• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.455-463
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• 2022

The current study adds to the body of knowledge about the mediation in the causal link between students' perceptions of the utility of eLearning and their learning performance. The data was collected from 500 questionnaires that were delivered to the students at the Vietnam National University of Ho Chi Minh City. Only 422 finished questionnaires were usable for analyses, indicating a responding rate of 84.4%. Multiple regressions were used to investigate causal correlations, whereas Goodman's (1960) techniques were used to investigate mediating relationships. The major findings reveal that both the utility and adoption of eLearning have an impact on students' learning performance, with usefulness being a crucial determinant of eLearning adoption for study. More meaningfully, statistical evidence on the mediation of adopting eLearning for study in the causal linkage from the usefulness of eLearning perceived by students to their learning performance was provided. The relevance of using eLearning for study is stressed in this study, where it is not only one of the key antecedents of their learning performance, but also acts as a mediator between the usefulness of eLearning and learning performance in the research model.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.511-518
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• 2022

Supervised learning based on deep learning has made a leap forward in various application fields. However, many supervised learning methods work under the common assumption that training and test data are extracted from the same distribution. If it deviates from this constraint, the deep learning network trained in the training domain is highly likely to deteriorate rapidly in the test domain due to the distribution difference between domains. Domain adaptation is a methodology of transfer learning that trains a deep learning network to make successful inferences in a label-poor test domain (i.e., target domain) based on learned knowledge of a labeled-rich training domain (i.e., source domain). In particular, the unsupervised domain adaptation technique deals with the domain adaptation problem by assuming that only image data without labels in the target domain can be accessed. In this paper, we explore the unsupervised domain adaptation techniques.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.4
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• pp.67-74
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• 2014

Departmentalized Classroom System is new school operating system to apply social needs. Recent social needs are characterized as learning environment and self-learning system. The purpose of this study is to provide basic data for equal learning environment condition in middle school applying departmentalized classroom system. This study has progressed through analyzing on 11 remodelling case of middle school in Gangwon-Do. The method of this study is visiting middle schools that operate the system, grasping the condition for environment composition, and investigating and analyzing practical use of the environment. The results of this study are summarized as follows: 1) The space compositions for departmentalized classroom system are generally desirable, but some schools take irrational space composition, especially on home base-teacher laboratory, classroom-teacher laboratory. 2) The space area distributions are different in every school. This result is based on not taking standard criterion on space area distribution.

• ETRI Journal
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• v.46 no.2
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• pp.205-217
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• 2024

We propose a bandwidth prediction approach based on deep learning. The approach is intended to accurately predict the bandwidth of various types of mobile networks. We first use a machine learning technique, namely, the gradient boosting algorithm, to recognize the connected mobile network. Second, we apply a handover detection algorithm based on network recognition to account for vertical handover that causes the bandwidth variance. Third, as the communication performance offered by 3G, 4G, and 5G networks varies, we suggest a bidirectional long short-term memory model with time distribution for bandwidth prediction per network. To increase the prediction accuracy, pretraining and fine-tuning are applied for each type of network. We use a dataset collected at University College Cork for network recognition, handover detection, and bandwidth prediction. The performance evaluation indicates that the handover detection algorithm achieves 88.5% accuracy, and the bandwidth prediction model achieves a high accuracy, with a root-mean-square error of only 2.12%.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.81-94
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• 2018

The purpose of this study is to substantiate the affecting factors of informal learning outcomes for professions in various dimensions of an individual and organization. In specific, the study analyzed the effects of learning motivation, job characteristics, and a supportive learning environment which have on task-related knowledge acquisition, adapting to organization and understanding contexts, relationship formation, and improving self-development-ability. The participants of the study were 261 professionals working at four major accounting firms in South Korea. Multiple regression models were applied step by step for analysis. In this study, the informal learning of professionals working at four major accounting firms is influenced by various factors of learning motivation, job characteristics, and a supportive learning environment. The detailed analysis results were as follows. Firstly, peer-support showed the most positive effect on task-related knowledge acquisition. Secondly, for adapting to organization and understanding contexts, task autonomy showed the greatest effect. Thirdly, peer-support was found to be the most important factor for relationship formation. Fourthly, for improving self-development ability, learning goal orientation showed to be the most important factor. The various factors facilitated the professional learning by empirical identification. The study presented practical implications for creating an effective informal learning support environment.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.4
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• pp.259-275
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• 2021

This study explored the usefulness and implications of the Bayesian hyperparameter optimization in developing species distribution models (SDMs). A variety of machine learning (ML) algorithms, namely, support vector machine (SVM), random forest (RF), boosted regression tree (BRT), XGBoost (XGB), and Multilayer perceptron (MLP) were used for predicting the occurrence of four benthic macroinvertebrate species. The Bayesian optimization method successfully tuned model hyperparameters, with all ML models resulting an area under the curve (AUC) > 0.7. Also, hyperparameter search ranges that generally clustered around the optimal values suggest the efficiency of the Bayesian optimization in finding optimal sets of hyperparameters. Tree based ensemble algorithms (BRT, RF, and XGB) tended to show higher performances than SVM and MLP. Important hyperparameters and optimal values differed by species and ML model, indicating the necessity of hyperparameter tuning for improving individual model performances. The optimization results demonstrate that for all macroinvertebrate species SVM and RF required fewer numbers of trials until obtaining optimal hyperparameter sets, leading to reduced computational cost compared to other ML algorithms. The results of this study suggest that the Bayesian optimization is an efficient method for hyperparameter optimization of machine learning algorithms.

