• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2152-2170
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• 2014

With advances in smart and ICT(information and communication technology) technologies, our life style has been changing dramatically. Now everybody can enjoy the benefits of such technologies in every aspect of his/her daily life. Currently more and more people are trying to have smart devices such as smart phones and tablet PCs so that smart devices become the bare necessities. New smart technologies have created a new concept called smart learning in education area. As educational smart contents become popular, we need quality standards for the contents. Those standards are essential for evaluating the smart contents and suggesting guidance for future smart contents production. Although there are some standards for the existing e-learning environments, to our best knowledge, there are no standards for educational smart contents in the literature. The purpose of this paper is to develop quality standards for educational smart contents. The proposed quality standards are based on the existing quality standards in e-learning environments and include some characteristics of smart learning. For development of quality standards, wide experts group from academy and industry are selected and surveyed. Their responses are analyzed based on thorough statistical analysis so that final quality standards for educational smart contents are developed.

• Journal of The Korean Association of Information Education
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• v.16 no.1
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• pp.81-89
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• 2012

Quality in smart learning is composed of many factors, and it is more complicated than the traditional education. This study put emphasis on three aspects of the smart learning quality(contents, systems, services). This study depended mostly on literature review, supplemented by FGI(Focus Group Interview) for classification of the smart learning quality factors. On a 5 point Likert scale, the survey enables the users to rate the relative importance of factors, followed by another factor performance rating. The questionnaire were composed of 39 questions. 8 questionnaire sheets were excluded which were not properly filled in or unsuitable for the analysis, and therefore, a total of 112 questionnaires were used for the final analysis. Collected data was statistically analyzed using the SPSS 18.0 for Windows statistical package. Importance-performance analysis(IPA; gap between importance and performance) is used for the empirical test.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.57-70
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• 2021

As COVID-19 spreads, people's interest in smart learning that can do non-face-to-face learning is increasing nowadays. In this study, we aim to empirically analyze how users' thoughts on COVID-19 and the information quality and system quality of smart learning systems affect users' acceptance of smart learning and examine the effect of perceived sensitivity and severity of COVID-19 on the satisfaction and use of smart learning through concerns about the risk of transmission. In addition, we examined the influence of information quality composed of content quality and interaction quality and system quality composed of system accessibility and functionality on the use of smart learning through user satisfaction. To verify the validity of the proposed model, we conducted a survey on 334 users with experience in using smart learning, and performed the analysis using Smart PLS 3.0. According to the analysis results, among information quality and system quality, only functionality has a positive (+) effect on the satisfaction of smart learning, and satisfaction has a positive (+) effect on the usage behavior. However, it is found that accessibility among system quality do not affect satisfaction, and concern about the risk of transmission has a negative effect on satisfaction. This study can provide meaningful guidelines to researchers when researching smart learning to support students' learning in a pandemic situation of a new infectious disease, such as COVID-19. It will also be able to provide useful implications for educational institutions and companies related to smart learning.

• Smart Media Journal
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• v.11 no.2
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• pp.39-52
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• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.383-390
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• 2014

In recent years, the convergence of IT and IT sightseeing tour has emerged as a fusion of academic disciplines in the future. Convergence study of social data analysis, raising the heat. Social Network Services (SNS) being utilized in many areas of marketing and to apply the case study is also increasing. This study is based u-smart tourist information systems for mobile learning content design. This is the pattern of things in the template library for things to increase the effectiveness of the learning content to mobile learning content to be converted to a. Design of mobile learning content using u-smart things smart phone app (App) and XMI to go through the design process of utilizing the heat. Future through the design process by implementing a mobile learning content to meet information quality tourist information content to create mobile learning content and learning things that can be content to live it up advantage.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.869-879
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• 2017

