• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.113-121
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• 2021

This study was intended to present an online survey and analysis of the survey results after the operation of the AI education leading school initiation workshop consulting training and the creative convergence type information education room consulting training. Through this, it was confirmed that there is a perception that support such as AI education leading school consulting training is necessary, and the network should be activated to share best practices and an efficient and flexible operating system in terms of operation of leading schools nationwide. could In addition, while the subjects of the survey recognized the importance of AI education-related competency, it was identified that they had low awareness of their AI education-related competency, and recognized the need for various support for systematic and customized AI education-related competency reinforcement.

• Therapeutic Science for Rehabilitation
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• v.12 no.1
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• pp.23-35
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• 2023

Objective : This study is to examine the practical use of clinical observational evaluation of sensory integration therapy and the difficulty and importance of measuring results for each sub-item, and through this, to confirm the usefulness of the application of Artificial Intelligence measurement technology in clinical observational measurement and the need for application. Methods : The questionnaire consisted of the actual use of the sensory integration evaluation tool, the difficulty of measurement for each detailed item of clinical observation, the usefulness of AI measurement technology, the importance of evaluation for each detailed item, and the need for developing AI measurement technology. Results : The detailed items that were difficult to measure during clinical observation were the Finger-to-Nose Test and Postural control (71.0%), followed by Eye movement and Protective Extension Test (67.7%). 83.9% of the study subjects answered that it would be useful to apply AI measurement technology when observing images. Postural control (on the ball) (90.3%) was the highest item that answered that AI measurement technology was needed, followed by Eye movement (83.9%), and Prone Extension and Protective Extension Test (77.4%). Conclusion : The results confirmed the desire of therapists that clinical observation is an important evaluation tool in the field of child occupational therapy in Korea.

• The Journal of Information Systems
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• v.33 no.1
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• pp.1-30
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• 2024

Purpose The purpose of this study is to examine the customer experience of generative AI among office workers aged 30 to 40, investigating usability, usefulness, and affect, and understanding concerns and expectations. Design/Methodology/Approach This research used Q methodology to assess the customer experience of generative AI. Users are engaged in a problem-solving journey, and data is collected by having participants rank 36 statements based on usability, usefulness, and affect, referred to as the three goals of User Experience. Participants use a forced distribution table with a scale from -5 to +5 to indicate the subjective importance of each statement. The results identified four groups, reflecting different perspectives and attitudes toward generative AI. Findings Participants express overall comfort with generative AI, perceive AI as more knowledgeable in unfamiliar domains, but harbor doubts about AI's understanding. Disagreements emerge on AI replacing humans, the value of unique human roles, data confidentiality, fears of AI advancement, and emotional impacts. Identified four groups: Users who treat AI as a soulless assistant and are active in business use, Uncle users who want to use new technologies properly and are not afraid of technology, users who recognize the limits of AI despite its efficiency, and users who require strong verification in the future. It has the potential to guide future guidelines, ethical codes, and regulations for the appropriate use of AI. In addition, this approach lays the groundwork for future empirical analyses of generative AI.

• Journal of the Korea Society of Computer and Information
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• v.29 no.11
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• pp.353-369
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• 2024

This paper presents strategies for enhancing productivity and strengthening global competitiveness as the domestic shipbuilding industry transitions into the era of Artificial Intelligence Transformation (AX), moving beyond digital transformation. Historically a labor-intensive industry, shipbuilding has evolved into smart shipyards powered by automation and digitalization, with increasing emphasis on green regulations and the importance of green fuels. The urgent adoption of alternative fuels, such as ammonia and liquid hydrogen, is critical in this context. However, the industry faces new challenges amid intensifying global competition and rapid technological changes. This study analyzes both domestic and international cases of AI transformation and the adoption of eco-friendly fuels in shipbuilding companies, proposing ways to manage risks through the establishment of AI governance to ensure sustainable growth. In particular, by utilizing the backcasting method, the study sets short-term, mid-term, and long-term goals while deriving phased strategies to provide significant insights and implications for policy formulation and corporate strategies aimed at the AI transformation of the domestic shipbuilding industry while complying with environmental regulations.

