• Information Systems Review
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• v.12 no.3
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• pp.19-48
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• 2010

This study focused on characterizing various factors in order for learners to maintain their interests in learning and to maximize learning effects as the top priority purpose of university e-Learning, on the basis of results of conceptual studies on existing e-Learning and practical studies, and then on examining them practically. It also analyzed which factors would have greater influence on learning effects of e-Learning in general. Moreover, in comparison with existing numerous studies which examined only factor such as learning effects of e-Learning, it analyzed such things in detail according to division into three items such as learning satisfaction, learning transfer and learning recommendation. To achieve such purposes of the study, it characterized and set 3 factors such as learning contents, instructional design and user convenience on the assumption that such factors have a significant influence on learning effects of e-Learning. Moreover, the factor of learning contents includes 3 detailed elements, i.e., learning issue and objective, knowledge information, and consistency and propriety, and the factor of instructional design includes 4 detailed elements, i.e., interest and sympathy, interaction, contents presentation and explanatory strategy. Lastly, the factor of user convenience includes 2 detailed elements such as screen configuration, and check-up of contents and teaching schedule. According to analytical results, it showed all 3 factors such as learning contents, instructional design and user convenience have a significant influence on learning effects of e-Learning(i.e., learning satisfaction, learning transfer and learning recommendation). In more detail, it showed the learning issue and objective from the factor of learning contents have the greatest influence on learning satisfaction of e-Learning. Then, it is the most important to set the learning issue and objective with given priority to learners and set the learning objective estimable, in order to raise the learning satisfaction. It showed the contents presentation from the factor of instructional design on the learning transfer. Therefore, it is the most important to structuralize mutual relation and presentation orders to promote learning systematically and to let learners access to such things, for the purpose of raising the learning transfer. Moreover, it showed the interest and sympathy from the factor of instructional design has the greatest influence on the learning recommendation. Thus, it is the most important to promote learners' interests to the maximum using well-timed media, and to give a lecture enough to arouse learners' sympathy.

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.1-9
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• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.133-152
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• 2004

As the Internet facilitates the rapid increase of information availability, the study on SDI service that provides users with relevant document in a timely manner has been developed. However, the practical use of this service has been low. This thesis aims at analyzing the reasons for this and developing relevance feedback based SDI system to improve the performance of the existing SDI system. Experimental systems that are developed for this study are SDI system based on users' minimum intervention feedback, SDI system based on perfect automation feedback, and SDI system based on users' maximum intervention feedback. The fourth system that utilizes the traditional SDI system is also studied to evaluate the level of performance improvement of the newly developed three types of SDI system. As a result of this study, SDI system based on users' maximum intervention feedback showed greatest performance improvement. The next performance improvement happened in order of SDI system based on perfect automation feedback, SDI system based on users' minimum intervention feedback, and the traditional SDI system. Feedback based systems showed greater performance improvement as they went through more feedback processes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4139-4147
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• 2014

The aim of this study was to review the characteristics of teacher education curriculum and reform tendency between China and Korea. This study used literature analysis of various studies, catalogs, documents of education universities in China and Korea. The results were as follows. Some common features in the teacher education curriculum were observed, such as the purposes of education, constituent area of the curriculum, and subjects, such as pedagogy and practice teaching. Other differences included that China requires more credits for graduation than Korea, but the elective subjects are assigned fewer credits. In both countries, it is necessary to increase the relevant subjects (pedagogy, practice teaching) for the specialty of a preliminary teacher and establish a permanent system for the curriculum needs of students. In terms of reform tendency, both countries should change the training concept and teacher education philosophy, mainly on enhancing quality-oriented education, emphasizing the students' sustainable self development ability, as well as attaching importance to concept of lifelong education. These results are expected to be helpful in improving the teacher education curriculum in China and Korea.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.15-22
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• 2020

In order to strengthen the disaster prevention phase and the management of social disasters, we will examine the plan of To-Be disaster management system interconnected by using intelligent information technologies such as IoT, Cloud, Big Data, Mobile and AI. The disaster management system can be upgraded by constructing an intelligent infrastructure based on Big Data analysis of the disaster signals before and after the disasters generated by private mobile and IoT. Big Data of disaster Signals can be customized to users in a timely manner through AI methodologies of supervised and unsupervised learning and reinforcement training. In the long term, it is expected that not only will the capacity of disaster response be improved, but the management ability centering on prevention will be enhanced as well.

