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Topic-centered English Learning Method Using Animated Movie with Reference to Awareness of Social Issues (애니메이션을 활용한 주제 중심의 영어 학습 방안: 사회문제 인식을 중심으로)

  • Kim, Hye-Jeong
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.4
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    • pp.217-225
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    • 2024
  • This study explores the use of animation as a tool for both English learning and recognizing social problems. In addition, this study examines how topic-centered learning paired with animation affects the acquisition of English vocabulary and expressions specific to discussing social problems. To achieve these goals, the study used two animations, Zootopia and Luca, and focused specifically on discrimination and prejudice. Conversation analysis, discussion activities, and learning of vocabulary and expressions in context were conducted. To evaluate the research, pre-tests, post-tests, a questionnaire, and thinking notes containing learners' opinions were used. Pre- and post-tests were administered to determine the extent of improvement in students' vocabulary and expression learning, and they reveal a statistically significant difference between the two tests. A questionnaire and thinking notes were analyzed in order to understand learners' responses and attitudes toward the class, and the results demonstrate an overall satisfaction with this class using animation topics (81.8%). The data highlights three reasons for this satisfaction: developing an in-depth understanding of movies, enhanced awareness of social problems, and increased engagement through the use of animations. These findings highlight the importance of conducting an in-depth analysis of the targeted topic when using animation.

A Study on the Effectiveness of Generative AI Utilization in Programming Education - focusing on ChatGPT and Scratch Programming (생성형AI 활용이 프로그래밍 학습에 미치는 효과성에 관한 연구 - ChatGPT와 스크래치 프로그래밍 중심으로)

  • Kwangil KO
    • Convergence Security Journal
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    • v.24 no.3
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    • pp.33-39
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    • 2024
  • The remarkable advancement of artificial intelligence technology is bringing innovative changes to the field of education. In particular, generative AI models like ChatGPT hold great potential in self-directed programming education due to their natural conversational abilities. This study analyzed the learning effects of using ChatGPT in Scratch classes for non-SW majors. Dividing the classes into those using ChatGPT and those not, and conducting the same evaluations and surveys for the ChatGPT-utilizing group, the results showed that ChatGPT significantly enhanced learning outcomes and the utility of ChatGPT was highly evaluated in advanced learning areas such as understanding Scratch's advanced features and algorithms. This study is significant as it empirically demonstrates the potential of generative AI like ChatGPT as an effective tool in programming education.

Development of a Multicultural Communication Assistant Application Utilizing Generative AI

  • Jung-hyun Moon;Ye-ram Kang;Da-eun Kim;Ga-kyung Lee;Jae-hoon Choi;Young-Bok Cho
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.8
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    • pp.33-41
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    • 2024
  • The continuous rise in the number of multicultural households and the issue of insufficient Korean language proficiency among marriage immigrants have highlighted the need to expand support programs for multicultural families and the importance of staffing multicultural centers. This paper designs and implements a diary application that leverages AI technology to enhance communication between parents and children in multicultural families based on diary entries. The proposed technology uses OCR, machine translation, Korean language correction, and sentiment analysis AI models to facilitate diary-based conversations between parents and children, addressing linguistic barriers and fostering emotional bonds. Additionally, it aims to provide direction for the development and harmony of future multicultural societies.

Research on art contents based on 4th industrial technology -Focusing on artificial intelligence painting and NFT art- (4차 산업 기술 기반의 예술 콘텐츠 연구 -인공지능 회화와 NFT 미술을 중심으로-)

  • Bang Jinwon
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.4
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    • pp.613-625
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    • 2024
  • This study analyzed the convergence case of AI painting and NFT art, art content created based on digital technology, an innovative technology of the 4th industrial technology, and explored its characteristics. Digital technology that innovates the paradigm of life in the 21st century is being used in creative art, and AI painting and NFT art that use it as an expression tool are changing the way they perceive and accept art. AI painting using big data and artificial intelligence technology is evolving into interactive daily art, and NFT art using blockchain and NFT technology is becoming the art of the metaverse with economic and cultural values. Therefore, this study attempted to explore various aspects and values of these digital convergence arts. For the study, representative examples of AI painting and NFT art were classified into cognitive creative AI painting and language generative AI, art economic NFTs, and art and cultural NFTs, and their characteristics, contents, and meanings were analyzed. It is hoped that the results of this study will contribute to the development of AI painting and NFT art, which are digital convergence arts.

