• 정보교육학회논문지
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• 제12권1호
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• pp.89-97
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• 2008

제 7차 초등학교 과학과 교육과정에서는 특히 탐구학습을 강조하고 있다. 그러나 단위 시간과 학습자료의 부족이라는 현실적인 이유 때문에 학교 교육 현장에서는 실제적인 적용이 어렵다. 본 연구에서는 이러한 문제점을 해결하기 위하여 웹기반 발견학습 시스템을 설계 구현하고 그 효과성을 검증하는데 목적이 있다. 검증 과정으로 초등학교 4학년 과학과의 용수철 늘이기 단원을 대상으로 일반적인 발견학습 모형을 적용한 비교집단과 웹기반 발견학습 시스템으로 수업을 받은 실험집단의 학업성취도에 있어 유의미한 차이가 있는지 조사하였다. 적용 결과, 웹기반 발견학습 시스템으로 수업을 한 경우, 전통적인 발견학습 모형 그대로 적용한 경우보다 학업 성취도가 높았다.

• 한국초등과학교육학회지:초등과학교육
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• 제25권3호
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• pp.307-317
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• 2006

Those students with ability and interest in science should be supported to develop their potential and to reach high levels of achievement in science and technology. In order to ensure that gifted pupils are able to enhance their creativity as well as research abilities, appropriate learning programs and environments are essential. One of the various teaching and learning models for the gifted in science is the discovery learning model based on inductive science activities. There is a clear line of continuity between knowledge discovery at the forefront of research and student's learning activities. If students receive excellent training in organizing scientific concepts for themselves, they will be able to skillfully apply appropriate scientific concepts and solve problems when facing unfamiliar situations. It is very important to offer an appropriate learning environment to maximize the learning effect whilst, at the same time, understanding individual student's characteristics. In this study, the authors took great pains to research effective learning environments for gifted science students. Firstly, appropriate classroom learning environments thought by the teacher to offer the most potential were investigated. 3 different classes in which a revised teaching and learning environment was applied in sequence were examined. Inquiries were conducted into students' activities and achievement through observation, interviews, and examination of students' worksheets. A Science Education expert and 5 elementary school teachers specializing in gifted education also observed the class to examine the specific character of gifted science students. A number of suggestions in discovery learning classes for elementary students gifted in science are possible; 1) Readiness is essential in attitudes related to the inquiry. 2) The interaction between students should be developed. A permissive atmosphere is needed in small group activities. 3) Students require training in listening to others. In a whole class discussion, a permissive atmosphere needs to be restricted somewhat in order to promote full and inclusive discussion. 4) Students should have a chance to practice induction and abduction methods in solving problems.

• 한국컴퓨터정보학회논문지
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• 제22권1호
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• pp.23-32
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• 2017

We can obtain useful knowledge from data by using a subgroup discovery algorithm. Subgroup discovery is a rule model learning method that finds data subgroups containing specific information from data and expresses them in a rule form. Subgroups are meaningful as they account for a high percentage of total data and tend to differ significantly from the overall data. Subgroup is expressed with conjunction of only literals previously. So, the scope of the rules that can be derived from the learning process is limited. In this paper, we propose a method to increase expressiveness of rules through internal disjunctive representation of attribute values. Also, we analyze the characteristics of existing subgroup discovery algorithms and propose an improved algorithm that complements their defects and takes advantage of them. Experiments are conducted with the traffic accident data given from Busan metropolitan city. The results shows that performance of the proposed method is better than that of existing methods. Rule set learned by proposed method has interesting and general rules more.

• Computers and Concrete
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• 제31권4호
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• pp.277-292
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• 2023

Much of our experiments are designed to uncover the cause(s) and effect(s) behind a phenomenon (i.e., data generating mechanism) we happen to be interested in. Uncovering such relationships allows us to identify the true workings of a phenomenon and, most importantly, to realize and articulate a model to explore the phenomenon on hand and/or allow us to predict it accurately. Fundamentally, such models are likely to be derived via a causal approach (as opposed to an observational or empirical mean). In this approach, causal discovery is required to create a causal model, which can then be applied to infer the influence of interventions, and answer any hypothetical questions (i.e., in the form of What ifs? Etc.) that commonly used prediction- and statistical-based models may not be able to address. From this lens, this paper builds a case for causal discovery and causal inference and contrasts that against common machine learning approaches - all from a civil and structural engineering perspective. More specifically, this paper outlines the key principles of causality and the most commonly used algorithms and packages for causal discovery and causal inference. Finally, this paper also presents a series of examples and case studies of how causal concepts can be adopted for our domain.

