• English Language & Literature Teaching
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• v.17 no.4
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• pp.49-74
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• 2011

The present paper aims to explore the role of non-negotiated input and output in language acquisition in the context of free Web chat. In order to examine how input and output contribute to language acquisition, with or without meaning negotiation, the present study examined a Korean EFL learner's chat data collected over 6 months. Chat texts across 43 chat sessions were analyzed, along with her comment notes and interviews. The input and output negotiated for meaning were traced throughout all sessions to find evidence that they were linked to acquisition. Other input and output in the interaction were also traced to ascertain if they contributed to acquisition. The chat text analysis, comment notes, and the interviews revealed that the opportunities of meaning negotiation in a free Web chat context was quite limited and that the learner acquired language even in the absence of meaning negotiation. The findings suggest that input and output via Web chat, whether negotiated or non-negotiated, play their respective roles, contributing to different aspects of acquisition.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.830-833
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• 2024

As Large Language Models (LLM) like OpenAI's ChatGPT[1] continue to grow in popularity, new applications and services are expected to emerge. This paper introduces an experimental study on a smart web-builder application assistance system that combines Computer Vision with GUI object recognition and the ChatGPT (LLM). First of all, the research strategy employed computer vision technology in conjunction with Microsoft's "ChatGPT for Robotics: Design Principles and Model Abilities"[2] design strategy. Additionally, this research explores the capabilities of Large Language Model like ChatGPT in various application design tasks, specifically in assisting with web-builder tasks. The study examines the ability of ChatGPT to synthesize code through both directed prompts and free-form conversation strategies. The researchers also explored ChatGPT's ability to perform various tasks within the builder domain, including functions and closure loop inferences, basic logical and mathematical reasoning. Overall, this research proposes an efficient way to perform various application system tasks by combining natural language commands with computer vision technology and LLM (ChatGPT). This approach allows for user interaction through natural language commands while building applications.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.378-384
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• 2023

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.139-151
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• 2023

This study aims to gain insights into ChatGPT, which has recently received significant attention. The study utilized a mixed method involving case studies and news big data analysis. ChatGPT can be described as an optimized language model for dialogue. The question arises whether ChatGPT will replace Google search services, posing a potential threat to Google. It could hurt Google's advertising business, which is the foundation of its profits. With AI-based chatbots like ChatGPT likely to disrupt the web search industry, Google is establishing a new AI strategy. The study used the BIG KINDS service and analyzed 2,136 articles over six months, from August 23, 2022, to February 22, 2023. Thirty of these articles were written in 2022, while 2,106 have been reported recently as of February 22, 2023. Also, the study examined the contents of ChatGPT by utilizing literature research, news big data analysis, and use cases. Despite limitations such as the potential for false information, analyzing news big data and use cases suggests that ChatGPT is worth using.

• English Language & Literature Teaching
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• v.13 no.4
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• pp.33-58
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• 2007

The present paper aims at comparing the two modes of CMC - synchronous and asynchronous - in terms of discourse markers used in turn-initial positions. It further attempts to examine the viability and limitations of these two modes of CMC in fostering EFL learners' face-to-face conversation skills. For these purposes, the present study analyzed 33 Korean EFL learners' Web chat and E-mail exchange data. Discourse markers in the participants' Web chat transcripts and those in their E-mail transcripts were identified and then compared in terms of their frequency and functions. The analysis revealed that the participants show difference in their preference for discourse markers depending on the modes of CMC. Also, the functions of discourse markers used for Web chat showed were strikingly different from those for e-mail. Especially, e-mail discourse markers revealed greater discrepancy from the markers in face-to-face conversation. The differences were found to be attributable to the time factor involved with the turn-taking systems of the two modes of CMC, especially the degree of instantaneousness in their turn-taking. Findings suggest that the turn taking skills and discourse marker use in CMC is not applicable to face-to-face conversation contexts. Pedagogical implications are discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.74-75
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• 2023

본 논문에서는 Chat GPT API 를 활용하여 웹 대시보드를 기획하는 것을 다루고 있다. 이 대시보드는 개인과 업무에서 생성된 데이터를 통합하여 데이터 분석을 쉽게 할 수 있도록 도와주며, 머신 러닝 절차를 기반으로 화면 구성이 이루어졌다. 이를 통해 비전문가도 쉽게 데이터 전처리, 시각화, 학습, 저장소 등의 기능을 사용할 수 있다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.113-119
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• 2017

The Rich Communication Service(RCS) is a next generation mobile messaging service. Since it has been developed and managed by a wireless service provider, 3rd party application developers cannot utilize the RCS features in their apps. A few studies have been proposed to solve this problem, even though they were not viable level of deployment. This paper presents a Web-based Rich Communication Service Software Framework(WebRSF) to help the 3rd party application developers adopt RCS features easily. WebRSF converts complicated RCS protocols to simple web-based protocols for providing the RCS 1-to-1 chat service to the 3rd parties. Communication protocols between WebRSF and its clients are defined in this paper. Also, a network configuration diagram and a message flow diagram are defined. Finally, performance evaluation between the WebRSF client and the RCS client are performed to simulate the load on clients' devices. It shows that the WebRSF client has 17% less loads than the RCS client while initiating sessions, and has 25% more loads after initiating sessions.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.79-95
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• 2024

The new AI based conversational chatbot, ChatGPT, launched in November 2022, is causing a stir. There are many opinions about this being a 'threat or a promise,' and thus it is important to understand what has been said about this tool and, based on the growing literature that has emerged on the subject, demystify its effective impact on society. To analyse this impact, a systematic literature review with the support of the preferred reporting items for systematic reviews and meta-analysis protocol was used. The data, scientific documents, were collected using the main scientific databases - SCOPUS and Web of Science - and the results were presented based on a bibliometric and thematic exploration of content. The main findings indicate that people are increasingly using this chatbot in more diverse areas. Therefore, this study contributes at the practical level, aiming to enlighten people in general - both in professional and personal life - about this tool and its impacts. Also, it contributes at the theoretical level, which involves expanding understanding and elucidation of the impacts of ChatGPT in different areas of study.

• Journal of Educational Research in Mathematics
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• v.12 no.1
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• pp.109-124
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• 2002

This study investigated various effects of WBD(web-based discussion) on mathematical communication, interaction and problem solving in the classroom. We developed a web site including BBS and chat room in order to encourage students' mathematical curiosities and self-studies. The web site had been operated for 6 months. Five classes of 1st grade students were selected from an middle school in Daejon. Moreover, we analyzed several cases for interactional behavior and effect. WBD promote dialogue between a teacher and students. Analysis of feed-back from BBS revealed that student's negative attitudes could be changed to positive ones by step-by-step discussions. Moreover, collaborative learning is enhanced by on-line discussion. But the effects of WBD are affected by the character and ability of a student.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.