• Journal of Distribution Science
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• v.13 no.12
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• pp.113-131
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• 2015

Purpose - In today's era of globalization, the competitive power of enterprises is growing fiercer, calling for organizations to be able to respond flexibly to survive and maintain predominance in competition. In turn, keen competition exists among enterprises for the systematic management of members' knowledge to secure predominance in such competition. Under such circumstances, SMEs must find and utilize positive causes for change that affect organizational performance. The objective of this study is to analyze the structural relationship between four factors known from prior research-a CEO's positive leadership, members' positive life positions, learning organization activities, and job engagement-and organizational performance. Research design, data, and methodology - To achieve this objective, this study established the following four research problems. First, do CEOs' positive leadership, members' positive life positions, learning organization activities, and job engagement affect organizational performance? Second, do CEOs' positive leadership, members' positive life positions, and learning organization activities affect job engagement? Third, do CEOs' positive leadership and members' positive life positions affect learning organization activities? Fourth, does CEOs' positive leadership affect members' positive life positions. Additionally, to achieve the objective of this study, the research model was selected on the basis of a documentary survey of 787 full-time employees at 100 SMEs, which was used to collect related data. Results - The following conclusions were drawn. First, a CEO's positive leadership directly affects members' positive life positions, learning organization activities, and job engagement. Second, positive leadership only indirectly affects organizational performance. That is, positive leadership has an indirect effect on organizational performance given the parameters of members' positive life positions, learning organization activities, and job engagement. Third, members' positive life positions directly affect learning organization activities and job engagement, but indirectly affect organizational performance with learning organization activities and job engagement as parameters. Fourth, learning organization activities directly affect job engagement and organizational performance. Additionally, learning organization activities indirectly affect organizational performance with job engagement as a parameter. Fifth, job engagement directly affects organizational performance. Conclusions - A CEO's positive leadership and members' positive life positions do not directly affect organizational performance but have a positive effect through learning organization activities and job engagement. In particular, CEOs' positive leadership was proven to be the major factor to affect members' positive life positions, learning organization attitudes, and job engagement, and learning organization activities and job engagement were found to be major factors that directly affect organizational performance. Considering these conclusions, the direct effect of a CEO's positive leadership on organizational performance is not statistically significant but seems to affect members' positive life positions, learning organization activities, and job engagement, which ultimately affects organizational performance. In addition, CEOs' positive leadership is an important factor that enhances the factors with the strongest effect on organizational performance-activities of learning organizations and job engagement.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.241-248
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• 2022

The current article examines the interactions among students' attitudes to e-learning, their implementation of e-learning in their studies, and learning effectiveness. Significantly, it emphasizes the mediating role of accepting e-learning in training. It applied reliability analyses to test the measurement of items and construct validity, using the research data collected from students at Vietnam National University of Ho Chi Minh. Then, the current article used multiple regressions to inspect the causal relations; and applied procedures to investigate the mediating influence. The empirical results indicate students' attitude to e-learning positively influences their implementation of e-learning in their studies. When students apply e-learning in their studies, they likely achieve the best possible training effectiveness. Statistical evidence on the mediating role of accepting e-learning in training by students on the linkage between their attitude to e-learning and training effectiveness is revealed in this article. The findings of this article make some contributions. For educational administrators, it offers insight into the links among students' attitudes to e-learning, their implementation of e-learning in their studies, and training effectiveness, which likely allows them to establish suitable online training programs. This will be beneficial to both learners and educational institutes.

• Educational Technology International
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• v.21 no.2
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• pp.155-191
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• 2020

The aim of this study was to examine the trends (e.g., the distribution of the studies by year, country, research methods, and participants' education level) and fundamental findings [e.g., interaction in Virtual Reality (VR) environments, educational content through VR and Augmented Reality (AR) technologies, learning environment in AR, etc.] regarding immersive learning technologies such as VR and AR in English Language Teaching (ELT) between 2010 and 2019. Employing a systematic review research methodology, data was gathered from 59 academic articles published in the following databases: EBSCOhost, ERIC, Web of Science, and Taylor & Francis. The studies were analyzed using a content analysis approach, and findings demonstrated that immersive learning technologies in ELT came to prominence in 2017. Mixed methods research was the most widely employed research method. The most studied language skill was vocabulary for AR and speaking for VR. The results also revealed advantages and challenges with regards to the use of immersive learning technologies in ELT. Further analysis illustrated the findings related to characteristics of immersive learning technologies in ELT. Based on this review, research and design implications for researchers and practitioners are presented.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.297-304
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• 2011

This study was to analyze the learning effectiveness of multi-media based class by comparing with traditional classroom method. The "Distribution Working Subject" course that is one of the required courses of Vocational high school was selected and its contents were digitalized on MS Powerpoint for multi-media based class. The thirty students were sampled for each experimental and control groups. The homogeneity and learning achievement of sample groups were tested for experiment. Same teacher took the classes of two groups and delivered same contents of course. Only difference between two groups was the delivery method, one is traditional classroom teaching method and the other was the multi-media based class. The learning achievements and satisfaction of sample were post-tested in order to analyze the learning effectiveness by comparing two teaching methods. The results showed that there was a significant difference between experimental and control group in learning achievement after ANCOVA controlled pre-test as covariance(F=5.08, p<.05). It means that the learning achievement of multi-media based class was higher than that of traditional classroom group. The results also showed that a significant difference in students' satisfaction between two groups (t=5.57, p<.001). This study concluded that using multi-media in class could produce more learning achievements and satisfaction of students than traditional classroom method.