• Journal of Technology Innovation
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• v.12 no.3
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• pp.1-24
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• 2004

E-Learning is another way of teaching and learning. E-learning is a networked phenomenon allowing for instant revisions and distribution, and goes beyond training and instruction to the delivery of information and tools to improve performance. The benefits of e-learning are many, including cost-effectiveness, enhanced responsiveness to change, consistency, timely content, flexible accessibility, and providing customer value. The proponents of e-learning stress the importance of using communities of interest to support and enhance the learning process. They also emphasizes that people learn more effectively when they interact and are involved with other people participating in similar endeavors. Although the role of e-learning in higher education has significantly increased, the resistance to new technology by professors and lecturers in university and colleges worldwide remains high. The purpose of this study is to identify the determinants of attitude and planned behavior toward e-learning class in universities. A survey methodology was used to investigate a proposed model of influence, and structural equation modeling was used to analyze the results. The hypothesized model was largely supported by this analysis, and the overall results indicate that attitude toward e-learning systems is mostly influenced by the perceived ease of use as well as the level of perceived usefulness, where both factors are influenced by years of experiences in using cyber system and the technical support level. As in other TAM related research, it can be concluded that the perceived ease of use and perceived usefulness contribute to the future use of e-learning system.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.155-162
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• 2017

This paper suggests efficient learning improvement method of computer use instruction based on flipped learning. Traditional computer use classes were difficult to practice and collaborative with sufficient lectures. However, we used KOCW (Korea Open Courseware) as a footsteps in the class using the flipped learning method and learned in advance before entering the classroom. In the classroom, we conducted collaborative hands on class based on mutual discussion. After the instruction, we measured learning motivation and satisfaction by gender, grade, and major using the motivation test tool. The results showed that degree of attention awareness, perception of class relevance and perception of learning satisfaction were analyzed as 'very satisfied' and 'satisfied' more than 90%.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.238-244
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• 2020

The development and distribution rate of smartphones have progressed so rapidly that it is safe for the entire nation to use them in the smart age, and the use of smartphones has become an essential medium for the use of domestic media content, and many people are using various contents regardless of gender, age, or region. Recently, various media outlets have been consuming video content for online learning, indicating that learners utilize video content online for learning. In the previous research, satisfaction studies were conducted according to the type of content, and the improvement plan was necessary because no research was conducted on how to evaluate the learning content itself and provide it to learners. In this paper, we would like to propose a system through evaluation and review of learning content itself as a way to improve the way of providing video content for learning and quality learning content.

• The Journal of Korean Physical Therapy
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• v.31 no.2
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• pp.88-93
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• 2019

Purpose: The aim of the study was to develop a Korean version of an ICF e-Learning tool (KICF e-Learning tool). Methods: The process of translation and adaptation of the ICF e-Learning tool was followed: two translators developed the Korean versions independently, and a consensus version of the translation was then produced. An expert committee, which was composed of five experts from physiotherapy, occupational therapy, speech pathology, and social welfare, reviewed the consensus Korean version to make a beta version of the tool. A field test was conducted to determine if the Korean version of the tool was easy to understand and suitable to use in ICF learning. Feedback from the field test were used for the final adaptation of the KICF e-Learning tool. Results: One-hundred and twenty-six volunteers (40 males and 76 females) were invited to examine the KICF e-Learning tool. The participants reported various levels of ICF knowledge from none to very good. Forty-eight participants reported no knowledge of ICF. The majority of participants (n=84) reported that Korean terms or expression in the tool were easy to understand and one-hundred fourteen participants would recommend the tool to another person. The Korean cases would be helpful for a Korean audience to study the ICF using the tool. Conclusion: The KICF e-Learning tool was developed and is ready for use by the public for the consistency of ICF education. On the other hand, development of an advanced module will be needed.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.77-105
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• 1996

The accuracy of knowledge is a major concern for expert system developers and users. Machine learning approaches have recently been found to be useful in knowledge acquisition for expert systems. However, the accuracy of concept acquired from machine learning could not be analyzed in most cases. In this paper we develop a comprehensive knowledge error analysis methodology for practical use of expert systems. Decision tree induction is an important type of machine learning method for business expert systems. Here we start to analyze with knowledge acquired from decision tree induction method, and extend the results to develop error analysis methodology for general machine learning methods. We give several examples and illustrations for these results. We also discuss the applicability of these results to multistrategy learning approaches.