Ephedra has anti-fibrogenic effects by inhibiting the TGF-β/Smad pathway in LX-2 cells (마황(麻黃) 열수 추출물의 TGF-β/Smad 경로 억제를 통한 간섬유화 억제효능)

  • Jea Hyun Yoo;Sang Mi Park;Dae Hwa Jung;Sang Chan Kim
    • Herbal Formula Science
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    • v.32 no.2
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    • pp.141-153
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    • 2024
  • Objective : Ephedrae Herba (Ephedra) has been frequently used in the East Asian traditional medicine including Korea, China and Japan in the clinical treatment of asthma, cold and influenza etc. This study was performed to explore an anti-fibrogenic potential of Ephedra Herba water extract (EHE) using immortalized human hepatic stellate cell line, LX-2 cells. Methods : We examined the anti-fibrogenic effects of EHE on canonical pathway of transforming growth factor-β1 (TGF-β1) signaling in LX-2 cells. Cell viability was measured using the MTT assay. mRNA levels were detected by real-time PCR. Proteins expression were detected by Western blot. Results : Treatment of EHE 30 ㎍/ml did not show any cytotoxicity on LX-2 cells. Pre-treatment of EHE (30 ㎍/mL) significantly inhibited α-smooth muscle actin expression induced by TGF-β1. Additionally, EHE significantly decreased Smad2 and Smad3 phosphorylations, Smad binding element-driven luciferase activity and plasminogen activator inhibitor type 1 expression by TGF-β1. Furthermore, increases of matrix metalloproteinases 2 genes by TGF-β1 was also attenuated by EHE treatment. Conclusion : These results suggest that EHE has an ability to suppress fibrogenic process in activated HSC via inhibition of TGF-β1-TGFBR mediated canonical (Smad dependent) pathway.

Strengthening Teacher Competencies in Response to the Expanding Role of AI (AI의 역할 확대에 따른 교사 역량 강화 방안)

  • Soo-Bum Shin
    • Journal of Practical Engineering Education
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    • v.16 no.4
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    • pp.513-520
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    • 2024
  • This study investigates the changes in teachers' roles as the impact of AI on school education expands. Traditionally, teachers have been responsible for core aspects of classroom instruction, curriculum development, assessment, and feedback. AI can automate these processes, particularly enhancing efficiency through personalized learning. AI also supports complex classroom management tasks such as student tracking, behavior detection, and group activity analysis using integrated camera and microphone systems. However, AI struggles to automate aspects of counseling and interpersonal communication, which are crucial in student life guidance. While direct conversational replacement by AI is challenging, AI can assist teachers by providing data-driven insights and pre-conversation resources. Key competencies required for teachers in the AI era include expertise in advanced instructional methods, dataset analysis, personalized learning facilitation, student and parent counseling, and AI digital literacy. Teachers should collaborate with AI to emphasize creativity, adjust personalized learning paths based on AI-generated datasets, and focus on areas less amenable to AI automation, such as individualized learning and counseling. Essential skills include AI digital literacy and proficiency in understanding and managing student data.

A Study of the Behavioral Intention on Conversational ChatGPT for Tourism Information Search Service: Focusing on the Role of Cognitive and Affective Trust (ChatGPT, 대화형 인공지능 관광 검색 서비스의 행동의도에 대한 연구: 인지적 신뢰와 정서적 신뢰의 역할을 중심으로)

  • Minsung Kim;Chulmo Koo
    • Information Systems Review
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    • v.26 no.1
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    • pp.119-149
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    • 2024
  • This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

A Study on the Effect of Emotional Workers' Self-compassion and Positive Self-talk on Work Engagement and Subjective Well-being (감정노동자의 자기자비와 긍정적 자기대화가 직무몰입 및 주관적 안녕감에 미치는 영향에 관한 연구)

