• Title/Summary/Keyword: CHAT

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A Study on the Data Literacy Education in the Library of the Chat GPT, Generative AI Era (ChatGPT, 생성형 AI 시대 도서관의 데이터 리터러시 교육에 대한 연구)

  • Jeong-Mee Lee
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.3
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    • pp.303-323
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    • 2023
  • The purpose of this study is to introduce this language model in the era of generative AI such as ChatGPT, and to provide direction for data literacy education components in libraries using it. To this end, the following three research questions are proposed. First, the technical features of ChatGPT-like language models are examined, and then, it is argued that data literacy education is necessary for the proper and accurate use of information by users using a service platform based on generative AI technology. Finally, for library data literacy education in the ChatGPT era, it is proposed a data literacy education scheme including seven components such as data understanding, data generation, data collection, data verification, data management, data use and sharing, and data ethics. In conclusion, since generative AI technologies such as ChatGPT are expected to have a significant impact on users' information utilization, libraries should think about the advantages, disadvantages, and problems of these technologies first, and use them as a basis for further improving library information services.

Design and Implementation of a Chat Application for Ad-hoc Groups (Ad-hoc 그룹을 위한 채팅 응용 프로그램 설계 및 구현)

  • Qu, JiaJie;Choi, Jongmyung
    • Proceedings of the Korea Contents Association Conference
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    • 2018.05a
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    • pp.351-352
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    • 2018
  • With the rise of the Internet era, instant messaging is playing an increasingly important role in the entire Internet market. Nowadays, most of chat softwares on the market are designed for chatting with friends. Before joining a group chat, we must be invited by your friends. On certain occasions, it is very troublesome to invite lots of people quickly if people want to build a group chat temporarily. Therefore I developed a chat application for ad-hoc groups to solve the problem. Ad-hoc groups can be used for some specific occasions for example some large meetings and gatherings. People can create a group at any time any where and other people can join the group chat fast. People that include friends and strangers all can join a group chat by scanning the QR code without adding anyone as friends.

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Data Augmentation of English Reading Comprehension Tutoring Dialogs using ChatGPT (ChatGPT 를 이용한 독해 튜터링 대화 데이터 확장)

  • Hyunyou Kwon;Sung-Kwon Choi;Jinxia Huang;Oh-Woog Kwon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.43-44
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    • 2023
  • 대화형 독해 튜터링 시스템을 위한 학생주도 대화 데이터셋 생성 및 확장에 ChatGPT 의 활용 가능성을 평가하였다. 단순히 수동으로만 구축한 기존의 데이터셋과 ChatGPT 에 의해 반자동으로 확장된 데이터셋을 비교한 결과, 구축량, 소요 시간, 비용 및 반복 작업 측면에서 ChatGPT 가 가진 유용성을 알 수 있었다. 그러나, 유형별 배분의 편중과, 부적절한 데이터 생성 등의 한계도 나타났다. Chat GPT 의 빠른 발전이 예상됨에 따라 대화형 튜터링 분야에 ChatGPT 에 의한 반자동 데이터 확장 방법이 널리 활용될 것으로 기대된다.

Analysis of ChatGPT's Coding Capabilities in Foundational Programming Courses (기초 프로그래밍 과목에서의 ChatGPT의 코딩 역량 분석)

  • Nah, Jae-Ho
    • Journal of Engineering Education Research
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    • v.26 no.6
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    • pp.71-78
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    • 2023
  • ChatGPT significantly broadens the application of artificial intelligence (AI) services across various domains, with one of its primary functions being assistance in programming and coding. Nevertheless, due to the short history of ChatGPT, there have been few studies analyzing its coding capabilities in Korean higher education. In this paper, we evaluate it using exam questions from three foundational programming courses at S University. According to the experimental results, ChatGPT successfully generated Python, C, and JAVA programs, and the code quality is on par with that of high-achieving students. The powerful coding capabilities of ChatGPT imply the need for a strict prohibition of its usage in coding tests; however, it also suggests significant potential for enhancing practical exercises in the educational aspect.

