• The Journal of Asian Finance, Economics and Business
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• 제9권5호
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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.

• 디지털융복합연구
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• 제3권2호
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• pp.143-157
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• 2005

Many papers point out that the e-Learning is one of the most important industries, and the effect on other industries can be more powerful than any other business. Therefore, we think about social, cultural, industrial and technological effect of the e-Learning in order to enlarge industry scale as well as educational performances. In many cases of developed countries, various kinds of study have been performed for the e-Learning quality assurance because quality of the e-learning should operate on effective and efficient learning and continuous market development of education industries. The e-Learning quality assurance has import function not only for learning contents reusability like a SCORM and metadata but also for learning system, solution and service operation, so activities for the quality assurance should consider of cultural and tactical approach when it is applied in the e-learning business. In this paper, we present the concept, domain and purpose of the e-Learning quality assurance. Furthermore, this paper proposes the process and methodology in order to make the quality assurance standard model which is consist of 6 phase such as Environment Research, Needs Analysis, Framework, Metrics, Development and Implementation, Evaluation and Feedback through the analysis and comparison of pre-studied worldwide quality control, management and assurance documents.

• Asia pacific journal of information systems
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• 제18권4호
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• pp.105-130
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• 2008

Consumers of e-learning market differ from those of other markets in that they are replaced in a specific time scale. For example, e-learning contents aimed at highschool senior students cannot be consumed by a specific consumer over the designated period of time. Hence e-learning service providers need to attract new groups of students every year. Due to lack of information on products designed for continuously emerging consumers, the consumers face difficulties in making rational decisions in a short time period. Increased uncertainty of product purchase leads customers to herding behaviors to obtain information of the product from others and imitate them. Taking into consideration of these features of e-learning market, this study will focus on the online herding behavior in purchasing e-learning contents. There is no definite concept for e-learning. However, it is being discussed in a wide range of perspectives from educational engineering to management to e-business etc. Based upon the existing studies, we identify two main view-points regarding e-learning. The first defines e-learning as a concept that includes existing terminologies, such as CBT (Computer Based Training), WBT (Web Based Training), and IBT (Internet Based Training). In this view, e-learning utilizes IT in order to support professors and a part of or entire education systems. In the second perspective, e-learning is defined as the usage of Internet technology to deliver diverse intelligence and achievement enhancing solutions. In other words, only the educations that are done through the Internet and network can be classified as e-learning. We take the second definition of e-learning for our working definition. The main goal of this study is to investigate what factors affect consumer intention to purchase e-learning contents and to identify the differential impact of the factors between consumers with purchase experience and those without the experience. To accomplish the goal of this study, it focuses on herding behavior and perceived usefulness as antecedents to behavioral intention. The proposed research model in the study extends the Technology Acceptance Model by adding herding behavior and usability to take into account the unique characteristics of e-learning content market and e-learning systems use, respectively. The current study also includes consumer experience with e-learning content purchase because the previous experience is believed to affect purchasing intention when consumers buy experience goods or services. Previous studies on e-learning did not consider the characteristics of e-learning contents market and the differential impact of consumer experience on the relationship between the antecedents and behavioral intention, which is the target of this study. This study employs a survey method to empirically test the proposed research model. A survey questionnaire was developed and distributed to 629 informants. 528 responses were collected, which consist of potential customer group (n = 133) and experienced customer group (n = 395). The data were analyzed using PLS method, a structural equation modeling method. Overall, both herding behavior and perceived usefulness influence consumer intention to purchase e-learning contents. In detail, in the case of potential customer group, herding behavior has stronger effect on purchase intention than does perceived usefulness. However, in the case of shopping-experienced customer group, perceived usefulness has stronger effect than does herding behavior. In sum, the results of the analysis show that with regard to purchasing experience, perceived usefulness and herding behavior had differential effects upon the purchase of e-learning contents. As a follow-up analysis, the interaction effects of the number of purchase transaction and herding behavior/perceived usefulness on purchase intention were investigated. The results show that there are no interaction effects. This study contributes to the literature in a couple of ways. From a theoretical perspective, this study examined and showed evidence that the characteristics of e-learning market such as continuous renewal of consumers and thus high uncertainty and individual experiences are important factors to be considered when the purchase intention of e-learning content is studied. This study can be used as a basis for future studies on e-learning success. From a practical perspective, this study provides several important implications on what types of marketing strategies e-learning companies need to build. The bottom lines of these strategies include target group attraction, word-of-mouth management, enhancement of web site usability quality, etc. The limitations of this study are also discussed for future studies.

• 한국전자거래학회지
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• 제26권1호
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• pp.107-126
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• 2021

전자상거래에서 상품 정보에 따른 신속하고 정확한 자동 상품 분류는 중요하다. 최근의 딥러닝 기술 발전은 자동 상품 분류에도 적용이 시도되고 있다. 성능이 우수한 딥러닝 모델개발에 있어, 학습 데이터의 품질과 모델에 적합한 데이터 전처리는 중요하다. 본 연구에서는, 텍스트 상품 데이터를 기반으로 카테고리를 자동 유추할 때, 데이터의 전처리 정도에 따른 영향력과 학습 데이터 선택 범위 영향력을 CNN모델을 사례 모델로 이용하여 비교 분석한다. 실험 분석에 사용한 데이터는 실제 데이터를 사용하여 연구 결과의 실증을 담보하였다. 본 연구가 도출한 실증 분석 및 결과는 딥러닝 상품 분류 모델 개발 시 성능 향상을 위한 레퍼런스로서 의의가 있다.

