• 대한공업교육학회지
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• 제30권2호
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• pp.72-81
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• 2005

The purpose of this study is to do research on correlation between multiple intelligence and e-Learning strategy, which can be used to develop and strengthen e-Learning strategy. The subject was 183 college students of engineering at C university who had ever taken a lesson through e-Learning. Two items are investigated in these college students. One is whether there is a gap and any gender-related difference in multiple intelligence and e-Learning strategy, and the other is what multiple intelligences have an effect on e-Learning strategy. The e-Learning strategy developed by In-Sock Lee and the instrument by Yong-Lin Moon were used. The results of this study are as follows. First, it appeared that there was a difference between gender in musical intelligence and naturalistic intelligence. The average of musical intelligence was higher in female collegian, while the average of naturalistic intelligence was higher in male collegian. But there was no gender-related difference in using e-Learning strategy. Second, it appeared that multiple intelligence gave an explanation of self-direction intelligence up to 31.1%, expression strategy 20.35%, and information processing strategy 16.6%. The results of this study showed that logical-mathematical intelligence affected all of three e-Learning strategies. So, new curriculum which can make use of logical-mathematical intelligence needs to be developed so as to devise efficient e-Learning strategies.

• Smart Structures and Systems
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• 제24권6호
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.422-425
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• 2004

Many believe that electronic distance teaming education transform higher education, saving money and improving learning qualify So, the open University, which teaches around 280,000 students at a distance, is examining the adaption of its distance teaching methods for the internet. But, there are only one type of distance learning education of one way direction. To understand all of a student which selected some of e teaming course, teacher must check that how many student to understand and what is the difficult problems. Without checking this condition, It will be a very difficult and boring distance learning course. In this paper, we introduce of intelligent learning contents of full duplex direction that teach understanding student and not understanding student. The computer simulation results confirms that full duplex e learning system has been proven to be much more efficient than one way direction which not considering about understanding problems.

• 디지털콘텐츠학회 논문지
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• 제19권7호
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• pp.1263-1270
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• 2018

본 연구는 개발도상국 고등교육을 위한 이러닝 플랫폼에 대하여 연구하였다. 먼저 ICT기술환경 등 이러닝 환경요인과 개발도상국을 위한 아세안사이버대학(ACU) 프로젝트를 소개한 후, 개발도상국 이러닝 플랫폼 사례로서 캄보디아 사례를 제시하였다. 캄보디아의 국가교육정책 및 ICT환경, 현지의 이러닝 수요 및 환경요소를 분석하였으며, 분석 결과에 따른 이러닝 전략과 세부방안을 도출하고 이러닝 플랫폼 C-MOOC Net을 제안하였다. 제안된 방법을 검증하기 위하여 C-MOOC Net 시스템의 프로토타입을 공개소프트웨어 기반으로 개발하여 실제로 운영한 결과 C-MOOC 허브의 연계, 현지 언어의 지원, 선호강좌의 개인화 등록 등 요구사항을 충족함을 확인하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제4권1호
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• pp.8-12
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• 2012

The purpose of this study is to review the possible effect of the learning paradigm shift from traditional method to ubiquitous learning. What are the societal issues that need to be address in order to design a new pedagogical platform trending from e-learning to m-learning and now the u-learning? That without the proper study of how learning environment may affect the learning process of an individual will lead to poor quality of education. This new era of learning environment offer a big opportunity for "anytime, anywhere" learning. Thus, Lifelong learning is at hand of everyone. Maximizing the benefit of new trend will be a great help and addressing the limitations will lead to quality education.

• 산업공학
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• 제18권1호
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• pp.10-21
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• 2005

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. In this research we compare the performance of Naive Bayesian learning and Centroid-Based Classification using the different data set of an on-line shopping mall and a credit card company. We analyze which method performs better under which conditions. We compared classification accuracy of them which depends on structure and size of train set and increasing numbers of class. The experimental results indicate that Naive Bayesian learning performs better, while Centroid-Based Classification is more robust in terms of classification accuracy.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.71-82
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• 2024

This paper proposes a new communication system for e-learning applications to mitigate the negative impacts of COVID-19 where the online massive demands impact the current commu-nications systems infrastructures and capabilities. The proposed system utilizes high-altitude platforms (HAPs) for fast and efficient connectivity provision to bridge the communication in-frastructure gap in the current pandemic. The system model is investigated, and its performance is analyzed using adaptive antenna arrays to achieve high quality and high transmission data rates at the student premises. In addition, the single beam and multibeam HAP radio coverage scenarios are examined using tapered uniform concentric circular arrays to achieve feasible communication link requirements.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.160-170
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• 2022

COVID pandemic has reshaped the world as it has been known to us and the education system is one of the most affected by it. Due to social distancing, quarantines and isolations have made it impossible for the knowledge transition to the masses using conventional methods. For cope with pandemic, the only other way available for some of the fortunate countries is the use of E-learning having somewhat the same traditional teaching method. This paper is concerned with the study of the preparedness of the learning system in some Sudanese universities due to the impact of the COVID-19 pandemic. Critical analysis has been performed to evaluate the current developing scenario, usage of the facilities available in open-source platforms, and the interaction of the universities folks with e-learning systems. The impact of such measures has been thoroughly investigated in this paper for Sudan which is already deprived of a proper education system. The investigation shows that the interact of the staff and the students with the system was acceptable where more than 85% of those enrolled to the system were interact properly and efficiently. The lecturers conducted through the platform were attended with more than 75% of the students. We also found that most of the lecturer were avoid to exam students by utilize the platform; where only 45% of the uploaded courses were conducted exams over Moodle platform. As Moodle is an open source and still need to be improved to be used for high examination credibility.

• International Journal of Internet, Broadcasting and Communication
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• 제4권2호
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• pp.12-16
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• 2012

This paper presents a learning framework that fits the digital age - an e-Friendly PLE. The learning framework is based on the theory of connectivism which asserts that knowledge and the learning of knowledge is distributive and is not located in any given place but rather consists of the network of connections formed from experiences and interactions with a knowing community, thus, the newly empowered learner is thinking and interacting in new ways. The framework's approach to learning is based on conversation and interaction, on sharing, creation and participation, on learning not as a separate activity, but rather as embedded in meaningful activities such as games or workflows. It sees learning as an active, personal inquiry, interpretation, and construction of meaning from prior knowledge and experience with one's actual environment.

• International Journal of Contents
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• 제4권2호
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• pp.19-23
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• 2008

This paper presents a novel method to construct a personalized e-Learning system based on dynamic estimations of item parameters and learners' abilities, where the learning content objects are of the same intrinsic quality or homogeneously distributed and the estimations are carried out using IRT(Item Response Theory). The system dynamically connects the test and the corresponding learning procedures. Test results are directly applied to estimate examinee's ability and are used to modify the item parameters and the difficulties of learning content objects during the learning procedure is being operated. We define the learning unit 'Node' as an amount of learning objects operated so that new parameters can be re-estimated. There are various content objects in a Node and the parameters estimated at the end of current Node are directly applied to the next Node. We offer the most appropriate learning Node for a person's ability throughout the estimation processes of IRT. As a result, this scheme improves learning efficiency in web-base e-Learning environments offering the most appropriate learning objects and items to the individual students according to their estimated abilities. This scheme can be applied to any e-Learning subject having homogeneous learning objects and unidimensional test items. In order to construct the system, we present an operation scenario using the proposed system architecture with the essential databases and agents.