• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.429-440
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• 2001

To achieve a computer tutor framework with high learning effects as well as practicality, the goal of this research has been set to developing an intelligent tutor for problem-solving in mathematics domain. The maine feature of the CyberTutor, a computer tutor developed in this research, is the facilitation of a learning environment interacting in accordance with the learners differing inferential capabilities and needs. The pedagogical information, the driving force of such an interactive learning, comprises of tutoring strategies used commonly in various domains such as phvsics and mathematics, in which the main contents of learning is the comprehension and the application of principles. These tutoring strategies are those of testing learners hypotheses test, providing hints, and generating explanations. We illustrate the feasibility and the behavior of our propose framework with a sample problem-solving learning in geometry. The proposed tutorial framework is an advancement from previous works in several aspects. Firstly, it is more practical since it supports handing of a wide range of problem types, including not only proof types but also finding-unkown tpes. Secondly, it is aimed at facilitating a personal tutor environment by adapting to learners of varying capabilities. Finally, learning effects are maximized by its tutorial dialogues which are derived from real-time problem-solving inference instead of from built-in procedures.

• Journal of Fisheries and Marine Sciences Education
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• v.20 no.3
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• pp.462-472
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• 2008

Education is a field that has tried to make use of the advantages of computers since they were introduced to the world. Intelligent Tutoring System and multimedia have become methods of teaching students of Computer Science, Education, Psychology, and Cognitive Science. Until now, they have been designed and produced only on the basis of a very specific domain and format. However, in the education field, most learners ask for integrated service that is practical, realizable, and sensitive to technological change. Therefore, in this study, we would like to present the technological and formal integration model as an ITS model which acknowledges changes in the fields of technology and education. As a technological integration model, the integration model of traditional Symbolic Artificial Intelligence and Artificial Neural Networks was presented. As a formal integration model, three integration models were presented according to (a) the process of learning diagnosis (b) learners' action behaviors (c) intelligence service respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.545-552
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• 1998

본 연구에서는 prolog을 저자 언어로 사용한 퍼지 지능형 튜터링 시스템을 습득 모듈, 튜터링 콘크롤러, 전문가 지식의 3부분으로 구성하여 UNSW prolog로 실행시켰다. 습득 모듈은 기존의 지식에 새로운 정보를 첨가하여 사용하는 모듈이고 튜터링 콘트롤러는 시스템 사이의 정보를 상호 조정하는데 사용한다. 전문가 지식은 전문가의 지식을 저장한 내부 지식 베이스로서 가르칠 내용에 대한 정보와 해를 구하는 해결 모듈을 포함하고 있다. 특히 애매한 지식 처리를 위하여 퍼지 이론을 적용하였다. 하지만 지능형 튜터링 시스템의 구현을 위하여 먼저 고려해야 할 것이 전문가 지식에서 지식의 변환 방법이다. 그러므로 본 논문에서는 frame과 시멘틱 네트의 성질을 결합하여 계측적 frame 상태로 지식을 포현하였다. 계층적 frame에서 설정된 frame을 goal을 나타내게 하여 G frame이라 하였다. G-frame을 AND-OR 그래프 특성에 따라서 prolog언어를 저자 언어로 사용하여 퍼지 지능형 튜터링 시스템을 설계 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.430-431
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• 2023

교육 분야에서는 각 학생의 특성과 요구에 부응하는 개인화 교육의 중요성이 증가하고 있다. 이에 따라 인공지능 기반의 튜터링 시스템, 특히 대화 기반의 튜터링이 주목받고 있다. 본 연구는 GPT-3.5-turbo 를 사용하여 데이터를 생성하는 과정에서 프롬프트 설계의 중요성과 인간의 감수 과정의 필요성을 확인했다. 또한, 자동 평가 방법을 제안하여 데이터의 품질과 유용성을 평가하였다.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.369-386
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• 2005

Although Intelligent Tutoring System(ITS) offers individualized learning environment that overcome limited function of existent CAI, and consider many learners' variable, there is little development to be using at the sites of schools because of inefficiency of investment and absence of pedagogical content knowledge representation techniques. To solve these problem, we should study a method, which represents knowledge for ITS, and which reuses knowledge base. On the pedagogical content knowledge, the knowledge in education differs from knowledge in a general sense. In this paper, we shall primarily address the multi-complex structure of knowledge and explanation of learning vein using multi-complex structure. Multi-Complex, which is organized into nodes, clusters and uses by knowledge base. In addition, it grows a adaptive knowledge base by self-learning. Therefore, in this paper, we propose the 'Extended Neural Logic Network(X-Neuronet)', which is based on Neural Logic Network with logical inference and topological inflexibility in cognition structure, and includes pedagogical content knowledge and object-oriented conception, verify validity. X-Neuronet defines that a knowledge is directive combination with inertia and weights, and offers basic conceptions for expression, logic operator for operation and processing, node value and connection weight, propagation rule, learning algorithm.

