• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.208-210
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• 2004

오늘날 인터넷상에서 존재하는 않은 정보들은 다양한 사용자의 개인 특성에 안게 새로운 정보의 지식으로 제공되어지기를 원한다. 기존의 연구는 단일 학술 기법을 통해 정보를 추출했으나 사용자에게 보다 의미 있는 정보를 제공하기 위해 다중 전략 학습 기법인 PMSL(Personalized Multi-Strategy Learning) 모듈 시스템을 제안하고자 한다. PMSL 모듈은 인터넷의 정보를 여과하여 필터링하고, 사용자 개인화의 키워드를 중심으로 연관된 객체를 추출한다. 이때 연관된 객체 추출시 대용량 데이터에서 시간적, 공간적면에서 효율적인 연관 탐색 기법인 Fp-Tree와 Fp-Growth 알고리즘을 적용시킴으로 결과의 효율성을 높이고자 하였으며, 연관규칙의 문제점을 보완하기 위해 가중치 기법인 TF＊IDF 학습 기법을 적용시켰다. PMSL 모듈을 실행한 결과 기존 학습 기법에 비해 보다 더 의미 있는 연관 지식을 추출하게 되었다.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.35-43
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• 2001

This thesis proposes a diagnostic formula for student's responses based on linguistic variable concept of fuzzy that makes domain expert to input the kernel elementeasily that constructs domain independent student module. And the domain expert can construct the rule with linguistic variable that is used to inference student's recognition state. This study designs a student module that can inference student's recognition state using this rule represented by linguistic variable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.599-601
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• 2009

In currently being adopted as a e-leaning standard, SCORM it is difficult to provide the customized contents to a learner by changing the learner's level at runtime, and to control selective studying. So, we designed and implemented the customized contents organization engine(CCOE) in order to complement SCORM's faults in this paper. The CCOE consists of a level evaluation module, a contents re-organization module and a question item selection module. A level evaluation module evaluates the learner's level based on a question item reaction theory. And a question item selection module selects some random items by each level or by considering the learner's level which is then provided to a studying before evaluation, a section evaluation, and a quiz. And then this module transmits the selected items to the contents reorganization module for providing the quiz. A contents re-organization module selects the customized contents based on the learner's level by searching the tagged difficulty to the content, and creates the sequence with the selected items and the transmitted items from the question item selection module. If proposed in this paper CCOE is applied, the higher effectiveness of learning is expected by providing the customized learning contents based on the re-evaluated learner's level by each section.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.105-115
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• 2012

This study paid attention to the possibility of broadcasting contents as a learning resource, which promoted the knowledge composition and the process of creation from the software having enriched contents not a delivering tool for the information in one direction. and tried to implement it thru e-PBL, which is one of teaching-learning models in e-learning. In order to implement the possibility of broadcasting contents in the e-PBL enviroment as a learning resource, the study focused on the design and development of e-PBL based on the broadcasting contents and found out the educational possibility for the broadcasting contents as the learning resource in e-PBL enviroment. This study focused on the design of learning module and development process which integrated strategic plans to maximize the utilization of broadcasting contents including development of online learning community. Also, This is verified by applying the learning module was to prove a differentiation.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.395-399
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• 2001

This paper describes modular fuzzy inference systems(MFIS) with adaptive capability to extract fuzzy inference modules from observation data through the learning process. The proposed MFIS is based on the structural similarity to Tagaki-Sugeno fuzzy models and a modular neural architecture. The learning of MFIS is done by assigning new fuzzy inference modules and by updating the parameters of existing modules. The fuzzy inference modules consist of local model network and fuzzy gating network. The parameters of the MFIS are updated by the standard LMS algorithm. The performance of the MFIS is illustrated with adaptive control of a nonlinear dynamic system.

• The Journal of Korean Association of Computer Education
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• v.22 no.1
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• pp.79-86
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• 2019

This study examines the impact of modular robot programming education on middle school informatics curriculum learning motivation. For this purpose, the experiment was conducted with a experimental group of 25 people and a control group of 25 people, and modular robot programming education and learning motivation test were used as research tools. As a result of processing the results of the learning motivation test paper with the independent sample t-test and the paired t-test, the experimental group had 9.36 points higher learning motivation than the control group and 15.44 points higher than the pre-test. In particular, it significantly affected the improvement of all the sub-components of the learning motivation, and among them, it greatly affected the enhancement of attention, relevance and satisfaction. In conclusion, it can be seen that modular robot programming education has a positive effect on improving students' motivation to learn the informatics curriculum.

