• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.779-790
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• 2021

Film literacy comprises the process of producing a new creation through understanding the elements that make up a film, the content of a film, and a critical and creative thinking process. Film literacy is employed in fields such as composition, science, social studies, and geography, and, additionally, it is used to cultivate humanities literacy and critical thinking skills. Yet despite the large proportion of the film script in the movie, it is not easy to find literacy education cases that use film English as a teaching method. Film English is a practical and authentic material, and is suitable as an English learning material in an EFL context like Korea. However, the approach of using films to teach and learn differs according to the content and genre of a film. Thus, the teacher may have a difficult time organizing and preparing for class. This study suggests six class activities that can be commonly applied to English classes using films based on the areas of critical, cultural, and creative (3Cs) activities. Four hundred and five college students taking Movie English classes participated in the present study and frequency analysis was conducted to find out their preferences through a questionnaire survey. The results from conducting class activities in university liberal arts classes suggest that the most preferred activities of students are related to cultural, critical, and creative, in that order. Creative activities that are far beyond English instruction utilizing various digital tools or providing additional reading materials can be a burden on learners.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.45-54
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• 2021

Jeong Sun-Ah built up her performance career for twenty years with bold and energetic acting and solidified her status as a leading actress of Korean musical since her debut. To benefit from the value of her experience this study performed an in-depth interview with her, applying the Theory of "Projection" and "Back-projection", which are the psychological principles of acting, and derived "acting(entering the roles)" and "de-acting(leaving the roles)" techniques. As result, Her acting mechanism involved emptying her ego, embodying a persona by projecting the role created by intensive exploration of materials like previous performance, film of the same title, original novel, and script, and then getting the ego back by back-projecting through dynamic activities such as overseas travel and dance. She pre-studied the roles by physically visiting sites that are important to the characters. She was unique in that she pursued a difference by changing vocal trainers for each musical production and undertook more intense physical training than vocal practice to achieve powerful singing performance. In most of her works (75%), she suffered from aftereffects such as depression, narcissism, hysteria, and insomnia due to disorder caused by breaking away from the roles. However, she relied on self-help and alternatives are needed in the future such as reinforcement of expert counselling. Jeong Sun-Ah appeared on an average of 1.6 productions per year, practiced for an average of 1.7 months, and performed for an average of 3.9 months with an average of 100 days of break between productions. Her performance record from this research demonstrates her constant preparation and passion, as well as the know-how of reserving and distributing energy. So, it has a valuable implications for acting education and self-management of actors and actress.

• 지역과문화
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• v.7 no.3
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• pp.23-48
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• 2020

Hahoebyeolsingut Talnori, which is under permanent performance, has lost its relevance to folklore and rituals of the villagers and has secured the possibility of change depending on the actor's choice. This article seeks to expand the current stuck performance of Hahoe mask play, which has great significance as a play and play for the audience. To this end, We studied the possibility of expanding the performance of Hahoe Talnori by trans-identity of the Choragi. Chorangi character derides yangban, seonbi and monk, who are representatives of the establishment. Those who have a consciousness of potential transformation, those who passively represent the masses, and those who are tacitly authorized by the audience to ridicule the ruling class. The audience feels exhilarated by the super-cool, but at the same time reduces the limits. We transformed Chorangi who is clever but cannot overcome the limits of his status, into a character with a sense of transformation by applying the method of turnning identity and changing identity of the theory of trans-identity. And I applied the method of expansion of the media conversion storytelling theory to create a new Chorangi Madang that conforms to the audience's needs and the spirit of the times. In addition to the performance of Yangban Seonbi Madang(Act of Nobleman and Scholar) which ends with an ambiguous reconciliation, we wanted to complete it in a way that even today's audiences could accept by applying the function of the Hahoebyeolsingut Talnori ambassador and the principle of implementation. And We writed it in a script. This article is meant to be an experimental study that attempted to transform traditional performing arts in the context of new creation of tradition. Preservation and transmission of traditional performing arts are important, but it is necessary to move forward according to the trend and spirit of the times.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.401-418
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• 2023

Recently, the socio-economic interest in Large Language Models (LLMs) has been growing due to the emergence of ChatGPT. As a type of generative AI, LLMs have reached the level of script creation. In this regard, it is important to address the issue of discrimination (sexism, racism, religious discrimination, ageism, etc.) in the performing arts in general or in specific performing arts works or organizations in a large language model that will be widely used by the general public and professionals. However, there has not yet been a full-scale investigation and discussion on the issue of discrimination in the performing arts in large-scale language models. Therefore, the purpose of this study is to textually analyze the perceptions of discrimination issues in the performing arts from LMMs and to derive implications for the performing arts field and the development of LMMs. First, BBQ (Bias Benchmark for QA) questions and measures for nine discrimination issues were used to measure the sensitivity to discrimination of the giant language models, and the answers derived from the representative giant language models were verified by performing arts experts to see if there were any parts of the giant language models' misperceptions, and then the giant language models' perceptions of the ethics of discriminatory views in the performing arts field were analyzed through the content analysis method. As a result of the analysis, implications for the performing arts field and points to be noted in the development of large-scale linguistic models were derived and discussed.

• Journal of the Korea Computer Graphics Society
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• v.30 no.1
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• pp.1-10
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• 2024

In immersive virtual environments including mixed reality (MR) and virtual reality (VR), avatars or agents, which are virtual humans, are being studied and applied in various ways as factors that increase users' social presence. Recently, studies are being conducted to apply generative AI as an agent to improve user learning effects or suggest a collaborative environment in an immersive virtual environment. This study proposes a novel method for interface application of a virtual assistant agent (VAA) using OpenAI's ChatGPT in an immersive virtual environment including VR and MR. The proposed method consists of an information agent that responds to user queries and a control agent that controls virtual objects and environments according to user needs. We set up a development environment that integrates the Unity 3D engine, OpenAI, and packages and development tools for user participation in MR and VR. Additionally, we set up a workflow that leads from voice input to the creation of a question query to an answer query, or a control request query to a control script. Based on this, MR and VR experience environments were produced, and experiments to confirm the performance of VAA were divided into response time of information agent and accuracy of control agent. It was confirmed that the interface application of the proposed VAA can increase efficiency in simple and repetitive tasks along with user-friendly features. We present a novel direction for the interface application of an immersive virtual environment through the proposed VAA and clarify the discovered problems and limitations so far.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.