• 대한안전경영과학회지
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• 제9권3호
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• pp.153-163
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• 2007

Over the fast few years, web-based e-Learning have made remarkable progress. According to advance of e-Learning, the evaluation of e-Learning effectiveness and success model become more important. This study had a focus on the effect of system characteristic of e-Learning systems and self-efficacy on learning performance. Data has been collected from 192 person experienced in e-Learning. The questionnaire method was adopted to collect the data for this study. The research was conducted by using SPSS 12.0 and AMOS 4.0. The research results and suggestions of the study are as follow. First of all, system quality and information quality of e-Learning system had positive relationship with perceived usefulness. Second, information quality was related positively to user satisfaction. Third, perceived usefulness was positively connected with user satisfaction. Fourth, user satisfaction and self-efficacy had relation to learning performance.

• 한국산업정보학회논문지
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• 제11권5호
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• pp.181-189
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• 2006

유비쿼터스 기술은 학습 분야에서 많은 변화를 요구 하고 있으며, 이러닝 컨텐츠 분야 역시 이 기술에 기초한 컨버전스 학습컨텐츠 개발로 변화되어야 한다. 그러나 현재까지 대다수의 이러닝 컨텐츠는 기술융합적 관점에서 매우 미약하고 학습자 눈높이에 맞춘 컨텐츠로 보기는 많은 무리가 따른다. 따라서 본 연구의 목적은 학습자 중심의 이런닝 컨텐츠 개발 방안을 제시하는데 있다. 이를 위해 형식, 비형식 학습의 장점을 적극 활용하게 되는 컨버전스 학습모형을 살펴 본 후, 컨버전스 시대 이러닝 컨텐츠 개발을 위한 학습관리시스템에 대한 과제분석, 스토리텔링, 그리고 피드백 디자인 전략의 중요성을 살펴 보고 학습자 중심의 효과적인 컨텐츠 개발 방안을 제시 한다.

• 융합보안논문지
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• 제5권3호
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• pp.9-14
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• 2005

본 논문에서는 언제, 어디서나, 어떤 내용에 관계없이 학습할수있는 유비쿼터스환경의 e-learning 모델을 위하여 기존 e-learning 모델의 한계점을 분석하고, 유비쿼터스 네트워크망과 차세대 센서기술등을 적용하여 SCORM표준안을 기반으로 한 LMS에 학습콘텐츠의 변환서비스와 협력학습서비스기능을 추가한 유비쿼터스 환경에 대응하는 LMS모델을 제안하였다.

• 경영정보학연구
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• 제12권2호
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• pp.25-45
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• 2010

오늘날 인터넷의 발전과 더불어, 대학 교육에 있어 e-러닝은 매우 중요한 교과목으로 자리를 잡게 되었다. 이에 따라 학교 당국에서는 보다 양질의 교육 컨텐츠 질 개발과 e-러닝을 수강하는 학생들의 e-러닝을 통한 만족도와 학습효과를 증대하기 위해 많은 노력을 하고 있다. 본 연구에서는 기술수용모델을 이용해 학생들의 e-러닝 수용에 대한 연구를 수행하였다. 특히, 온라인 환경에서의 신뢰는 기술수용에 있어 매우 중요한 영향을 미치는데, 본 연구에서는 학생들의 e-러닝 수용에 있어 신뢰 수준에 따른 e-러닝 수용 과정을 분석하였다. 본 연구 결과는 e-러닝에 대한 수용의 심도 깊은 이해를 통해 보다 좋은 e-러닝 시스템을 구현과 e-러닝 전략 개발에 유용한 시사점을 제시해 줄 것이다.

• International Journal of Contents
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• 제5권1호
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• pp.1-8
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• 2009

The new paradigm called the web 2.0 recently appeared in the web environment. We pay attention to the positive effects which may be brought about by application of the web 2.0 to e-learning; we think that it can improve problem solving skills of learners and reinforce their creativity. But until now, e-learning model, which understood the web 2.0 concept completely, has been never developed. In this context, we propose the web 2.0-based e-learning platform which induces all the courses for education such as the selection of topic, preparation of lecture schedule and contents, teaching and learning, to be decided by participants. We believe that this platform can replace or supplement the e-learning of web 1.0 age, and realize the positive effects.

• 4차산업연구
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• 제3권1호
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• pp.13-20
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• 2023

Purpose - By designing a PEF(Personalized Education Feedback) system for real-time prediction of learning achievement and motivation through real-time EEG analysis of learners, this system provides some modules of a personalized adaptive learning system. By applying these modules to e-learning and offline learning, they motivate learners and improve the quality of learning progress and effective learning outcomes can be achieved for immersive self-directed learning Research design, data, and methodology - EEG data were collected simultaneously as the English test was given to the experimenters, and the correlation between the correct answer result and the EEG data was learned with a machine learning algorithm and the predictive model was evaluated.. Result - In model performance evaluation, both artificial neural networks(ANNs) and support vector machines(SVMs) showed high accuracy of more than 91%. Conclusion - This research provides some modules of personalized adaptive learning systems that can more efficiently complete by designing a PEF system for real-time learning achievement prediction and learning motivation through an adaptive learning system based on real-time EEG analysis of learners. The implication of this initial research is to verify hypothetical situations for the development of an adaptive learning system through EEG analysis-based learning achievement prediction.