• 한국과학교육학회지
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• 제16권1호
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• pp.13-34
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• 1996

The purpose of this study is to develop appropriate science teaching models which can be applied effectively to relevant situations. Five science teaching models; cognitive conflict teaching models, generative teaching model, learning cycle teaching model, hypothesis verification teaching model and discovery teaching model, were identified from the existing models. The teaching models were modified and in primary and secondary students using a nonequivalent pretest-posttest control group design. Major findings of this study were as follows: 1. For teaching science concepts, three teaching models were found more effective; cognitive conflict teaching model, generative teaching model and discovery teaching model. 2. For teaching inquiry skills, two teaching models were found more effective; learning cycle teaching model and hypothesis verification teaching model. 3. For teaching scientific attitudes, two teaching models were found more effective; learning cycle teaching models and discovery teaching model. Each teaching model requires specific learning environment. It is strongly suggested that teachers should select a suitable teaching model carefully after evaluating the learning environment including teacher and student variables, learning objectives and curricular materials.

• International Journal of Contents
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• 제12권4호
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• pp.8-16
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• 2016

This research proposes the composition logic of an Active Learning Environment (ALE), to enable discovery by learning through experience, whilst increasing knowledge about modern architectural heritage. Linking information to the historical heritage using Information and Communication Technology (ICT) helps to overcome the limits of previous learning methods, by providing rich learning resources on site. Existing field trips of cultural heritages are created to impart limited experience content from web resources, or receive content at a specific place through humanities Geographic Information System (GIS). Therefore, on the basis of the blended space theory, an augmented space experience method for overcoming these shortages was composed. An ALE space framework is proposed to enable discovery through learning in an expanded space. The operation of ALE space is needed to create full coordination, such as a Content Management System (CMS). It involves a relation network to provide knowledge to the rule engine of the CMS. The application is represented with the Deoksugung Palace Seokjojeon hall example, by describing a user experience scenario.

• 한국학교수학회논문집
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• 제3권1호
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• pp.177-188
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• 2000

Mathematics is extreme the differences of the scholarly attainments in comparison with other subjects at a middle school. Specially, the students at islands and places leave much to be desired the scholarly attainments standards of mathematics. Therefore, every school takes movement class according to level these days. And the small schools put in effect the cooperation of group work through the small groups. These classes are effective at the scholarly attainments extension to some degree, but each student is extreme the differences of scholarly attainments. On this, the small school was the subject of study at the present research and put in effect the cooperation of group work through the small groups. The students were divided in three groups; the top class, average, the low class, And they were offered the fitting textbooks matching the cooperation of group work and the opportunities of discovery learning fitting an individual ability and standard. Consequently, some educational materials were made, for example, question papers, commonness learning materials, choice learning materials. These materials were put in effect to the students to be able to succeed discovery learning. With this, the students were investigated an interest of mathematics and the influence giving at the studies attainment. And the students were put in effect the cooperation of group work through the small groups to improve uniformity and sturdiness of the mathematical education. The conclusion at the present research is as follows. 1) When the students put in effect the cooperation of group work through the small groups, the scholarly attainments of mathematics totally didn't display useful changes as improvement. However, the students of average and the low class gradually seemed to improve the scholarly attainments of mathematics as the help of the top class positively. 2) An individual and cooperation learning in the method of the cooperation of group work through the small groups displayed many changes at the learning attitude of the students by means of discovery learning thanks to the learning heads. 3) When the investigator put in effect the cooperation of group work through rather the small groups than the large groups, the numbers of the students experiencing interest about mathematics increased in 26% and this learning method should continue to progress.