• 대한공업교육학회지
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• v.38 no.2
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• pp.89-113
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• 2013

The study started from the point that learners should be basically equipped to quickly respond to changes in demand for future human resources efficiently and effectively, and an attitude to take part in learning voluntarily should thus be cultivated. To this end, the author applied the TAI model based on a module as a class strategy to solve problems related to several classes occurred in specialized high schools. This application of the TAI model was also motivated by the necessity for designing an appropriate teaching-learning method that encourages improvement of self-learning capacity, consistent learning motivation, and willingness rather than external factors. Through this work, the author aims to heighten the interest of learners and improve endurance in learning. The study results are as follows. First, the learning unit was structuralized as a module and then learning stages were proceeded with so that capacity to adapt to learning would improve. The achievement standard (learning goal) was structuralized in a module type by analyzing and reorganizing the textbook considering the link between the actual practice field and a curriculum based on subject characteristics. Through the process of module type learning stages, the student's capacity to ascertain characteristics of units and to adapt to learning both improved. Second, through application of a TAI model based on a module, Self-Directed Learning capacity and capacity to adapt to a new field improved. By applying the module, Self-Directed Learning could be accomplished more effectively than in the existing passive learning environment. By grafting cooperative learning of the TAI model, students had greater interest and achievement in classes, self-confidence and community consciousness, and an opportunity to broaden their thinking. In particular, improvement of self-confidence is effective in cultivating the capacity required in industrial society to transcend the learning of simple functions and knowledge, as well as the capacity to adapt to new environments. Third, by solving tasks focused on fields related to industrial sites, not only actual survey capacity but also additional capacity to identify and solve tasks through various experiences improved. Furthermore, it was helpful for students to have interest and motivation about their own life and learning to cultivate the qualities and capacity to adapt to the working world where new knowledge and technology rapidly change. Fourth, by applying a standard-based assessment system for technical subjects introduced in 2012 to model design for learning plans, clearer and more objective assessment criteria were arranged, and individual learning through instruction at each achievement level could be accomplished. This improved achievement level of individual learners was helpful in reaching achievement goals at specific levels by overcoming the disadvantages of cooperative learning in each group.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.537-547
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• 2014

In this paper, the ALT (ALTernative) board and a NetLogo extension module are developed for the active participatory simulation (APS) learning. Through the participatory simulation with HubNet each student can attend the experiment as one of clients. Only one HubNet server, however, is able to use an external device so that the bifocal modeling based learning with multiple users is impossible. In order to overcome the drawback, and enable clients participate into the experiment and collect the experimental data and the measured data, an ATmega 32 based board and its firmware are developed. In addition, Java extension module based on TCP/IP socket interfaces is developed to exchange the data with HubNet server. Finally, we show some NetLogo program examples to use the developed hardware and software for APS and seek the way to use them for science education.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.736-741
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• 2006

The design of a classification system generally involves data acquisition module, learning module and decision module, considering their functions and it is often an important component of intelligent systems. The learning module provides a priori information and it has been playing a key role for the classification. The conventional learning techniques for classification are based on a winner take all fashion which does not reflect the description of real data where boundarues might be fuzzy Moreover they need all data for the learning of its problem domain. Generally, in many practical applications, it is not possible to prepare them at a time. In this paper, we design an adaptive classification model using incremental training fuzzy neural networks, FNN-I. To have a more useful information, it introduces the representation and membership degree by fuzzy theory. And it provides an incremental learning algorithm for continuously gathered data. We present tie experimental results on computer virus data. They show that the proposed system can learn incrementally and classify new viruses effectively.

• 한국정보교육학회:학술대회논문집
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• 2007.08a
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• pp.267-272
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• 2007

학교 교육에서 문해력과 수리력에 비해 그 중요성이 간과되고 있는 공간 지각 능력과 도해력을 학습하기 위해서 학습자 중심의 지도 그리기 교육이 실제화 되어야 한다. 따라서 이 글에서는 보다 더 실제적 이고 효과적인 지도교육을 위한 지도그리기모듈을 구현하고자 한다. 특히 사회과의 경우 사고의 방법과 과정을 중요시 하는 교육목표를 가지고 있기 때문에, 현재의 저학년 초등교과교육 중 지도 그리기 학습의 문제점을 살펴보고 구체적 조작기의 아동을 위한 공간 능력의 향상과 구체물의 평면화 등 지도 그리기 교육의 목표를 수월하게 도달하기 위한 모듈을 구현하여 초등 지리 교육의 수월성과 함께 학습자의 수준에 맞는 흥미로운 학습을 도모하고자 한다.