학습 온톨로지 생성을 통한 학습 성과

김정민,정현숙 한국공학교육학회 2008 공학교육연구 Vol.11 No.2

Teaching is communication between instructor and students. The learning outcomes can be enhanced by active learning of students. However, there are many obstacles to effective learning below, such as lecture notes authored by instructor, passive student participation, and paper-based homework. In this paper, we propose an effective method for enhancing learning effect through constructing learner ontologies in which knowledge discovered by students is conceptualized and organized. The learning ontology is composed of a teacher ontology and many learner ontologies. The learning ontology is used in discussion, visual presentation, and knowledge sharing between instructor and students. We used the learning ontology in two lectures in practice and learned that the learning ontology enhances learning effect through analysis of feedbacks of students.

직접교수모형의 교수전략 온토로지를 기반으로 한 교수학습과정안 설계

이재무 한국지식정보기술학회 2017 한국지식정보기술학회 논문지 Vol.12 No.1

This study is to build an instructional strategy ontology to aid the effective design of a Teaching-Learning plan for novice designers who lack instructional design knowledge. Most of designer tend to represent ambiguously the instructional strategy. Therefore they need to provide fluently learning procedures and activities to achieve the learning goals. The Instructional model was selected as a direct instructional model that is appropriate for learning computer skills and is used widely in computer education field. This study constructed instructional strategy ontology for direct instruction model using ontology authoring tools. The study proposes a method for designing a Teaching-Learning plan in addition to analysis effects through the questionnaire. This method uses instructional strategy ontology of direct instruction model that was built by the author. The instructional ontology can be shared and reused among the designers. The proposed method made a Teaching-Learning plan that could describe teacher’ and learner’s activities concretely by decomposed instructional strategy. Finally, it made a Teaching-Learning plan with fluent content using instructional strategy ontology for novice designers. Moreover, it supports a balanced design considering the overall structure through the visual interface. However, we have limitations as this study proposes the only design method for Teaching-Learning plan using instructional strategy ontology. In the future, we will need further researches to support the automatic design of Teaching-Learning plan with intelligent facilities.

학습 온톨로지 생성을 통한 학습 성과 강화에 관한 연구

김정민(Kim Jung Min),정현숙(Chung Hyun Sook) 한국공학교육학회 2008 공학교육연구 Vol.11 No.2

수업은 교수자와 학습자의 상호작용으로 정의될수 있으며 학습자의 능동적 활동에 의해 학습 성과가 향상될 수 있다. 그러나 교수자에 의해 작성되고 배포되는 강의자료, 교수자의 일방적인 강의, 페이퍼 위주의 과제 제출 등으로 학습자의 적극적인 학습 참여가 제한되고 있다. 본 논문에서는 학습자가 스스로 발견한 지식을 개념화하고 지식 구조를 정의함 으로써 학습자 온톨로지를 생성하는 방법을 제안한 다. 또한 교수자 온톨로지와의 연계를 위해 온톨로지 매칭 및 연계 기법을 제안한다. 교수자 온톨로지와 학습자 온톨로지는 통합되어 학습 온톨로지를 구성하며 이 온톨로지를 토대로 교수자와 학습자들 사이에 토론, 발표, 지식 공유 등이 이루어진다. 제안 하는 온톨로지 기반 학습은 실제 수업에 적용되었으며 학습자들의 피드백 분석을 통해 그 효과를 보였 다. Teaching is communication between instructor and students. The learning outcomes can be enhanced by active learning of students. However, there are many obstacles to effective learning below, such as lecture notes authored by instructor, passive student participation, and paper-based homework. In this paper, we propose an effective method for enhancing learning effect through constructing learner ontologies in which knowledge discovered by students is conceptualized and organized. The learning ontology is composed of a teacher ontology and many learner ontologies. The learning ontology is used in discussion, visual presentation, and knowledge sharing between instructor and students. We used the learning ontology in two lectures in practice and learned that the learning ontology enhances learning effect through analysis of feedbacks of students.