User Factors and Trust in ChatGPT: Investigating the Relationship between Demographic Variables, Experience with AI Systems, and Trust in ChatGPT (사용자 특성과 ChatGPT 신뢰의 관계 : 인구통계학적 변수와 AI 경험의 영향)

  • Park Yeeun;Jang Jeonghoon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.4
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    • pp.53-71
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    • 2023
  • This study explores the relationship between various user factors and the level of trust in ChatGPT, a sophisticated language model exhibiting human-like capabilities. Specifically, we considered demographic characteristics such as age, education, gender, and major, along with factors related to previous AI experience, including duration, frequency, proficiency, perception, and familiarity. Through a survey of 140 participants, comprising 71 females and 69 males, we collected and analyzed the data to see how these user factors have a relationship with trust in ChatGPT. Both descriptive and inferential statistical methods, encompassing multiple linear regression models, were employed in our analysis. Our findings reveal significant relationships between user factors such as gender, the perception of prior AI interactions, self-evaluated proficiency, and Trust in ChatGPT. This research not only enhances our understanding of trust in artificial intelligence but also offers valuable insights for AI developers and practitioners in the field.

Quality Evaluation of Automatically Generated Metadata Using ChatGPT: Focusing on Dublin Core for Korean Monographs (ChatGPT가 자동 생성한 더블린 코어 메타데이터의 품질 평가: 국내 도서를 대상으로)

  • SeonWook Kim;HyeKyung Lee;Yong-Gu Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.2
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    • pp.183-209
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    • 2023
  • The purpose of this study is to evaluate the Dublin Core metadata generated by ChatGPT using book covers, title pages, and colophons from a collection of books. To achieve this, we collected book covers, title pages, and colophons from 90 books and inputted them into ChatGPT to generate Dublin Core metadata. The performance was evaluated in terms of completeness and accuracy. The overall results showed a satisfactory level of completeness at 0.87 and accuracy at 0.71. Among the individual elements, Title, Creator, Publisher, Date, Identifier, Rights, and Language exhibited higher performance. Subject and Description elements showed relatively lower performance in terms of completeness and accuracy, but it confirmed the generation capability known as the inherent strength of ChatGPT. On the other hand, books in the sections of social sciences and technology of DDC showed slightly lower accuracy in the Contributor element. This was attributed to ChatGPT's attribution extraction errors, omissions in the original bibliographic description contents for metadata, and the language composition of the training data used by ChatGPT.

Exploring automatic scoring of mathematical descriptive assessment using prompt engineering with the GPT-4 model: Focused on permutations and combinations (프롬프트 엔지니어링을 통한 GPT-4 모델의 수학 서술형 평가 자동 채점 탐색: 순열과 조합을 중심으로)

  • Byoungchul Shin;Junsu Lee;Yunjoo Yoo
    • The Mathematical Education
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    • v.63 no.2
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    • pp.187-207
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    • 2024
  • In this study, we explored the feasibility of automatically scoring descriptive assessment items using GPT-4 based ChatGPT by comparing and analyzing the scoring results between teachers and GPT-4 based ChatGPT. For this purpose, three descriptive items from the permutation and combination unit for first-year high school students were selected from the KICE (Korea Institute for Curriculum and Evaluation) website. Items 1 and 2 had only one problem-solving strategy, while Item 3 had more than two strategies. Two teachers, each with over eight years of educational experience, graded answers from 204 students and compared these with the results from GPT-4 based ChatGPT. Various techniques such as Few-Shot-CoT, SC, structured, and Iteratively prompts were utilized to construct prompts for scoring, which were then inputted into GPT-4 based ChatGPT for scoring. The scoring results for Items 1 and 2 showed a strong correlation between the teachers' and GPT-4's scoring. For Item 3, which involved multiple problem-solving strategies, the student answers were first classified according to their strategies using prompts inputted into GPT-4 based ChatGPT. Following this classification, scoring prompts tailored to each type were applied and inputted into GPT-4 based ChatGPT for scoring, and these results also showed a strong correlation with the teachers' scoring. Through this, the potential for GPT-4 models utilizing prompt engineering to assist in teachers' scoring was confirmed, and the limitations of this study and directions for future research were presented.

