• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.83-96
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• 2000

본연구는 웹 상에서 원격 협력 학습을 위한 수준별 협력 학습자 진단 및 스케줄링 에이전트의 설계와 구현에 관한 연구이다. 원격 협력 학습은 동일한 학습내용에 흥미를 갖는 아동이 동시에 학습할 수 있는 환경이 필요하며 학습자의 지식 또한 비슷한 수준이어야 효과적인 협력학습을 할 수 있다. 분산 환경의 이질적인 학습자를 모으기 위해서는 좀 더 자율적이고 지능적인 시스템이 필요하며 학습자에 대한 지식을 표현하는 학습자 모델이 요구된다. 이를 위해 에이전트 시스템이 적절하게 사용될수 있으며 학습자의 수준을 판단하기 위한 진단 에이전트와 협력학습이 가능한 여러명의 학습자들을 알맞은 시간과 서버에 연결하는 스케줄링 에이전트를 웹 기반 지능형 교수 시스템에 접목하였다. 학습자 수준을 진단하는 진단 에이전트는 확신도를 높이기 위해 3-모수 로지스틱 확신공식과 시간 가중치 확신인자 공식을 적용하여 신뢰도를 높였다 또한 협력학습의 스케줄링을 위해 다양한 제약조건들의 최적해를 구하기 위해 제약 만족 문제(CSP)로 스케줄링 에이전트를 모델링하였다 본 연구에서 설계 구현한 협력학습자 진단 및 스케줄링 에이전트의 효율성을 살펴보기 위해 여러명의 학습자를 대상으로 실험하였다. 실험을 통해 각 학습자의 지식 수준 진단과 다수의 학습자가 적절한 협력학습을 하기 위한 스케줄링이 매우 효율적으로 이루어짐을 볼 수 있었다.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.67-79
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• 2021

The advent of the 4th Industrial Revolution is also causing many changes in defense operations. Defense reform and the fourth industrial revolution promoted smart defense innovation, and attempts are being made to incorporate cutting-edge science and technology into various fields such as weapons systems and defense operations. Education and training is one of the areas in which information and intelligence are urgently needed in the spirit of defense operations. Due to the nature of defense education and training, which aims to fight against the enemy, there is no emphasis on psychological training in the field rather than informatization, but in developed countries with various experiences of modern warfare, investment and vitalization of education and training are vital. Through this, efforts are being made to foster soldiers with problem-solving skills in uncertain battlefields. The informatization and intelligence of defense education and training is no longer a matter that can be delayed, and the innovation of education and training using cutting-edge science and technology can be said to be an age-old task to improve the results of education and training in the fourth industrial revolution. The purpose of this is because the application of related technologies is not the goal itself as the 4th Industrial Revolution arrives, but it has been made possible through the rapid advancement of science and technology that has made it difficult to realize education and training, even though it has long been desired. Ultimately, education and training data will be integrated and artificial intelligence-based intelligent learning systems will maximize the performance of education and training, thereby improving the combat readiness.

• The Journal of Korean Association of Computer Education
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• v.9 no.5
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• pp.31-39
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• 2006

The change into the knowledge based information society requires a transformation of educational paradigm. Accordingly, intelligent learning and distance education are attracting a fair amount of attention. To apply the instructional learning method in this field, we need to consider a individualization of learning, as it were, abstraction of fact and path through learning, which is based on learner's traits, this focus entails a argument for individualized reasoning strategy. Therefore, in this paper, we design a learner's cognitive union, which is based on X-Neuronet(eXtended Neuronet), represent learner's hierarchical knowledge is able to self-learn, and grows adaptive union by proprietor. Additionally, we propose a individualized reasoning strategy, which relies upon learner's cognitive union, and verify the validity.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.71-77
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• 2008

This study conducted to tried to find a way of on-line assessment of learner's interest and comprehension during interactive learning process. The result of experiment confirmed hat learners' behavior patterns acquired from log data could be good predictors of learner's level of interest and comprehension in actual performance on KORI program. To predict learning outcome depending on the behaviors of individual learners, self-efficacy and mastery goal orientation were measured as individual differences. Then, participants were asked to use TA program KORI program at home for ten days and their response patterns were recorded through network. After using KORI, the levels of interest and comprehension were measured. As the result of multiple regression analysis, each learner's interest and comprehension were predicted depending on the combination of log data captured on real-time. This prediction process was done differently depending on learners' characteristics. Since equations which predict learners' interest and comprehension are different depending on learners' characteristics, differential interfaces should be provided depending upon changes in their level of interest and comprehension.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.51-60
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• 2006

The goal of qualitative analysis is to capture and formalize qualitative and intuitive knowledge about physical world. Qualitative reasoning has been successfully applied to electric and mechanical mechanism domains, in which most of reasoning has focused on simulation. This paper introduces a qualitative comparative analysis technique which predicts how a change in a given situation propagates. We developed a comparative analysis technique which extends previous research by including a reasoning technique about the relative rate of the change of a parameter. Previous research focuses only on the relative change of a parameter. Causal model for the given situation is generated from qualitative domain model. The propagation by the change in causal relations are traced by applying our comparative analysis. By providing explanation as well as prediction for the given change, our technique is expected to be used in design, diagnosis, intelligent tutoring system, environmental evaluation.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.303-320
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• 2024

This study presents the development and performance evaluation of a custom GPT-based chatbot tailored to provide solutions following Polya's problem-solving stages. A beta version of the chatbot was initially deployed to assess its mathematical capabilities, followed by iterative error identification and correction, leading to the final version. The completed chatbot demonstrated an accuracy rate of approximately 89.0%, correctly solving an average of 57.8 out of 65 image-based problems from a 6th-grade elementary mathematics textbook, reflecting a 4 percentage point improvement over the beta version. For a subset of 50 problems, where images were not critical for problem resolution, the chatbot achieved an accuracy rate of approximately 91.0%, solving an average of 45.5 problems correctly. Predominant errors included problem recognition issues, particularly with complex or poorly recognizable images, along with concept confusion and comprehension errors. The custom chatbot exhibited superior mathematical performance compared to the general-purpose ChatGPT. Additionally, its solution process can be adapted to various grade levels, facilitating personalized student instruction. The ease of chatbot creation and customization underscores its potential for diverse applications in mathematics education, such as individualized teacher support and personalized student guidance.