• 한국정보교육학회:학술대회논문집
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• 2007.08a
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• pp.71-75
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• 2007

오늘날 지능형 교수 시스템은 과거와는 달리 전문영역 지식, 학습자 지식과 융통적인 개별 학습과 개인교수를 지원하기 위한 교수 전략에 대한 지식이 사용되고 있다. 학습자들이 배웠던 내용이 무엇인지를 설명하고 가르칠 도메인 지식을 전문영역 지식으로 표현한다. 교수법 모듈은 학습을 제어하거나 가르치기 위한 모든 결정을 한다. 학생 모형은 학습자의 지식을 기술하고 학습자 개개인에 대한 특정한 정보를 저장한다. 본 논문에서는 지능형 교수 시스템의 구성 요소인 학습자 모형의 지식을 기존의 인공지능에서의 지식 표현 기법인 생성 시스템의 절차 지식을 온톨로지를 사용하여 설계하였다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.694-696
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• 1998

지능형 재활 교육 시스템은 학습 대상이 정상인이 아닌 발달 장애인이라는 점과 학습자 단독으로 학습이 어렵다는 점이 일반적인 지능형 교육 시스템과 다르다. 이러한 교육 시스템은 학습자 단독 학습이 아닌 학습 보조자가 학습자의 옆에서 학습을 보조하는 형태이므로 시스템과 학습 보조자와의 연계가 시스템 구현시 중요한 부분이라고 할 수 있다. 그러므로 지능형 교육 시스템의 핵심이라 할 수 있는 Student Model의 설계 역시 학습 보조자의 개입에 대한 자유도를 어느 정도 허락하는 것인가가 주된 목표일 것이다. 본 논문에서는 이러한 점을 고려한 지능형 교육 시스템에서의 Student Model을 구현한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1061-1065
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• 2004

The knowledge-based society of the 21st century requires effective education and learning methods in each professional field because the development of human resource determines its competence more than any other factors. It is highly desirable to develop an intelligent tutoring system, which meets ever increasing demands of education and learning. Such a system should be adaptive to each individual learner's demands as well as the continuously changing state of the learning process, thus enabling the effective education. The development of a learning environment based on learner modeling is necessary in order to be adaptive to individual learning variants. An intelligent learning environment is being developed targeting the heritage education, which is able to provide a customized and refined learning guide by storing the content of interactions between the system and the learner, analyzing the correlations in learning situations, and inferring the learning preference from the learner's learning history. This paper proposes a heritage learning system of Bulguksa temple, integrating the ontology-based learner modeling and the learning preference which considers perception styles, input and processing methods, and understanding process of information.

• Journal of Korea Game Society
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• v.18 no.4
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• pp.75-82
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• 2018

With the development of information and communication technology, various methods have been tried to provide learners with a fun educational environment through fun and interest. It is a good example to utilize technologies such as games and robots in education for edutainment and game-based learning. In this study, we propose an intelligent rhythm education system using user data collection and analysis for humanoid robot rhythm generation. To do this, the user selects music and inputs rhythm information according to the selected music. The robot utilization data of this user extracts patterns through collection and analysis. Patterns are based on frequency, and FFT similarity comparison method is applied when past data is insufficient. The proposed method is validated through experiments of kindergarten children.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.226-230
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• 2009

Intelligent Tutoring System (ITS) is a procedure of analyzing collected data for teaming, making a strategy and performing adequate service for learners. To perform suitable service for learners, modeling is the first step to collect data from the process of their learning. The model, however, cannot be authentic if collected data can contain learners' inconsistent behaviors or unpredictable learning inclination. This study focused on how to sort normal and abnormal data by analyzing collected data from learners through visualization. A model has been set up to assort unusual data from collected learner's data by using DOLLS-HI which makes possible to diagnose learner's learning propensity based on housing interior learning contents in the experiment. The created model has been confirmed its improved reliability comparing to previous one.