• Communications of Mathematical Education
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• v.34 no.3
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• pp.299-324
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• 2020

The purpose of this study was to identify high school students' mathematics learning style and its characteristics according to their personality disposition types and to propose mathematics learning strategies fit into each personality disposition type. For this purpose, MBTI personality test and survey to find mathematics learning style for 375 high school students were executed. The results were as follows. First, many students highly evaluated the effects of private education and prefer reference book to textbook. Second, there were significant differences on following variable domains of mathematics learning style such as learning attitude, learning habit(concentrativeness to concept understanding), problem solving strategies(effort for problem comprehension, use of various strategies), self management(metacognition) by MBTI personality disposition types(SJ, SP, NT, NF groups). Third, based on the results, the following mathematics learning strategies fit into each personality disposition type were recommended. SJ type students are needed to effort creative approach for open problem and to use mindmap as mathematics learning strategy. SP type students are needed to fulfill stepwise problem solving process and to effort constantly practice long/short term learning objectives. NT type students are needed to expand opportunity to study with friends and to use SRN(self reflection note) or mathematics journal writings as mathematics learning strategy. NF type students are needed to use mathematics learning note writing activity which include logical basis for each step of problem solving and to invest more time on learning algebra which need meticulous calculation.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.56-66
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• 2023

The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

• Management & Information Systems Review
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• v.37 no.3
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• pp.1-25
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• 2018

This research performed the empirical test for the effects of learning transfer on perceived usefulness, perceived ease of use, self-efficacy and work environment using 390 employees who have experienced e-learning in domestic and foreign companies. Analyzed the mediating effects of self-efficacy and work environment in addition to direct effect of each factor on learning transfer. The results showed that perceived usefulness and perceived ease-of-use of e-learning learner had a positive(＋) effect on self-efficacy and a positive influence on supervisor and peer support and organizational climate. Self-efficacy showed a positive effect on learning transfer, and supervisor support, peer support and organizational climate had a positive influence on learning transfer as well. Perceived usefulness also had a positive effect on learning transfer. However, perceived ease-of-use had no significant effect on learning transfer. As a result of the mediating effect analysis, self-efficacy and work environment were analyzed to have mediating effects between perceived usefulness, perceived ease of use, and learning transfer. The implications of this study are as follows. First, this study designed a new research model that reflects factors influencing the effect of learning transfer on acceptance of e-learning that is common in corporate education. It has derived a research model of perceived usefulness and perceived ease-of-use, which were used as mediating variables for external characteristics factors, as independent variables, using self-efficacy and work environment as mediating variables, which were studied as external factors. Second, most of the studies on technology acceptance model and learning transfer are conducted in a single country. The reliability was enhanced by testing the study models using different samples from 26 countries. Third, perceived usefulness and ease-of-use in existing studies have been considered as key determinants of acceptance intention and learning transfer. This study explored the mediating effects of learner and environmental factors on the accepted information technology and strengthened and supplemented the path of learning transfer of perceived usefulness and ease-of-use. In addition, based on the sample analysis of various countries used in this study, it is expected that future international comparative studies will be possible.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.13-23
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• 2021

In this paper, we proposed a framework that generates the trajectory of a single rigid body based on its COM configuration and contact pose. Because we use a smaller input dimension than when we use a full body state, we can improve the learning time for reinforcement learning. Even with a 68% reduction in learning time (approximately two hours), the character trained by our network is more robust to external perturbations tolerating an external force of 1500 N which is about 7.5 times larger than the maximum magnitude from a previous approach. For this framework, we use centroidal dynamics to calculate the next configuration of the COM, and use reinforcement learning for obtaining a policy that gives us parameters for controlling the contact positions and forces.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.2
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• pp.143-153
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• 2009

This paper identifies some natural habits and patterns of children's and adolescents' information seeking and use by drawing a wide range of studies conducted with children and adolescents as study participants. The patterns reported here indicate that children's and adolescents' information seeking and use are affected by the nature of information tasks, the qualities of access tools, their cognitive ability to seek and use information, and their prior knowledge and experience about the tasks and topics given. The findings should provide insights for identifying future research issues as well as for programming the information environments particularly conducive to learning.