• 디지털산업정보학회논문지
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• 제19권2호
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• pp.79-87
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• 2023

On-line learning has been adopted as a major educational method due to the COVID-19 pandemic. Students and faculties got accustomed to on-line educational environment as they experienced it during the COVID-19 pandemic. Development of various technologies and social requirement for educational renovation lay groundwork for on-line learning as well. Therefore, on-line learning or blended learning will be likely to go on after the end of COVID-19 pandemic and it is necessary to prepare the guidelines for effective utilizing on-line learning. The primary purpose of this study is to examine the learning behaviors and the learning effects by using LMS data. Learning behaviors were measured in terms of learning time and access frequency for pre-recorded video lectures targeting computer-practice classes. The results of empirical analysis reveal that frequency was the significant predictor of course achievements but learning time was not. The findings of empirical analysis will provide insights that the effective planning and designing on-line classes based on learning behaviors are key to enhancing learning effects and learner's satisfaction.

• Steel and Composite Structures
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• 제49권1호
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• pp.65-79
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• 2023

This paper presents a development of empirical evaluations, which can be used to evaluate the damage of fiber-reinforced concrete composites (FRC) wall subjected to close-in blast loads. For this development, a combined application of numerical simulation and machine learning approaches are employed. First, finite element modeling of FRC wall under blast loading is developed and verified using experimental data. Numerical analyses are then carried out to investigate the dynamic behavior of the FRC wall under blast loading. In addition, a data set of 384 samples on the damage of FRC wall due to blast loads is then produced in order to develop machine learning models. Second, three robust machine learning models of Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) are employed to propose empirical evaluations for predicting the damage of FRC wall. The proposed empirical evaluations are very useful for practical evaluation and design of FRC wall subjected to blast loads.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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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.

• KDI Journal of Economic Policy
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• 제43권4호
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• pp.1-21
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• 2021

This paper aims to investigate whether there is empirical evidence supporting the learning-to-export hypothesis, which has received little attention in the literature. By taking full advantage of plant-product level data from Korea during 1990-1998, we find some evidence for the learning-to-export effect, especially for the innovated product varieties with delayed exporters: their productivity, together with research and development and investment activity, was superior to their matched sample. On the other hand, this learning-to-export effect was not significantly pronounced for industries protected by import tariffs. Thus, our empirical findings suggest that it would be desirable to implement certain policy tools to promote the learning-to-export effect, whereas tariff protection is not justifiable for that purpose.

• 한국컴퓨터정보학회논문지
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• 제21권11호
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• pp.135-139
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• 2016

This paper investigates the empirical implications. The research question of this study is to verify the influences of psychological and environmental factors toward performance satisfaction and durability of learning in E-Learning University. For empirical verification, a survey was conducted targeting 500 students in E-learning Universities. The results show that actional environment on academic satisfaction in learning is the most important factor followed by physical environment, internal motivation, and academic burnout. The effect of psychological factors on learning persistence was important in the order of academic vision, internal motivation, actional environment and physical environment. The effect of academic satisfaction on learning durability proved to be statistically significant. The results suggest that actional environment should be considered with top priority to increase the academic satisfaction. learning satisfaction, academic vision, and academic satisfaction to enhance students' intention to continue studies are important. Academic burnout has a negative effect on both academic satisfaction and learning persistence, suggesting that this aspect should be properly addresses. The effects of student background variables in E-learning were explored.

• 한국IT서비스학회지
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• 제19권5호
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• pp.107-124
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• 2020

Due to spread of covid-19, which began in December 2019, the usage of online distance learning has expanded within colleges. However, because of the lack of readiness for running online distance learning, professors and students had to experience a lot of inconvenience. In the near future, the usage of online distance learnig is expected to more expand, thus, it seems that there should be a strategies for sustainable online learning operations. This study aims to investigate which factors have impact on the continuance intention to usage of online distance learning of airline department students, focused on Post-Acceptance Model. For the empirical analysis, this study utilized a structural equation model after collecting 136 survey data. The results is as follow; First, user interface has positive impact on confirmation and confirmation has positive impact on satisfaction of online distance learning. Seconds, confirmation has positive impact on perceived usefulness, flow and social presence. Third, social presence has positive impact on satisfaction of online distance learning, but perceived usefulness and flow didn't have statistically meaningful impact on satisfaction. Finally, statisfaction of online distance learning has huge positive impact on continuance intention to usage. It is expected that the implications of this study enable colleges effectively to run online distance learning in preparation for the post-covid 19 era.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제26권2호
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• pp.83-104
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• 2023

Lecture theatres and computing laboratories are common types of classrooms used for teaching and learning in this study; both were equipped with a computer network through which teachers and students can access learning management system, digital library, educational software, and so on. Students were divided into groups of two or three; each group of students collaborated on the worksheets in the laboratory and naturally sat together when attending a class held in the lecture theatre. The social organization of classroom learning would promote student learning but what drives student learning; how to engage students with learning; and how to maintain their interest in learning are of research interest in the present study. The study illustrated the theoretical and empirical links, student motivation has a relation to rich collaboration with peers, communication as verbal interactions as well as teacher-student interactions. These are within socio-cultural contexts for learning to take place. The study was extended to make comparisons of the motivational orientations between student genders. It was found that female students were keener on fun or enjoyment in learning, peer communication, and teacher's intervention, whereas male students were concerned more about digital learning tools, a positive working relationship, social reciprocity, and interpersonal relationships.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.136-136
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• 2022

This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

• 디지털산업정보학회논문지
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• 제11권3호
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• pp.179-200
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• 2015

Recent national policies National Competency Standards(NCS) to develop teaching-oriented education in the field of industry and learning is taking place. Plan to take advantage of the Internet and multimedia classes, information and communication technology (ICT) for ways to leverage the integration appearing in various forms. The purpose of this study is causal influence on the ARCS motivation theory can determine the basic psychology of human motivation factors and the desires of a typical human nature theory dealing with the psychological needs of interactivity and immersion is learning achievement and learning transfer and to validate the demonstration. By applying information and communication technology sector in the development of learning in information and communication equipment training program modules from a field study conducted at the NCS with a clear empirical and empirical research through the synchronization to the learner and to explore the possibility of generalization.

• 토지주택연구
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• 제8권3호
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• pp.123-130
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• 2017

This study aims to empirically verify the impacts of career learning on employability and the mediating effect of job expertise in a public corporation. For the empirical analysis, I surveyed 958 employees(valid respondents) working in a public corporation. And the structural equation modeling(SEM) was used to statistically analize and test the research hypotheses. The independent variable is 'career learning', the dependent variable is 'employability' and the mediating variable is 'job expertise'. The results are as follows. The empirical analysis shows that the positive effects of 'career learning ${\rightarrow}$ job expertise', 'job expertise ${\rightarrow}$ employability' and 'career learning ${\rightarrow}$ employability' are all verified. And the mediating effect of job expertise between career learning and employability is also partially verified. So, all the proposed hypotheses are accepted. From this result, I can clearly suggest that the employees can be growing to professionals with high employability when they retire if they are voluntarily and self-motivated to set up their career plan and to enhance their job expertise. In this context, it is expected that the company should support the employees to continue to strengthen their own expertise in their job place through their mid-long term career learning plan.