• Journal of the Korean Society for Library and Information Science
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• v.34 no.4
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• pp.5-26
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• 2000

The purpose of this study was to measure performance of university libraries, especially investigating the components of service quality and their relationship to the customer satisfaction. The result of the study was summarized as follows: First, the factors on satisfaction of library service revealed 12 factors such as access of information, quality of employees, suitable collections, issues related to civil petitions, equipments and facilities, timeliness, operating hours, use of information technology, library user education, reference service, public relation and individual service. Second, the factors of library service on customer satisfaction showed the following primary factors: suitable collections, issues related to civil petitions, access of information, equipments and facilities, timeliness, public relation, reference service, operating hours, and individual service. Third, the components of library service on customwe satisfaction showed the following primary components: availability, the number of books and journals, facilities of air conditioning, public relation, usefulness of retrieval system, waiting time for Internet use, operating hour, speed of repairs, receipt of civil petitions, use of non-book materials.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.121-128
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• 2024

This study introduces specializer high school students , as a fusion education method using Inventor software to design a robot arm, which is then 3D printed and controlled by an Arduino microcontroller. Students gain practical experience and have the opportunity to integrate knowledge and skills from various academic fields. They start by designing in CAD software, proceed to fabricate actual robot arm components using 3D printing technology, and finally program and control the assembled robot arm. This interdisciplinary education enhances students' problem-solving abilities, fosters creativity, and increases their motivation to learn. To implement such educational endeavors in actual curricula, ongoing teacher support and appropriate resources are essential. This research serves as a foundational exploration of the applicability of fusion education in future learning contexts.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.13-38
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• 2024

As economic uncertainties have increased recently due to COVID-19, there is a growing need to quickly grasp private consumption trends that directly reflect the economic situation of private economic entities. This study proposes a method of estimating private consumption in real-time by comprehensively utilizing big data as well as existing macroeconomic indicators. In particular, it is intended to improve the accuracy of private consumption estimation by comparing and analyzing various machine learning methods that are capable of fitting ultra-high-dimensional big data. As a result of the empirical analysis, it has been demonstrated that when the number of covariates including big data is large, variables can be selected in advance and used for model fit to improve private consumption prediction performance. In addition, as the inclusion of big data greatly improves the predictive performance of private consumption after COVID-19, the benefit of big data that reflects new information in a timely manner has been shown to increase when economic uncertainty is high.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.427-432
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• 2012

The article herein suggested a compound repository and a descriptive method to develop a compound knowledge process. A data target saved in a compound knowledge repository suggested in this article includes all compound knowledge meta data and digital resources, which can be divided into the three following factors according to the purpose: user roles, functional elements, and service ranges. The three factors are basic components to describe abstract models of repository. In this article, meta data of compound knowledge are defined by being classified into the two factors. A component stands for the property about a main agent, activity unit or resource that use and create knowledge, and a context presents the context in which knowledge object are included. An agent of the compound knowledge process performs classification, registration, and pattern information management of composite knowledge, and serves as data flow and processing between compound knowledge repository and user. The agent of the compound knowledge process consists of the following functions: warning to inform data search and extraction, data collection and output for data exchange in an distributed environment, storage and registration for data, request and transmission to call for physical material wanted after search of meta data. In this article, the construction of a compound knowledge repository for recommendation system to be developed can serve a role to enhance learning productivity through real-time visualization of timely knowledge by presenting well-put various contents to users in the field of industry to occur work and learning at the same time.