학습 온톨로지 생성을 통한 학습 성과 강화에 관한 연구

김정민(Kim Jung Min),정현숙(Chung Hyun Sook) 한국공학교육학회 2008 공학교육연구 Vol.11 No.4

수업은 교수자와 학습자의 상호작용으로 정의될수 있으며 학습자의 능동적 활동에 의해 학습 성과가 향상될 수 있다. 그러나 교수자에 의해 작성되고 배포되는 강의자료, 교수자의 일방적인 강의, 페이퍼 위주의 과제 제출 등으로 학습자의 적극적인 학습 참여가 제한되고 있다. 본 논문에서는 학습자가 스스로 발견한 지식을 개념화하고 지식 구조를 정의함 으로써 학습자 온톨로지를 생성하는 방법을 제안한 다. 또한 교수자 온톨로지와의 연계를 위해 온톨로지 매칭 및 연계 기법을 제안한다. 교수자 온톨로지와 학습자 온톨로지는 통합되어 학습 온톨로지를 구성하며 이 온톨로지를 토대로 교수자와 학습자들 사이에 토론, 발표, 지식 공유 등이 이루어진다. 제안 하는 온톨로지 기반 학습은 실제 수업에 적용되었으며 학습자들의 피드백 분석을 통해 그 효과를 보였 다. Teaching is communication between instructor and students. The learning outcomes can be enhanced by active learning of students. However, there are many obstacles to effective learning below, such as lecture notes authored by instructor, passive student participation, and paper-based homework. In this paper, we propose an effective method for enhancing learning effect through constructing learner ontologies in which knowledge discovered by students is conceptualized and organized. The learning ontology is composed of a teacher ontology and many learner ontologies. The learning ontology is used in discussion, visual presentation, and knowledge sharing between instructor and students. We used the learning ontology in two lectures in practice and learned that the learning ontology enhances learning effect through analysis of feedbacks of students.

A Web-Based Domain Ontology Construction Modelling and Application in the Wetland Domain

Jun Xing,Min Han 한국멀티미디어학회 2007 멀티미디어학회논문지 Vol.10 No.6

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

A Web-Based Domain Ontology Construction Modelling and Application in the Wetland Domain

Xing, Jun,Han, Min Korea Multimedia Society 2007 멀티미디어학회논문지 Vol.10 No.6

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

A WEB-BASED DOMAIN ONTOLOGY CONSTRUCTION MODELING AND APPLICATION IN THE WETLAND DOMAIN

Jun Xing,Min Han 한국멀티미디어학회 2006 한국멀티미디어학회 국제학술대회 Vol.2006 No.-

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model - Onto Maker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. Onto Maker constructs the wetland ontologisms and the model in this work can also be referred to other environmental domains.

Intelligent Agent Based Architectures for E-Learning System : Survey

Muhammad Arif,Mehdi Hussain 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.6

E-learning is the internet enabled learning. Internet has ongoing to restructuring education. Intelligent agent based e-learning provide a common infrastructure to assimilate varied software components. There are two sorts of e-learning synchronous and asynchronous. This paper described the detail of well-known agent based architecture for e-learning. E-learning is going to be gigantic. There are multiple benefits of e-learning; it is convenient, self-service mix, match, on demand any time anyplace, private learning, Self-paced and elastic. E-learning provide cost effective and virtual environment. E-learning gives the ability to user to collect the quantifiable and sensible material, examine, and distribute and custom e-learning knowledge from multiple e learning sources.