• Research in Mathematical Education
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• v.26 no.4
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• pp.333-349
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• 2023

Recently, AI has become a crucial tool in mathematics education due to advances in machine learning and deep learning. Considering the importance of AI, examining teachers' beliefs about AI in mathematics education (AIME) is crucial, as these beliefs affect their instruction and student learning experiences. The present study developed a scale to measure preservice teachers' (PST) beliefs about AIME through factor analysis and rigorous reliability and validity analyses. The study analyzed 202 PST's data and developed a scale comprising three factors and 11 items. The first factor gauges PSTs' beliefs regarding their roles in using AI for mathematics education (4 items), the second factor assesses PSTs' beliefs about using AI for mathematics teaching (3 items), and the third factor explores PSTs' beliefs about AI for mathematics learning (4 items). Moreover, the outcomes of confirmatory factor analysis affirm that the three-factor model outperforms other models (a one-factor or a two-factor model). These findings are in line with previous scales examining mathematics teacher beliefs, reinforcing the notion that such beliefs are multifaceted and developed through diverse experiences. Descriptive analysis reveals that overall PSTs exhibit positive beliefs about AIME. However, they show relatively lower levels of beliefs about their roles in using AI for mathematics education. Practical and theoretical implications are discussed.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

• Knowledge Management Research
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• v.20 no.2
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• pp.25-42
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• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.19-24
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• 2024

The future military combat environment is rapidly expanding the role and importance of artificial intelligence (AI) in defense, aligning with the current trends of declining military populations and evolving dynamics. Particularly, in the civilian sector, AI development has surged into new domains based on foundation models, such as OpenAI's Chat-GPT, categorized as Super-Giant AI or Hyperscale AI. The U.S. Department of Defense has organized Task Force Lima under the Chief Digital and AI Office (CDAO) to conduct research on the application of Large Language Models (LLM) and generative AI. Advanced military nations like China and Israel are also actively researching the integration of Super-Giant AI into their military capabilities. Consequently, there is a growing need for research within our military regarding the potential applications and fields of application for Super-Giant AI in weapon systems. In this paper, we compare the characteristics and pros and cons of specialized AI and Super-Giant AI (Foundation Models) and explore new application areas for Super-Giant AI in weapon systems. Anticipating future application areas and potential challenges, this research aims to provide insights into effectively integrating Super-Giant Artificial Intelligence into defense operations. It is expected to contribute to the development of military capabilities, policy formulation, and international security strategies in the era of advanced artificial intelligence.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.286-292
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• 2023

This article is set against the backdrop of the rapid development of the metaverse and artificial intelligence technologies, and aims to explore the possibility and potential impact of integrating AI technology into the traditional 3D animation production process. Through an in-depth analysis of the differences when merging traditional production processes with AI technology, it aims to summarize a new innovative workflow for 3D animation production. This new process takes full advantage of the efficiency and intelligent features of AI technology, significantly improving the efficiency of animation production and enhancing the overall quality of the animations. Furthermore, the paper delves into the creative methods and developmental implications of artificial intelligence technology in real-time rendering engines for 3D animation. It highlights the importance of these technologies in driving innovation and optimizing workflows in the field of animation production, showcasing how they provide new perspectives and possibilities for the future development of the animation industry.

• Annual Conference of KIPS
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• 2024.10a
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• pp.912-913
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• 2024

본 논문은 'AI 튜터와 함께하는 매칭 플랫폼' 개발 과정에서의 데이터 수집 및 정제에 대해 다룬다. 이 플랫폼은 사용자에게 개인화된 멘토 매칭 및 강의 추천 서비스를 제공하며, 이를 위해 웹크롤링을 통해 데이터를 수집하고, 그 데이터를 정제하는 과정을 거쳤다. 특히, 요리 레시피 데이터를 기반으로 한 취미 레벨 테스트 기능이 포함되어 있으며, 정제된 데이터를 통해 딥러닝 기반의 추천 알고리즘과 AI 튜터링 시스템을 구축했다. 본 연구는 이러한 시스템이 사용자 맞춤형 학습 경험을 제공하는 데 어떻게 기여하는지 논의한다.