This study identifies the effects of HTML5 service quality on the use intention of smart learning and present the policy implications through empirical studies. This study select assurance, reliability, tangibles, responsiveness, empathy as independent variables of HTML5 service quality and also select perceived usefulness, degree of perceived ease of use as parameters and select use intention of smart learning as dependent variables. The control variables such as learning devices, service, learning place, use age, use times are adapted. As a result of analysis by applying the structural equation model, it was estimated that the reliability of HTML5 service quality, tangibles affect negatively on perceived ease of use, but reliability, assurance, tangibles, empathy, responsiveness of HTML5 service affect positive impacts on perceived usefulness, and also certainty, empathy, responsiveness was identified as positive impacts on the perceived ease of use. It was proven that perceived ease of use effect positive on the perceived usefulness and also usefulness or ease to use have positive effects on the usage intention of users.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.142-146
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• 2023

We present a method for generating 3D structures and rendering objects by combining VAE (Variational Autoencoder) and GAN (Generative Adversarial Network). This approach focuses on generating and rendering 3D models with improved quality using residual learning as the learning method for the encoder. We deep stack the encoder layers to accurately reflect the features of the image and apply residual blocks to solve the problems of deep layers to improve the encoder performance. This solves the problems of gradient vanishing and exploding, which are problems when constructing a deep neural network, and creates a 3D model of improved quality. To accurately extract image features, we construct deep layers of the encoder model and apply the residual function to learning to model with more detailed information. The generated model has more detailed voxels for more accurate representation, is rendered by adding materials and lighting, and is finally converted into a mesh model. 3D models have excellent visual quality and accuracy, making them useful in various fields such as virtual reality, game development, and metaverse.

• Journal of The Korean Association of Information Education
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• v.17 no.2
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• pp.135-146
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• 2013

Smart Learning has been introduced in the educational field recently and it has been used in various ways to improve the quality of education. This research is focused on smart learning contents development for settlement in the educational field. It has carried forward studying in smart learning contents development using storyline, which is a kind of application authoring tool. We analyzed previous studies related to smart learning and presented the characteristics of storyline and the process of content development. Furthermore, we developed the content of digit sorting in Information Life for 6th grade elementary students and applied it to the field to evaluate the educational effectiveness. Through experimental results, the mean difference between traditional activities instruction and instruction using smart learning content was not significant. Nevertheless it has been found the immediate feedback and repeating of activities using smart learning has had positive impacts for understanding, satisfaction and learning interest.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.243-250
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• 2015

Mobile learning content implementing is IT tourism convergence study that IT convergence IT and tourism. Learning to increase the effectiveness of mobile learning content for each learning module, It proposed u-smart tourist information 2.0 systems. Mobile learning content, implementation is u-smart tourist information 2.0 can use the system. Convergence/integration of design patterns and XML is so interesting to students. This is the maximum benefit which is taught classes for each learning module divided into learning the Design Pattern NCS. As a result, the learner. In particular, attendance has come out better the effect of learning and improved. Another advantage is tourism, information content information quality mobile learning content for and construct a tourist information content that you can do in real time. Also, mobile learning content, implementation in the next NCS expected to use a lot of help in learning. This study is the result of increased learning the analysis of the lessons learned. Implement mobile learning content gives fun and interesting to the learner to ten design process using the u-Smart Tourist Information class 2.0.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.468-478
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• 2018

The goal of this study is to propose a new directivity for business training based on an analysis of the learner's satisfaction, the cause of the learning effect and the cause of reenrollment in smart learning courses. The data from 878 learners of 11 companies was analyzed by ANOVA and multiple regression analysis and the following results were obtained. First of all, the satisfaction of studying by smart learning showed various results depending on the motivation, process and contents of studying. According to the results, high rates of satisfaction were observed when the people take an active part in studying, as reflected in the frequency and time of studying. Also, when the learning contents were presented in an animated manner, the satisfaction of the students was increased. Second, the motivation of the students to participate in the smart learning and study process was reflected in the frequency, time and quality of their studies, thus confirming the learning effect. Lastly, the satisfaction and effectiveness of studying by smart learning are the causes of reenrollment. Based on the analysis results, it was concluded that the corporation's support and proper compensation are needed to increase the rate of satisfaction and the effectiveness of smart learning from the corporation's perspective. Also, from the viewpoint of the smart learning system operators, it is necessary to find ways of developing the learning contents.