• Journal of the Korean Home Economics Association
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• v.51 no.2
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• pp.253-261
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• 2013

The purpose of this study was to investigate the moderating effects of parental monitoring on the relationship between children's dependency on mobile phones and control of learning behavior. The data came from the 2010 Korean Children and Youth Panel (N = 1,609) conducted by the National Youth Policy Institute. The analysis method used was Structural Equation Modeling by using SPSS 17.0 and AMOS 7.0. To test the significant moderating effects, Ping's two-step technique, which is free from the requirement of nonlinear constraints, was used. Our results demonstrated that children's dependency on mobile phones had negative effects on control of learning behavior, and the interaction effects between such dependency and parental monitoring affected the control of learning behavior. Thus, these results proved the moderating effects of parental monitoring in the control of learning behavior. This study suggests that parental monitoring buffers against having difficulties to control and adjust one's behavior associated with control of learning behavior, which is affected by the dependency on mobile phones among children. We discussed that the risks of children's dependency on mobile phones and parental monitoring should be acknowledge as a significant protective factor.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.477-486
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• 2011

The purpose of this paper was to examine the teaching and learning activities using mobiles devices in a university. We analyzed the instructional methods, instructional strategies, devices types, and evaluation activities. In addition, we conducted deep interviews with the students who used the mobile devices in terms of their understanding on the mobile learning, mobile learning methods, evaluation methods, difficulties and their expectations. These findings will be used to improve the quality of the teaching and learning methods using mobile devices in higher education.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.245-251
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• 2023

Facial expression recognition plays a significant role in understanding human emotional states. With the advancement of AI and computer vision technologies, extensive research has been conducted in various fields, including improving customer service, medical diagnosis, and assessing learners' understanding in education. In this study, we develop a model that can infer emotions in real-time from a webcam using transfer learning with TensorFlow.js and MobileNet. While existing studies focus on achieving high accuracy using deep learning models, these models often require substantial resources due to their complex structure and computational demands. Consequently, there is a growing interest in developing lightweight deep learning models and transfer learning methods for restricted environments such as web browsers and edge devices. By employing MobileNet as the base model and performing transfer learning, our study develops a deep learning transfer model utilizing JavaScript-based TensorFlow.js, which can predict emotions in real-time using facial input from a webcam. This transfer model provides a foundation for implementing facial expression recognition in resource-constrained environments such as web and mobile applications, enabling its application in various industries.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.71-86
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• 2019

The unprecedented demands of mobile communication networks by the rapid rising popularity of mobile applications and services require future networks to support the exploding mobile traffic volumes, the real time extraction of fine-rained analytics, and the agile management of network resources, so as to maximize user experience. To fulfill these needs, research on the use of emerging deep learning techniques in future mobile systems has recently emerged; as such, this study deals with deep learning based mobile communication research activities. A thorough survey of the literature, conference, and workshops on deep learning for mobile communication networks is conducted. Finally, concluding remarks describe the major future research directions in this field.

• The Journal of Korean Association of Computer Education
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• v.12 no.4
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• pp.23-34
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• 2009

The main purpose of this study was to develop a mobile platform that supported college students to become self-regulated learners, and to examine its effects on students' academic achievement and self-regulated learning abilities. For this purpose, a mobile platform was designed and developed through the steps of systems approach. All the sub-steps were monitored and pilot-tested. The mobile platform incorporated a number of features designed specifically for the self-regulation components, with the intention of enhancing students' academic achievement and self-regulated learning abilities. Finally, research results suggested that students were taking advantage of the mobile platform that supported students' self-regulated learning. There were statically significant differences in academic achievement according to the type of mobile platform, F(1,133)=1767.202, P<.001

• Human Ecology Research
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• v.59 no.3
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• pp.341-351
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• 2021