주자학 속에 숨은 양명학: 노수신의 주자학과 그의 인심도심 해석

최진덕 ( Choi Jin Duk ) 한국사상사학회 2015 韓國思想史學 Vol.0 No.51

노수신은 16세기 당시부터 양명학을 한다고 비판받아 왔다. 오늘날에도 신향림은 그를 “최초의 양명학자”로 지목한다. 하지만 노수신의 산문은 매우 주자학적이다. 그의 시에서 간혹 양명학적 소신이 드러날뿐이다. 간혹 보이는 그의 양명학은 그의 주자학과 모순이라 보기 어렵다. 주자학적 본체론의 깊이에는 “이는 하나(理一)”라는 진리가 있다. 이 진리는 왕양명의 만물일체설과 다르지 않다. 주자학적 본체론의 깊은 곳에 양명학이 숨어있다. 그러므로 모든 주자학자는 잠재적으로 양명학자일 수 있다. 노수신은 주자학적 본체론의 깊이에 침잠함으로써 양명학과 만난다. 그의 『인심도심변』은 주희의 인심도심 해석이 주자학적 본체론과 공부론의 체와 용을 겸비하지 못하고 용의 차원에 그치고 있음을 안타깝게 여겨 16자 전심결을 주자학적으로 완전하게 해석한다. 『중용장구서』 에서의 주희의 인심도심 해석보다 더 주자학적인 노수신의 인심도심 해석은 나정암의 그것과 흡사하다. 그런데 노수신은 주자학적 본체론의 깊이에서 하나(一)과 무(無)를 말하면서 양명학과 만나는 반면, 나정암은 하나와 무를 말하지 않으면서 양명학과는 반대 방향으로 나아간다. 하지만 노수신은 양명학을 하더라도 극단으로 가지는 않는다. 그에겐 강렬한 깨달음의 체험도 없고 광자기상도없다. 주자학과 양명학은 근본적으로 연속적이지만 주자학이 권력화되던 시절에 양명학적 소신을 피력하기란 쉽지 않기도 했다. Noh Susin(盧守愼, 1515-1590) had been accused of his inclination to Yangming``s Learnning by the fundamentalist scholars of Chuhsi``s Learning in Chosun Dynasty. However, in his proses discussing the themes of Chuhsi``s Learning, we cannot find out any evidence that he was a scholar of Yangming``s Learning as opposed to Chuhsi``s Learning. On the contrary he seems to be faithful to the authenticity of Chuhsi``s Learning more than any other scholar of Chuhsi``s Learning. Only in his poems we can find out some phrases showing his inclination to Yangming``s Learning. Is there any discontinuity between Chuhsi``s Learning in his proses and Yangming``s Learning in his poems? At first we must know that Yangming``s Learning has the same theory of ontology as Chuhsi``s Learning, and that Yangming``s Learning is different from Chuhsi``s Learning only in the theory of self-cultivation. According to the ontology of Chuhsi``s Learning, all different things in this changing world are flowing into one thing while interacting with each other. This oneness of all things is the ontological depth of Chuhsi``s Learning, but Chuhsi``s Learning cannot provide any efficient method of self-cultivation to arrive at the ontological depth and to become a sage. The sudden enlightenment theory of self-cultivation proposed by Wang Yangming is more appropriate than the moral and intellectual theory of self-cultivation in Chuhsi``s Learning. We can say that the ontological depth of Chuhsi``s learning calls for Yangming``s Learning. The inclination to Yangming``s Learning of Noh Susin seemed to be due to his experience of the ontological depth of Chuhsi``s Learning, which was the result of his arduous study of Chuhsi``s Learning. He became inclined to Yangming``s Learning because he was faithful to Chuhsi``s Learning. Also his new interpretation of Men``s mind and Tao``s mind was to revive the ontological depth of Chuhsi``s Learning omitted in the interpretation of Chuhsi himself which considers the two minds as the two desires of the psychological level.

온톨로지 기반 학습 콘텐츠의 난이도 계산 방법

박재욱(Jae-Wook Park),박미화(Mee-Hwa Park),이용규(Yong-Kyu Lee) 한국컴퓨터정보학회 2011 韓國컴퓨터情報學會論文誌 Vol.16 No.2

이러닝 시스템에서 난이도를 이용한 학습추천 시스템 설계에 관한 연구가 활발히 진행 중이다. 난이도는 학습자의 수준에 맞는 후행학습을 추천하는데 매우 중요한 요소임에도 불구하고 현행 난이도 기반 학습 추천시스템은 각 학습 콘텐츠의 제작자가 주관적으로 정한 난이도를 적용함으로써 정확한 후행 학습 콘텐츠를 추천하기가 어렵다. 본 논문에서는 객관적인 난이도 지표를 제공하기 위하여 온톨로지에 기반한 새로운 학습콘텐츠 난이도 계산 방법을 제안한다. 기존 온톨로지나 지식맵을 이용한 난이도 계산 방법들은 선행학습과 후행학습 또는 주제간의 선후 관계를 표현하고 이를 이용하여 난이도를 계산하였으나, 이 방법들도 콘텐츠 작성자의 주관적인 판단에 의해 후행학습이 결정된다는 문제점이있다. 본 논문에서는 이를 해결하기 위하여 콘텐츠를 구성하는 단어들의 상하위 관계 및 심화도를 나타내는 온톨로지를 이용하여 단어들 간 온토로지의 경로상의 거리로 난이도를 계산한다. 이를 통하여 학습자에게 보다 객관적인 난이도 정보를 제공하고 학습자 수준에 가장 적합한 후행학습 콘텐츠를 추천할 수 있다. Much research has been conducted on the e-learning systems for recommending a learning content to a student based on the difficulty of it. The difficulty is one of the most important factors for selecting a learning content. In the existing learning content recommendation systems, the difficulty of a learning content is determined by the creator. Therefore, it is not easy to apply a standard rule to the difficulty as it is determined by a subjective method. In this paper, we propose an ontology-based method for determining the difficulty of a learning content in order to provide an objective measurement. Previously, ontologies and knowledge maps have been used to recommend a learning content. However, their methods have the same problem because the difficulty is also determined by the creator. In this research, we use an ontology representing the IS-A relationships between words. The difficulty of a learning content is the sum of the weighted path lengths of the words in the learning content. By using this kind of difficulty, we can provide an objective measurement and recommend the proper learning content most suitable for the student's current level.