This article has two distinctive parts. The first proposes and discusses a systematic process based on consulting experiences of LG CNS (leading information system company in Korea) for ERP selection. Also, the second provides the key factors that are critical to the successful implementation of ERP. The second part reports the results of a study carried out to assess a number of different ERP implementations in different organizations. A case study method of investigation was used, and the experiences of five Korean manufacturing companies were documented. The critical factors in the adoption of ERP are identified as: learning from the experiences of others, appointment of a process innovator, establishment of committees and project teams, training and technical support for the users, and appropriate changes to the organizational structure and managerial responsibilities.

• 한국콘텐츠학회논문지
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• 제14권4호
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• pp.425-434
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• 2014

이 연구는 학교경영컨설팅을 수행하는 컨설턴트가 갖추어야 하는 역량에 대하여 전문가와 예비컨설턴트의 인식을 중심으로 분석함으로써 학교경영컨설턴트의 역량 강화와 학교컨설팅 연구에 대한 시사점을 도출하고자 수행되었다. 이러한 연구 목적을 달성하기 위하여 전문가와 예비컨설턴트를 대상으로 역량 중요도와 역량 보유도를 조사하였다. 연구 결과, 학교경영컨설턴트가 갖추어야 하는 주요 역량은 '학교경영컨설팅의 배경 개념 원리', '학교경영컨설팅의 과정방법', '학교경영의 내용', '경청과 공감', '의사소통', '문제해결', '팀워크와 협력', '대인관계', '진정성', '헌신'으로 분석되었다. 전문가와 예비컨설턴트가 인식하는 학교 경영컨설턴트 역량의 중요도 인식에는 차이가 있었고, 예비컨설턴트가 인식하는 학교경영컨설턴트 역량의 중요도와 보유도는 컨설팅 경험을 통하여 변화를 보였다. 이 연구의 결과는 학교경영컨설턴트의 교육과 자격에 반영할 수 있고,학교경영컨설팅의 '학습성' 원리를 확인하였다는 점에서 의의가 있다.

• Asia pacific journal of information systems
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• 제29권4호
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• pp.789-816
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• 2019

Text classification is a challenging task, especially when dealing with a huge amount of text data. The performance of a classification model can be varied depending on what type of words contained in the document corpus and what type of features generated for classification. Aside from proposing a new modified version of the existing algorithm or creating a new algorithm, we attempt to modify the use of data. The classifier performance is usually affected by the quality of learning data as the classifier is built based on these training data. We assume that the data from different domains might have different characteristics of noise, which can be utilized in the process of learning the classifier. Therefore, we attempt to enhance the robustness of the classifier by injecting the heterogeneous data artificially into the learning process in order to improve the classification accuracy. Semi-supervised approach was applied for utilizing the heterogeneous data in the process of learning the document classifier. However, the performance of document classifier might be degraded by the unlabeled data. Therefore, we further proposed an algorithm to extract only the documents that contribute to the accuracy improvement of the classifier.

• 한국산학기술학회논문지
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• 제22권4호
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• pp.580-586
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• 2021

현재 사출성형분야의 Computer Aided Testing(CAT) 방법론으로 CAE(Computer Aided Engineering)를 이용한 수치 해석 기법이 주를 이루고 있다. 그러나 최근 시뮬레이션에 추가로 인공지능 기법을 응용하는 방법론이 연구되고 있다. 우리는 지난 연구에서 다양한 Machine Learning 기법을 활용하여 사출 성형 공정에 따른 변형 결과를 비교하였으며, 최종적으로 MLP(Multi-Layer Perceptron) 예측모델을 생성하였고, HMA(Hybrid Metaheuristic Algorithm)를 이용하여 최적화 결과를 얻어냈다. 그러나 MLP는 예측 성능이 우수한 반면 블랙박스와 같이 결정 과정에 대한 설명이 부족하다. 본 연구에서는 Radiator Tank 부품에 대하여 사출 성형 해석 소프트웨어인 Autodesk Moldflow 2018을 이용하여 수치 해석 기법으로 데이터를 생성하고, Machine Learning 소프트웨어인 RapidMiner Studio version 9.5를 활용하여 여러 Machine Learning Algorithms 모델을 생성하여 평균 제곱근 오차를 비교하였다. Decision-tree는 Root Mean Square Error(RMSE) 값이 다른 Machine Learning 기법에 비해 양호한 예측 성능을 갖추고 있었다. Decision-tree의 크기를 결정하는 Maximal Depth에 따라 분류 기준을 높일 수 있지만 복잡성도 함께 증가시켰다. Decision-tree를 이용하여 구속 조건을 만족하는 중간 값을 선정하여 시뮬레이션을 진행한 결과 기존의 시뮬레이션만 진행한 것보다 7.7%의 개선 효과가 있었다.