The purpose of this study was to examine the longitudinal relationships between Korean adolescents'mobile phone dependency, trajectories of depression, and self-regulated learning abilities. To achieve these goals, structural equation modeling analysis was conducted, using the 3rd, 5th and 7th wave of the data on 4th graders taken from the Korean Children and Youth Panel Survey. The results can be summarized as follows. First, growth-curve longitudinal analysis indicates that depression in 6th through 10th grade has increased. Second, mobile phone dependency among adolescents at 6th grade has a significant effect on both the initial value and the rate of change in depression. Also, the initial value and the rate of change in depression have significant relationships with mobile phone dependency at 10th grade. Moreover, both increased levels of mobile phone dependency and the rate of change in depression significantly influence adolescents'self-regulated learning abilities at 10th grade. Based on a longitudinal data set, these findings demonstrate the causal relationships between Korean adolescents'trajectories of depression and their mobile phone dependency. The findings also provide a comprehensive framework with implications for adolescents'development through an understanding of the relationships between adolescents'depression and mobile phone dependency, which impact their self-regulated learning abilities.

• Journal of Computing Science and Engineering
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• v.4 no.1
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• pp.80-95
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• 2010

In order to truly integrate e-Learning system into regular curriculum at a university, mobile access to Learning Management Systems has to be enabled. Mobile devices have the potential to be integrated into the classroom, because they contain unique characteristics such as portability, social interactivity, context sensitivity, connectivity and individuality. Adoption of Learning Management Systems by students is still on the low rate, mostly because of poor usability of existing e-Learning systems. Our initial research has confirmed this hypothesis. Usability issue is rising to the higher level on the mobile platform, because of the mobile devices' limited screen size, input interfaces and bandwidth, and also because of the context of use. Our second hypothesis was that it is wrong to consider a mobile device as a surrogate for desktop or laptop personal computer (PC). By just adopting the existing Learning Management System on mobile devices with adaptive technologies such as Google proxy, we do not acquire the satisfactory results. Usability can prove to be even lower compared to desktop application. One possible solution to the problem could be development of rich client applications for today's mobile devices that would raise the usability to a higher level. We developed a PocketPC prototype application by using user-centered design principles, which we presented as a third alternative in usability research conducted among university students. Results gathered in such a way have confirmed that development of e-Learning system, in order to be widely accepted by students, needs to have the user(student) in the center of development process.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.49-53
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• 2010

e-learning and m-learning have some problems that data transmission frequently discontinuously, communication cost increases, the computation speed of mass data drops, battery limitation in the mobile learning environments. In this paper, we propose the PULIMS for u-learning systems. The proposed system intellectualize the education environment using intelligent mobile agent, supports the customized education service, and helps that learners feasible access to the education information through mobile phone. We can see the fact that the efficience of proposed method is outperformed that of the conventional methods. The PULIMS is new technology that can be used to learn whenever and wherever learners want in Ubiquitous education environment.

• The Journal of Korean Association of Computer Education
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• v.18 no.1
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• pp.55-68
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• 2015

The purpose of the study is to examine a structural relationship among mobile self-efficacy, mobility, perceived ease of use, perceived usefulness, and intention to use of a mobile learning service using technology acceptance model. The result revealed that mobile self-efficacy, mobility had a direct effect on perceived ease of use. Second, mobile self-efficacy, mobility, perceived ease of use had a direct effect on perceived usefulness. Third, mobile self-efficacy, mobility, perceived usefulness had a direct effect on intention to use of a mobile learning service. However, perceived ease of use did not have a effect on behavioral intention of mobile learning service.

• Asia Marketing Journal
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• v.21 no.4
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• pp.77-89
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• 2020

Population-level learning has traditionally been used to provide an explanation for the underlying mechanism of industry change. But it has yet to examine the impact on strategic decisions such as market entry. This conceptual paper aims to provide an insight into how population-level learning affects entry likelihood by acting as a tool for interpreting population-level changes. We study this in the context of the fast-paced mobile gaming industry where population-level information is salient and develop a set of propositions with regard to the likelihood of entry.