• 지능정보연구
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• 제21권4호
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• pp.1-16
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• 2015

교통사고의 원인을 규명하고 미래의 사고를 방지하기 위한 노력의 일환으로 데이터 마이닝 기법을 이용한 교통 데이터 분석의 연구가 이루어지고 있다. 하지만 기존의 교통 데이터를 이용한 마이닝 연구들은 학습된 결과를 사람이 이해하기 어려워 분석에 많은 노력이 필요하다는 문제가 있었다. 본 논문에서는 많은 속성들로 표현된 교통사고 데이터로부터 유용한 패턴을 발견하기 위해 규칙 학습 기반의 데이터 마이닝 기법인 연관규칙 학습기법과 서브그룹 발견기법을 적용하였다. 연관규칙 학습기법은 비지도 학습 기법의 하나로 데이터 내에서 동시에 많이 등장하는 아이템(item)들을 찾아 규칙의 형태로 가공해 주며, 서브그룹 발견기법은 사용자가 지정한 대상 속성이 결론부에 나타나는 규칙을 학습하는 지도학습 기반 기법으로 일반성과 흥미도가 높은 규칙을 학습한다. 규칙 학습 시 사용자의 의도를 반영하기 위해서는 하나 이상의 관심 속성들을 조합한 합성 속성을 만들어 규칙을 학습할 수 있다. 규칙이 도출되고 나면 후처리 과정을 통해 중복된 규칙을 제거하고 유사한 규칙을 일반화하여 규칙들을 더 단순하고 이해하기 쉬운 형태로 가공한다. 교통사고 데이터를 대상으로 두 기법을 적용한 결과 대상 속성을 지정하지 않고 연관규칙 학습기법을 적용하는 경우 사용자가 쉽게 알기 어려운 속성 사이의 숨겨진 관계를 발견할 수 있었으며, 대상 속성을 지정하여 연관규칙 학습기법과 서브그룹 발견기법을 적용하는 경우 파라미터 조정에 많은 노력을 기울여야 하는 연관규칙 학습기법에 비해 서브그룹 발견기법이 흥미로운 규칙들을 더 쉽게 찾을 수 있음을 확인하였다.

• 한국정보통신학회논문지
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• 제22권3호
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• pp.527-533
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• 2018

최근 단말-대-단말(Device-to-device, D2D) 통신기술이 차세대 무선통신시스템의 핵심기술로 큰 관심을 받고 있다. 이러한 단말간 통신에서는 자신의 주변에 어떠한 단말이 있는지 파악하는 주변단말 탐색(Neighbor discovery)이 매우 중요하다. 본 논문에서는 최근 큰 관심을 받고 있는 딥러닝(Deep learning) 기술을 활용하여 단말간 통신에서 주변단말을 파악하는 방안에 대해서 제안한다. 제안 방안은 기존의 방안과 달리 무선채널의 공간적 연관성을 이용하여 단말간의 신호 전송 없이 단말이 기지국으로 전송하는 상향링크 파일럿 신호를 기반으로 주변 단말을 찾고 따라서 기존의 방식에 비해 신호전송 복잡도(signaling complexity)를 크게 줄일 수 있다. 또한 제안 방안에서는 떨어져 있는 거리에 따라서 주변 단말을 분류 가능하여 기존 방안에 비해서 좀 더 세밀한 단말 탐색이 가능하다. 마지막으로 본 논문에서는 tensorflow를 이용한 컴퓨터 시뮬레이션을 통해 제안 방안의 성능을 검증하였다.

• 지식경영연구
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• 제2권1호
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• pp.109-132
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• 2001

The purpose of this article is to develop a dynamic model of organizational capabilities and knowledge creation, and at the same time identify the organizational capability factors for effective knowledge creation, by empirically analyzing the history of new Quinolone antibacterial drug compound (LB20304a) discovery process at LG, as a case in point. Major findings of this study are as follows. First, in a science-based area such as drug development, the core of successful knowledge creation lies in creative combination of different bodies of scientific explicit knowledge. Second, the greater the difficulty of learning external knowledge, the more tacit knowledge is needed for the recipient firm to effectively exploit that knowledge. Third, in science-based sector such as pharmaceutical industry, the key for successful knowledge creation lies in the capability of recruiting and retaining star scientists. Finally, for effective knowledge creation, a firm must keep its balance among three dimensions of organizational capabilities: local, process, architectural capabilities.