• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.294-300
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• 2021

The current society relies upon social media on an everyday basis, which contributes to finding which of the following supervised machine learning algorithms used in sentiment analysis have higher accuracy in detecting Malay internet slang and short forms which can be offensive to a person. This paper is to determine which of the algorithms chosen in supervised machine learning with higher accuracy in detecting internet slang and short forms. To analyze the results of the supervised machine learning classifiers, we have chosen two types of datasets, one is political topic-based, and another same set but is mixed with 50 tweets per targeted keyword. The datasets are then manually labelled positive and negative, before separating the 275 tweets into training and testing sets. Naïve Bayes and Random Forest classifiers are then analyzed and evaluated from their performances. Our experiment results show that Random Forest is a better classifier compared to Naïve Bayes.

• Korean Journal of Culture and Social Issue
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• v.18 no.3
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• pp.329-347
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• 2012

Criminal media such as dramas and movies are growing in popularity. However, the effects of criminal media as well as its psychological mechanism are not clearly examined. Based on social learning theory (Bandura, 1978), past studies showed that arrest and punishment to the criminal in media have a suppressing effect. The present research examined the ironic possibility that media coverage of punishment could increase the audience's criminal intention and proposed the mediating role of counterfactual thinking in the effect. We hypothesized that when punishment was depicted as accidental rather than unavoidable in media coverage, perceived high mutability and counterfactuals focusing on the accidental factors could clarify the ways to commit the crime without being caught and subsequently increase future criminal intention. In this study, 95 college students read a story of plagiarizing either no, accidental, or inevitable punishment, and later asked to report their intention to plagiarize. An ANCOVA with participants' own history of plagiarism as a covariate found that the intention of plagiarism in future was significantly different. The results showed that the intention of plagiarism in the accidental punishment condition was higher than that in the inevitable punishment condition. Further, the intention of plagiarism in the accidental punishment condition was the same level with non-punishment condition. The findings suggest that whether criminals are caught or not is not enough to reduce criminal intentions of audience, but how criminals are caught matters.

• Hwankyungkyoyuk
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• v.21 no.3
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• pp.48-58
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• 2008

The purpose of this study was to investigate the influences of environmental education program through various instructional media on pro-environmental attitudes of forth graders in an elementary school in Seoul. The students were divided into an experimental group and a control group. A questionnaire was used to survey the effects of applying environmental education program through various instructional media. The SPSS 12.0 program was used to analyze the results. The student in the experimental group acquired a higher level of pro-environmental attitudes than the control group did. The environmental education program through various instructional media used in this study were effective especially in dealing with the environmental educational subdomains such as verbal commitment, actual commitment, affect. The major results of this study were as follows. First, environmental education program through various instructional media had a positive effect on the environmental concerns and needs for learning of environmental problems. Second, the group by environmental education program through various instructional media showed the significant difference(p<.001) on the pro-environmental attitudes as it proved those are effect on 3 subdomains of verbal commitment, actual commitment and affect. Third, environmental education program through various instructional media had a positive correlation(from 585 to .680) among the 3 subdomains of verbal commitment, actual commitment and affect. So, students who hold verbal commitment showed good effect on the actual commitment and affect. In conclusion, the environmental education program through various instructional media had a positive effect on pro-environmental attitudes of elementary school students. It is demanded that more intensive research on this study should be done, linking with teaching and teaming method, as a follow-up activity.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.861-870
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• 2017

In this paper, we propose the roles of social robots in educational environments. This proposal becomes an extension of R-learning. The purpose of social robots is the communication and interaction with human. Social robots have two roles. One is similar to the role of educational service robot and the other is communication role with people in education environments. We make an scenario to explain how to operate the roles of social robots using robot jibo SDK. The scenario was designed for mild interaction with the user in the educational environment. And it was made using jibo animation part to control the external reaction of jibo and behaviors part to control the internal reaction in jibo SDK. Social robots collect data effectively, based on grafting technologies and interaction with people in educational environments. Concludingly, various data collected by social robots contribute to solving problems, developing and establishing of educational environments.