An Empirical Study on Effect of Marketing Public Relation on Wechat Platform of China (중국 위챗 플랫폼의 MPR효과에 관한 실증연구)

  • Yang, Yu;Qing, Cheng-Lin
    • Asia-Pacific Journal of Business
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    • v.10 no.1
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    • pp.73-86
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    • 2019
  • Since its launch, WeChat has been changing the Chinese lifestyle, changing the traditional way of distribution, and changing the way companies market with the combination of information innovation and New Media. Now, WeChat plays an indispensable role in peopl's daily lives, not only in chatting software, but also in shopping, delivery, ordering, payment, and games. This study was centered on people who have used WeChat and around these backgrounds, planned study models. Through prior research, the purpose of the research is to explore the factors influencing the effects of the WeChat platform on MPR and explore the media effects of advertising attitude between WeChat platform features and MPR effects and provide basic material on its continued development. The research has shown that the reliability and diversity of the WeChat platform has a significant impact on both advertising attitude and purchase intention and propaganda intention of MPR effects. Advertising attitude has a positive impact on purchase intention and propaganda intention, and advertising attitude is shown to have a mediated effect between the WeChat platform and the MPR effects. The results of this study suggest the theoretical enlightenment of "continuous and stable development of the WeChat platform", and it is expected that marketing development plans of various social platforms will provide basic materials.

A Qualitative Research on Exploring Consideration Factors for Educational Use of ChatGPT (ChatGPT의 교육적 활용 고려 요소 탐색을 위한 질적 연구)

  • Hyeongjong Han
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.659-666
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    • 2023
  • Among the tools based on generative artificial intelligence, the possibility of using ChatGPT is being explored. However, studies that have confirmed what factors should be considered when using it educationally based on learners' actual perceptions are insufficient. Through qualitative research method, this study was to derive consideration factors when using ChatGPT in the education. The results showed that there were five key factors as follows: critical thinking on generated information, recognizing it as a tool to support learning and avoiding dependent use, conducting prior training on ethical usage, generating clear and appropriate questions, and reviewing and synthesizing answers. It is necessary to develop an instructional design model that comprehensively composes the above elements.

Development of application for recommending food recipes with foodstuffs in the refrigerator using ChatGPT and ordering foodstuffs (ChatGPT을 이용한 냉장고 보관 식료품 활용 레시피 추천 및 식료품 주문 앱 개발)

  • Seong-Mo Yang;Myeong_Jin Jeong;Jae-Hyung Jeong;Se-Ryeong Lee;Min- Seo Jeon;Tae-Jin Yun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.491-492
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    • 2023
  • 본 논문에서는 일상생활의 편의성을 높이기 위한 새로운 AI 애플리케이션 'Chat Chef'를 제안 한다. 이 앱은 사용자의 냉장고 속 재료 정보를 바탕으로 ChatGPT를 이용하여 요리 레시피를 추천하는 기능을 제공한다. 사용자는 앱을 통해 냉장고 내의 재료들을 사진으로 촬영하면, 이미지 인식을 위해 YOLOv7를 이용하여 감자, 당근, 양파 등과 같은 식료품들을 약 3,000장의 이미지 데이터를 학습하여 인식하며, 바코드를 인식하여 제품들 목록을 데이터베이스에 저장한다. 제안한 'Chat Chef' 앱은 재료 목록과 ChatGPT API를 이용하여 사용자에게 개인화된 레시피를 제공하며, 요리 과정에 대한 정보를 제공한다. 이와 같이 ChatGPT와 같은 AI 기술을 활용하여 실생활에 적용할 수 있는 활용 방안을 제시한다.

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