  • PARK, Yu Mi;YU, Eun Jin;PARK, Jong Woo
    • Journal of Korean Society for Quality Management
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    • v.52 no.3
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    • pp.459-478
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    • 2024
  • Purpose: This study aims to identify protective factors enabling emotional workers to manage stress and cope proactively. By enhancing their internal resources, it aims to provide a theoretical foundation for fostering positive outcomes and offering a basis for integrated human resource management and employee welfare. Methods: The data analysis utilized SPSS 22.0 and Smart PLS 4.0. After conducting tests for normality, exploratory factor analysis, confirmatory factor analysis, reliability analysis, measurement model validation, and structural model validation were performed. Relationships between variables were examined, and the significance and suitability of hypothesis paths were verified. Results: Firstly, it was confirmed that self-compassion and positive self-talk positively influence resilience, self-control, work engagement and subjective well-being. Secondly, resilience positively influences self-control, work engagement and subjective well-being. Thirdly, self-control positively influences work engagement but does not statistically significantly influence subjective well-being. Fourthly, work engagement positively influences subjective well-being. Fifthly, work engagement was found to mediate between self-control and subjective well-being. Conclusion: The study confirmed that self-compassion and positive self-talk serve as antecedents to enhancing emotional workers' resilience, self-control, work engagement, and subjective well-being. Additionally, by analyzing the structural relationships between these factors, it established a theoretical framework.

3D Object State Extraction Through Adjective Analysis from Informal Requirements Specs (비정형 요구사항 스펙에서 형용사 분석을 통한 3D 객체 상태 추출화)

  • Ye Jin Jin;Chae Yun Seo;Ji Hoon Kong;R. Young Chul Kim
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.10
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    • pp.529-536
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    • 2024
  • Recent advancements in AI technology have led to its application across various fields. However, the lack of transparency in AI operations makes it challenging to guarantee the quality of its outputs. Therefore, we integrate requirements engineering in software engineering with conversational AI technology to ensure procedural fairness. Traditional requirements engineering research uses grammar-centered analysis, which often fails to fully interpret the semantic aspects of natural language. To solve this, we suggest combining Noam Chomsky's syntactic structure analysis with Charles Fillmore's semantic role theory. Additionally, we extend our previous research by analyzing adjectives in informal requirement sentence structures. This enables precise emotional analysis of the main characters in comics. Based on the results of the analysis, we apply the emotional states of the objects to the states in the UML state diagram. Then, we create the 3D object with Three.js based on the object that reflects the emotional states in the state diagram. With this approach, we expect to represent the emotional state of a 3D object.

Optimum Size Selection and Machinery Costs Analysis for Farm Machinery Systems - Programming for Personal Computer - (농기계(農機械) 투입모형(投入模型) 설정(設定) 및 기계이용(機械利用) 비용(費用) 분석연구(分析硏究) - PC용(用) 프로그램 개발(開發) -)

  • Lee, W.Y.;Kim, S.R.;Jung, D.H.;Chang, D.I.;Lee, D.H.;Kim, Y.H.
    • Journal of Biosystems Engineering
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    • v.16 no.4
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    • pp.384-398
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    • 1991
  • A computer program was developed to select the optimum size of farm machine and analyze its operation costs according to various farming conditions. It was written in FORTRAN 77 and BASIC languages and can be run on any personal computer having Korean Standard Complete Type and Korean Language Code. The program was developed as a user-friendly type so that users can carry out easily the costs analysis for the whole farm work or respective operation in rice production, and for plowing, rotarying and pest controlling in upland. The program can analyze simultaneously three different machines in plowing & rotarying and two machines in transplanting, pest controlling and harvesting operations. The input data are the sizes of arable lands, possible working days and number of laborers during the opimum working period, and custom rates varying depending on regions and individual farming conditions. We can find out the results such as the selected optimum combination farm machines, the overs and shorts of working days relative to the planned working period, capacities of the machines, break-even points by custom rate, fixed costs for a month, and utilization costs in a hectare.

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