• Communications of Mathematical Education
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• v.13 no.1
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• pp.337-360
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• 2002

그래프 능력을 바탕으로 한 함수의 그래프 표현은 함수 교수 ${\cdot}$ 학습상 중요한 위치를 차지한다. 그러나 부적절한 함수 그래프 과제 교수 ${\cdot}$ 학습 방법은 학생들의 지식 구성, 이해 과정에 영향을 주면서 수학적 오류를 형성하게 하였다. 그러므로 체계적인 오류 분석을 기반으로 한 좋은 교수학적 프로그램을 통해 수학적 오류를 예견하고 학습 과정에서 그것을 잘 처치, 활용하는 것이 효과적인 함수 교수 ${\cdot}$ 학습을 위해 요구된다. 본 연구에서는 지필 환경하에서 함수 그래프 과제를 수행한 학생들에게서 일반적으로 나타나는 수학적 오류를 점검하고, 새로운 교육용 테크놀러지 환경하에서 이러한 수학적 오류가 변화되는 과정을 살펴보고자 하였다. 첫 번째 연구 문제를 위해 고등학생 119명을 대상으로 양적 연구를 실시하였으며, 함수에 대한 개념 이미지로부터의 오류가 가장 많이 나타났음을 확인할 수 있었다. 두 번째 연구문제를 위해 고등학생 2명을 대상으로 사례 연구를 실시하였는데, 그 결과 기존의 수학적 오류가 새로운 교수학적 환경하에서 변화, 극복되는 것을 확인할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1226-1227
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• 2023

최근 그래프 기반 분석에 대한 연구가 활발히 진행되면서 이를 정보 보안 분야에 적용하려는 시도가 이루어지고 있다. 특히 GNN(Graph Neural Network)은 복잡한 네트워크 데이터를 모델링하고 관계를 분석하는 데 효과적이며, 악성 코드 탐지 등 사이버 공격에 대한 대응 능력을 향상시키는 데 활용할 수 있다. 하지만 GNN을 사용하기 위해서는 그래프의 노드가 될 IOC(Indicator of Compromise) 데이터가 필요하다. 본 논문에서는 IOC Extractor 중 하나인 Cyobstract를 통하여 위협 보고서로부터 IOC를 추출하는 방법과 이를 활용하여 그래프를 구축하고 분석할 방향을 제시한다.

• Communications of Mathematical Education
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• v.10
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• pp.519-528
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• 2000

최근 10 여년 동안 교육 현장의 각 부분에 여러 가지 종류의 테크놀로지가 도입되면서, 교육의 내용과 방법에 있어서 점진적인 변화가 나타나고 있다. 예를들어, 수학 과목에 있어서는 그래픽 계산기, 도형 및 기하 학습 프로그램, 스프레드 시트, 함수 그래픽 프로그램 등의 도입으로 교과 과정 전반에 걸친 변화가 일고 있는데, 처음에는 이들 테크놀로지가 단순히 기존의 수업에서 수많은 반복을 요하거나, 지필식 방식으로는 정확하게 나타내기 어려운 도형이나 그래프를 빠르고 정확하게 그려내주는 보조수단으로 사용되었지만, 시간이 지나면서 이들 테크놀로지에 대한 활용도가 높아지게 되고, 이들 테크놀로지에 대한 교사들의 활용능력이 증대됨에 다라서, 이러한 테크놀로지가 단순한 보조수단에 머무르지 않고 주지에 기술이나 개념을 설명하는 방법 자체를 변화시키고 있다. 예를들어, 함수 교육에 있어서 그래픽 프로그램이 사용될 때에도, 초기 단계에서는 이들 함수의 개념을 설명할 때에는 거의 집합론이나 대수학적인 방법을 이용하였고, 최종 단계로 이들 함수를 좌표계 위에 표현하기 위한 보조수단으로 잠깐씩 사용되는 경우가 대부분이었으나, 최근들어서는 함수 학습의 초기과정부터 곧바로 이들 그래프 프로그램을 적극적으로 도입하여 학습자로 하여금 다양한 그래프 조작을 하게 함으로써, 어려운 집합론이나 대수학적인 개념을 도입하지 않고서도 함수에 대한 개념을 시각적으로 직관적으로 파악하도록 하는 학습 방안들이 제시되고 있는 것이다. 본 고에서는 현행 중고등학교 함수 교육 과정에서 그래프에 대한 다양한 조작 기능을 제공함으로써 학습자로 하여금, 제시되는 함수에 대한 시각적이고 직관적인 이미지를 가질 수 있도록 하기 위해서 개발된 ‘그래프 마법사’라는 프로그램을 소개하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.8
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• pp.243-250
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• 2020

Knowledge graph-based question answering not only requires deep understanding of the given natural language questions, but it also needs effective reasoning to find the correct answers on a large knowledge graph. In this paper, we propose a deep neural network model for effective reasoning on a knowledge graph, which can find correct answers to complex questions requiring multi-hop inference. The proposed model makes use of highly expressive bilinear graph neural network (BGNN), which can utilize context information between a pair of neighboring nodes, as well as allows bidirectional feature propagation between each entity node and one of its neighboring nodes on a knowledge graph. Performing experiments with an open-domain knowledge base (Freebase) and two natural-language question answering benchmark datasets(WebQuestionsSP and MetaQA), we demonstrate the effectiveness and performance of the proposed model.

