• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.3
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• pp.37-51
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• 2017

We investigated how entrepreneurship, information technology acceptance, and media utilization influence on office worker commitment and how effects are modulated by learning orientation. The purpose of this study is to identify variables that influence on office worker commitment. To do so, entrepreneurship, information technology acceptance, and media utilization that are the core competencies of individuals and organizations in the era of smart information are proposed as predictor variables, office worker commitment as a outcome variable and learning orientation as a modulator. For this study, a questionnaire survey was conducted on office workers, and finally 340 valid questionnaires are used for analysis. Hierarchical regression analysis is used with demographic characteristics as control variables and learning orientation as a modulating variables. A result showed that the higher need for achievement and proactiveness of entrepreneurship is, the higher job commitment is and that the perceived usefulness of information technology acceptance and communication utilization ability of media utilization competitiveness have a positive effect on job commitment. A research showed that learning orientation is modulating the relationship between entrepreneurship and job commitment, and between media utilization capability and job commitment, respectively. We concluded that we should actively seek synergies of learning orientation along with accumulation of online communication utilization capacity and perceived usefulness of information technology, and of proactiveness need for achievement and in entrepreneurship in order to improve the work committment in the smart information society where the digital environment is advanced.

• International Journal of Contents
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• v.16 no.2
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• pp.78-91
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• 2020

In this study, an investigation was conducted into the influencing factors for the learning motivation of players in the game, including experience, vicarious experience, the need of achievement, the need of power, and mastery motivation. Then, a discussion was conducted regarding the role played by learning motivation, learning performance, and satisfaction with continuous use. A survey was conducted with 519 players, most at the intermediate gaming level in . As demonstrated by the results of this study, experience, vicarious experience, the need of power, and the mastery of motivation have significant positive association with the players' motivation of learning the game. Learning performance and satisfaction have a positive impact on the continuity of use. Additionally, the correlation between the need of achievement and learning motivation is insignificant. Overall, the research results confirm the significance of the social-cognitive theory relative to the learning motivation. Players began to transform, satisfied with their achievements in the game, as well as gradually evolving toward self-improvement to achieve satisfaction. It offers a new explanation and crucial reference for mastering the gaming trend among the contemporary players.

• Journal of Korea Game Society
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• v.11 no.5
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• pp.79-88
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• 2011

The purpose of this study is to confirm meaning for quest-based learning designed as one of learning methods with new media, which the contents were made of QR code based on smart-phone. For this purpose, this study conducted 8 times of class during one month with 32 elementary third graders. And analysis for the result of this study was carried out MANOVA focus on four sub-factor of motivation. The results showed positive effect for quest-based learning in attention and confidence factor on motivation. Quest-based learning of gaming version as a learning method using various media can use a learning method for facilitation of learner participation, supporting of learning by doing.

• Journal of Fashion Business
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• v.16 no.2
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• pp.1-11
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• 2012

The purpose of this study was to examine the effects of UBL (Ubiquitous basedlearning) on fashion and consumer behavior course. Thirty-one undergraduate university students completed a 15-week capstone course in a clothing and textiles department. About sixteen percent students were majoring in liberal arts and sixty-three percent of the participants were majoring in the clothing and textiles. Mainly, the participants were junior and senior undergraduate students. The participants demonstrated positive attitude toward the UBL (Ubiquitous based-learning) on fashion and consumer behavior course. The results showed that seventy-seven percent of the participants have more opportunities to handle multi-media resources using social network and social media. Eighty percent of the participants have been developed of communication skills. Seventy-one percent of the participants were helped to learn foreign language skills. Overall, most of the participants were satisfied that their presentation skill was improved in class and they had willing to recommend the class to other students for the future.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.156-160
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• 2007

정보 통신 기술의 발전으로 교육 환경은 이러닝(e-Learning)과 모바일 러닝(Mobile Learning)이 지원되는 융합(convergence)된 네트워크 환경이 구축되고 있으며, 새로운 교수법을 필요로 한다. 학습자의 학습 환경(learning environment)에 따라 이러닝과 모바일 러닝이 상호작용(interaction)하여 학습 활동이 끊김없이(seamless) 수행되도록 한다. 본 논문에서는 이러닝과 모바일 러닝 환경에서 학습 활동을 수행하는 과정에서 상호작용하는 레이어를 설계한다. 각 레이에의 흐름(flow)에서 필요한 요소로 메타데이터(metadata)를 도출하고, 메타데이터를 다른 요소에서 필요로 할 때 재사용(reusable)할 수 있도록 하였다.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.1-5
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• 2021

Cyberbullying is a problem that is faced in many cultures. Due to their popularity and interactive nature, social media platforms have also been affected by cyberbullying. Social media users from Arab countries have also reported being a target of cyberbullying. Machine learning techniques have been a prominent approach used by scientists to detect and battle this phenomenon. In this paper, we compare different machine learning algorithms for their performance in cyberbullying detection based on a labeled dataset of Arabic YouTube comments. Three machine learning models are considered, namely: Multinomial Naïve Bayes (MNB), Complement Naïve Bayes (CNB), and Linear Regression (LR). In addition, we experiment with two feature extraction methods, namely: Count Vectorizer and Tfidf Vectorizer. Our results show that, using count vectroizer feature extraction, the Logistic Regression model can outperform both Multinomial and Complement Naïve Bayes models. However, when using Tfidf vectorizer feature extraction, Complement Naive Bayes model can outperform the other two models.

• Smart Media Journal
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• v.12 no.4
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• pp.9-18
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• 2023

Steganography is a technology capable of protecting data by hiding the existence of data. Recently, with the development of deep learning technology, deep learning-based steganography are being developed. Deep learning can learn by analyzing high-dimensional features of data, so it can improve the performance and quality of steganography. In this paper, we investigated the research trend of image steganography based on deep learning.

• Journal of Korean Library and Information Science Society
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• v.43 no.2
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• pp.227-246
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• 2012

The purpose of this study is to survey the reading reality of comic books for learning in elementary schools, to research the perceptions of students and their parents to reading comic books for learning, and to suggest the methods which librarians and teachers make use of the comic books for learning in their classes. For doing this, firstly 3 elementary schools were chosen and every school, 4 classes from 3rd year to 6th year, total 12 classes' students and their parents were searched. As the results of this, it's revealed that most of students have experiences of reading the comic books which are circulated in school libraries, etc., and both groups of students and their parents thought the comic books to help their academic achievement, and they have the thought that the reading comic books induce themselves to read the other normal books for more informations. It's suggested that the comic books for learning should be thought of the important media for teaching learning, and be utilized as the media for normal reading attitude s and habits of students in elementary school libraries.

• Korean Medical Education Review
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• v.19 no.3
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.991-1000
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• 2015

This paper is studying for New Online Learning Model on Smart digital era. It can expect the result of learning degree on Online Learning Class. Using 7-factors of Online Class's operating policy, make the expectation model by 'decision tree' method. And through applying another class, we can getting a generality. Finally, Over the traditional Online Class model, we can take the real-time status of Online class learning degree. It is useful both students and teacher. It is the one of 'Smart learning Model'.