• The Research Journal of the Costume Culture
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• v.28 no.6
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• pp.815-829
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• 2020

The aim of this study is to investigate fashion activism that supports sustainability by pursuing social transformation through social media. This is achieved by publicizing the environmental and labor problems of the fashion industry. For this study, a literary survey and netnography were conducted from January 2017 to November 2020. We classified and analyzed environmental and labor issues that could be considered fashion activism on social media. The results are as follows. First, movements for conscious consumption appeared as #haulternative, #fashionourfuture, #SecondHandSeptember, and #wornwear projects. These movements are concerned with buying used goods, re-dressing clothes owned by individuals, and transforming and wearing them with new methods. Second, activism for environmental protection includes #fashionOnclimate by Global Fashion Agenda and Sustainable Fashion Matterz' #Watermatterz. These movements are directly involved in learning about the seriousness of environmental destruction caused by the fashion industry and participating in environmental protection with critical awareness. Third, the #whomademyclothes and the Clean Clothes Campaign are activism for improving the working environment, and are playing a role in publicizing labor issues by informing the general public about inadequate working conditions linked to the fashion industry. Thus, fashion activism on social media examined in this study can contribute to visualizing chronic problems that hinder sustainable development within the fashion industry.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.345-351
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• 2017

The international status of the Korean language has been elevated as the demand for studying the language among foreign students has grown sharply over the past few years. Unfortunately, foreign students face difficulties in learning the language, conflicts are also deepening between Korean and foreign students. Using Erin Sander's design research spiral, this paper investigates foreigners' Korean language learning experiences, identify the main cognitive and affective factors influencing their learning process. Research findings collected with the design analysis revealed needs and insights that offer opportunities relevant specifically for the conception, design and development of new products and services related to Korean language learning.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.79-86
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• 2019

This paper is an overview of key elements of Korea National Open University's smart mobile learning system, and an attempt to evaluate its main services relative to the FRAME model and the Mobile Learning Development Model for distance learning in higher education. KNOU improved its system architecture to one based on xMOOC e-learning content delivery while also upgrading its PC-based online/mobile learning services to facilitate an easier and more convenient access to lectures and for better interactivity. From the users' viewpoint, the upgraded 'U-KNOU Campus' allows for a more integrated search capability coupled with better course recommendations and a customized notification service. Using the new system, the students can access not only the school- and peer-issued messages via online bulletin boards but also share information and pose questions to others including to the school faculty/officials and system administrators. Additionally, a new mobile payment method has been incorporated into the system so that the students can select and pay for additional courses from anywhere. In spite of these advances, the issue of device usability and content development remain; specifically U-KNOU Campus needs to improve its instructor-learner and learner-to-learner interactivity and mobile evaluation interface.

• (The)Korea Educational Review
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• v.23 no.1
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• pp.183-204
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• 2017

Since the development of Smart technology and the advent of various Smart media, a learning environment for individual learners and the school has been changing. In the stream of changing learning environments, in 2011, the government announced SMART education strategies, introducing the term officially, "SMART education." With the governments' efforts to develop and implement SMART education in school, many policies has been enacted and many research has been conducted and increased gradually. However, as policies of SMART education have initiated in situation where there is no clear understanding in regard of SMART education, many researchers and teachers confused of SMART education and its identity and attributes, even though it has been 6 years since the concept was introduced. Unfortunately, SMART education has been implemented as one type of instructional methodology as utilizing Smart technology. Thus, in this research, we tried to build theoretical foundation of SMART education through analyzing former research on SMART education to define the attributes of SMART education. To examine how SMART education has been implemented in terms of its attributes, also, we analyzed research that conducted instructional design and implementation on SMART education in actual learning environments. As the results of former research analysis, the attributes of SMART education include Information and Communication Technology, open learning environment, self-directed learning, customized learning, and social learning. In majority of research, SMART education focused on utilizing Smart technology and media in teaching and learning environments but self-directed, and customized learning were less adapted in SMART learning environments. In the following research, how to improve educational benefits of SMART education through adapting original attributes of SMART education need to be examined.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.983-987
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• 2009

One of the critical themes in the language acquisition is its exposure to linguistic environments. Linguistic environments, which interact with infants, include not only human beings such as its parents but also artificially crafted linguistic media as their functioning elements. An infant learns a language by exploring these extensive language environments around it. Based on such large linguistic data exposure, we propose a machine learning based method on the cognitive mechanism that simulate flexibly and appropriately infant's language learning. The infant's initial stage of language learning comes with sentence learning and creation, which can be simulated by exposing it to a language corpus. The core of the simulation is a memory-based learning model which has language hypernetwork structure. The language hypernetwork simulates developmental and progressive language learning using the structure of new data stream through making it representing of high level connection between language components possible. In this paper, we simulates an infant's gradual and developmental learning progress by training language hypernetwork gradually using 32,744 sentences extracted from video scripts of commercial animation movies for children.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.267-277
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• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.