• Knowledge Management Research
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• v.25 no.2
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• pp.1-18
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• 2024

With the increasing demand for and utilization of large language models (LLMs), the risk of user sensitive information being inputted and leaked during the use of LLMs also escalates. Typically recognized as a tool for mitigating the hallucination issues of LLMs, knowledge graphs, constructed independently from LLMs, can store and manage sensitive user information separately, thereby minimizing the potential for data breaches. This study, therefore, presents a knowledge graph-based chatbot that transforms user-inputted natural language questions into queries appropriate for the knowledge graph using LLMs, subsequently executing these queries and extracting the results. Furthermore, to evaluate the functional validity of the developed knowledge graph-based chatbot, performance tests are conducted to assess the comprehension and adaptability to existing knowledge graphs, the capability to create new entity classes, and the accessibility of LLMs to the knowledge graph content.

• 대한공업교육학회지
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• v.40 no.1
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• pp.105-120
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• 2015

The purpose of this study was to extract of Sub-elements of technological communication skills and to construct of a system model. In order to achieve the goal of the study, it was carried out in two steps: (1)Extraction sub-elements and definitions of technological communication skills, (2)Development of a system model of technological communication skills. Obtained conclusions by the process of this research were as follows. First, sub-elements of the technological communication skills were extracted and they were images, sketches, flowcharts, drawings, prototyping, symbols tables graphs and presentations. Second, using the 'technological communication tools' based on the "collaborative activities in online and offline', technological communication skills were defined as communication skills to be raised through the process of 'Idea through the Communication', 'Realization through the Communication', 'Wrap up through the Communication'. Third, technological communication skills were described as the system, in which 'Idea through the Communication(images, sketches, flowcharts)', 'Realization through the Communication(design, prototyping)', 'Wrap up through the Communication(symbol table graph, presentation)' were collaboratively activated. Fourth, checking tool for the technological communication skills was developed, based on checking tool for the existing communication skills and system model for technological communication skills. And it was improved by the expert validity test.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.410-427
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• 2009

This study aims to rethink the meaning of graphicacy, discuss the possible criteria to evaluate the level of graphicacy, and show how the graphicacy differs through different grades. First, it finds that as school grades advance, implicit information processing abilities, and conceptual information processing abilities were more required comparing to explicit information processing abilities, when interpreting graphic data. Secondly, the percentage of items which examinee showed a proficient level, decreased as school grades advanced. Thirdly, the graphicacy level of sixth graders was the status of being able to derive explicit information from pictorial maps and read implicit information in simple contour map or line graphs. Ninth graders were able to infer causal relationship between geographic phenomenons by utilizing graphic materials. Tenth graders could read graphic materials by utilizing simple knowledge and experience.

• Journal of The Korean Association For Science Education
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• v.39 no.5
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• pp.655-668
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• 2019

In this study, we investigated the middle school students' processes of scientific graph construction from the perspective of the problem solving process. Ten 9th graders participated in this study. They constructed a scientific graph based on pictorial data depicting precipitation reaction. The think-aloud method was used in order to investigate their thinking processes deeply. Their activities were videotaped, and semi-structured interviews were also conducted. The analysis of the results revealed that their processes of scientific graph construction could be classified into four types according to the problem solving strategy and the level of representations utilized. Students using the structural strategy succeeded in constructing scientific graph regardless of the level of representation utilized, by analyzing the data and identifying the trend based on the propositional knowledge about the target concept of the graph. Students of random strategy-higher order representation type were able to succeed in constructing scientific graph by systematically analyzing the characteristics of the data using various representations, and considering the meaning of the graph constructed in terms of the scientific context. On the other hand, students of random strategy-lower order representation type failed to construct correct scientific graph by constructing graph in a way of simply connecting points, and checking the processes of graph construction only without considering the scientific context. On the bases of the results, effective methods for improving students' ability to construct scientific graphs are discussed.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.840-849
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• 2014

The paper shows that algorithm education positively affects algorithmic thinking for elementary students. Experiments are conducted on thirty five sixth graders without prior experience of algorithm. The experimental group is given eleven sessions of lesson for four weeks in which algorithmic solution is sought for graph coloring problems. After four weeks of experiments questionnaires are distributed to the students in order to measure differences in algorithmic interest and algorithmic thinking ability. The following results are obtained: Firstly, it may be observed that algorithm education with graph coloring may be effective in reinforcing students' interest in algorithms. Secondly, the experiment shows that algorithmic thinking ability may be enhanced from participating in graph coloring activities. In conclusion, algorithm education with graph coloring problem helps students develop algorithmic thinking ability as well as cultivate students' interest in algorithmic thinking.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.62-68
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• 1983

We suggest a Quasi- dual graph model in consideration of dynamic module assignment and relocation to assign task optimally to two processors that have different processing abilities. An optimal module partitioning and allocation to minimize total processing cost can be achieved by applying shortest-path algorithm with time complexity 0(n2) on this graph model.