• Journal of Digital Convergence
• /
• v.14 no.2
• /
• pp.227-233
• /
• 2016

Typical Web-based learning system is operating the variety of learning contents. However, it is not easy to efficiently select appropriate learning contents. In this paper, we propose a learning content delivery method that can provide the most suitable preferences and feedback to the learner. By analyzing the profile of the learner, it determines the positive feedback and evaluation to be provided to the learner. The result of applying learning techniques were applied to provide the best learning content to adaptively out the form. The proposed method appears as a learning experience and learning outcomes are higher after a study was conducted to suggest that could help in the learning progress of the students themselves. This paper are applied to real learners. And the learners using the system were surveyed by the questionnaire on learning experience and learning outcomes were analyzed.

• Journal of Science and Technology Studies
• /
• v.2 no.1 s.3
• /
• pp.39-61
• /
• 2002

This study reviews the emergence of new innovation policy paradigm in advanced countries and their impacts on the development of innovation theories in 1980s and 1990s. It shows that the characteristics of new policy paradigm are the emphasis on the user-orientedness and the socio-economic aspects of innovation and the preference of capability enhancement of innovators over resource subsidy This new perspectives of innovation policies had effects on the emergence and development of 'the innovation system theory' which is based on the key concepts such as interactive teaming, innovating capability and national systems of innovation. In spite of the development of the innovation system theory, it has some problems to be solved for the innovation policy design because 'the social' is still peripheral factors in the constitution on the innovation system theory. This study makes some suggestions to incorporate the social dimension of innovation into the innovation system theory.

• Journal of Digital Convergence
• /
• v.19 no.6
• /
• pp.39-46
• /
• 2021

This study aims to investigate the relationship among the learning flow, perceived effectiveness of online learning and learning burnout in college online classes. A total of 149 college students participated in the study and completed the survey including learning flow, learning burnout and demographic information. The results showed that participants with higher learning flow showed less learning burnout. In addition, the perceived effectiveness of online learning partially mediated the relationship between cognitive learning flow and learning burnout, but did not mediate the relationship between defined learning flow and learning burnout. Since learners with higher cognitive learning flow perceived online learning as more effective, it is necessary to find out how to build learners' cognitive learning flow to decrease learning burnout. The results imply that universities should provide students with administrative support and an appropriate online learning environment.

• Journal of Digital Convergence
• /
• v.10 no.10
• /
• pp.139-146
• /
• 2012

The emotional factor has not been focused in e-learning studies. But the emotions of student are very important in e-learning because it is a self-regulated learning. This study is focused on the emotional factor in e-learning. This study examines the effect of perceived customer orientation to emotional presence, commitment and customer satisfaction in e-learning. The results of this study showed that the perceived customer orientation effect to the commitment about the learning and the customer satisfaction in e-learning.

• Journal of Digital Convergence
• /
• v.8 no.3
• /
• pp.115-127
• /
• 2010

This study investigates the effect of E-learning service quality toward users' learning satisfactions when moderating by users' study motivations at cyber universities. For this end, the E-learning service quality was measured with SERVQUAL which was widely employed in academic research area. From rich survey analysis, this study finds that the three factors of E-learning service quality such as concreteness, certainty, credibility and sympathy are statistically correlated with users' learning satisfactions, but the responsiveness is not. Also in order to test the hypothesis that the study motivation is a moderate variable, the three step regression analysis was applied. Finally, this research finds that the study motivation has the role of moderate variable to affect the users' learning satisfactions.

• Journal of Digital Convergence
• /
• v.12 no.6
• /
• pp.549-557
• /
• 2014

The learning application of the rotating object utilizing smart devices, it is possible by using the touch functionality and 3D graphics to enhance the realism and operational feeling, and to overcome the limitations of learning content existing. In this study, I designed a "rotation class" based on the learning contents of elementary and middle mathematics education and developed the learning application which driven by smart Android-based device by using Andoroid API class and the OpenGL ES Because this application is driven by the smart devices, learners easily can make the rotated objects and observe them. It can be utilized in various for elementary and middle education.

• Journal of Digital Convergence
• /
• v.13 no.3
• /
• pp.31-36
• /
• 2015

The Many universities and educational institutions have focused on shifting education paradigm into smart learning using high-tech devices and internet as the level of technology has growing rapidly in every society. Especially, cyber universities and open universities in Korea are trying to develop educational network system and infrastructure corresponding to new convergence technology environment. Therefore, the purpose of this study is to introduce clouded based education system in order to suggest an effective way of using new educational learning system. This study shows the case of Hangout learning system used in K University in Korea to suggest a new educational learning model for real-time lecture and cloud based service platform for improving educational learning environment.

• Journal of Digital Convergence
• /
• v.19 no.9
• /
• pp.411-421
• /
• 2021

This study was conducted to compare the effects of student-generated questions (SGQ) and online quiz-based learning (OQL) applied to a physiology and a pharmacology course with 173 nursing students in total. The levels of learning motivation of all participants at 15th week decreased significantly compared with 8th week. There were no statistical difference on learning motivation, communication, and critical thinking between SGQ and OQL, and regardless of the order SGQ and OQL were applied. However, the level of learning satisfaction in students taking pharmacology course was significantly higher in OQL than SGQ (t=2.184, p=.003). We suggest that either SGQ or OQL or both SGQ and OQL be used throughout a semester in biological nursing science subjects without changing teaching strategy during a semester.

• Journal of Digital Convergence
• /
• v.17 no.1
• /
• pp.189-194
• /
• 2019

This paper is a study on the methodology of making customized contents according to user 's tendency through the development of learning contents utilizing IT. A variety of learners around the world use mobile devices and mobile learning contents to conduct their learning activities in various fields, and foreign language learning is one of the typical mobile learning areas. Foreign language learning contents suggested in this study is constructed based on the learner's verbal and text information in accordance with the user's vocal tendency. It is necessary to find out a suitable method to translate the user's native language text into the target language and make it into user friendly content.

• Journal of Digital Convergence
• /
• v.12 no.6
• /
• pp.325-332
• /
• 2014

It is generally accepted that classification accuracy is affected by the number of learning documents, but there are few studies that show how this influences automatic text classification. This study is focused on evaluating the deviation-based classification model which is developed recently for genre-based classification and comparing it to other classification algorithms with the changing number of training documents. Experiment results show that the deviation-based classification model performs with a superior accuracy of 0.8 from categorizing 7 genres with only 21 training documents. This exceeds the accuracy of Bayesian and SVM. The Deviation-based classification model obtains strong feature selection capability even with small number of training documents because it learns subject information within genre while other methods use different learning process.