• Title/Summary/Keyword: AI core competency

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Artificial intelligence ethical awareness according to the core competency level among dental hygiene students (치위생 전공 학생들의 핵심역량 수준에 따른 인공지능 윤리의식)

  • Hye-Sun Shin;Seon-Ju Sim
    • Journal of Korean society of Dental Hygiene
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    • v.24 no.5
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    • pp.503-512
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    • 2024
  • Objectives: This study investigated the ethical awareness regarding artificial intelligence (AI) among dental hygiene students based on core competency levels and proposed a competency-based educational approach to improve AI ethical awareness. Methods: Eighty-six dental hygiene students participated in the study and provided informed consent. The core competency survey tool included innovation, communication, relations, and services. The AI ethical awareness survey tool was divided into eight categories, each with 24 questions: responsibility, stability and reliability, non-discrimination, transparency and explainability, people-centered service, employment, tolerance and limits, and robot rights. Results: The group with high core competency had higher levels of AI ethical awareness (p<0.05), particularly in terms of responsibility, transparency, and people-centered service. The level of AI ethical awareness was significantly correlated with the relationship competency and service competency (p<0.05). Conclusions: These results highlight the association between AI ethical awareness and core competencies. These results suggest that competency-based education in universities is critical for improving AI ethical awareness. Furthermore, we intend to use the findings as preliminary data to suggest a direction for competency-centered education to improve AI ethical awareness.

A Study on the Standard AI Developer Job Training Track Based on Industry Demand

  • Lee, Won Joo;Kim, Doohyun;Kim, Sang Il;Kim, Han Sung
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.251-258
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    • 2022
  • In this paper, we propose a standard AI developer job training track based on industry needs. The characteristic of this curriculum is that it can minimize the mismatch of AI developer job competency between industries and universities. To develop an AI developer job training track, a survey will be conducted for AI developers working in industrial fields. In this survey, among the five NCS-based AI developer jobs, job analysis is conducted by deriving AI developer jobs with high demand for manpower in industrial fields. In job analysis, the core competency unit elements of the job are selected, and knowledge, skills, tools, etc. necessary to perform the core competency unit elements are derived. In addition, a standard AI developer job curriculum is developed by deriving core subjects and road-map that can educate knowledge, skills, tools, etc. In addition, we present an efficient AI developer job training method using the standard AI developer job training course proposed in this paper.

Development of checklist questions to measure AI core competencies of middle school students (중학생의 AI 핵심역량 측정을 위한 체크리스트 문항 개발)

  • Eun Chul Lee;JungSoo Han
    • Journal of Internet of Things and Convergence
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    • v.10 no.3
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    • pp.49-55
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    • 2024
  • This study was conducted with the purpose of developing a checklist of questions to measure middle school students' AI capabilities. To achieve the goal of the study, literature analysis and question development Delphi survey were used. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements are understanding of artificial intelligence (5 elements), artificial intelligence thinking (5 elements), utilization of artificial intelligence (4 elements), artificial intelligence ethics (6 elements), and artificial intelligence social-emotion (6 elements). elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 31 questions were developed. The developed questions were verified through the first Delphi survey, and 10 questions were revised according to the revision opinions. The validity of 31 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the level of reliability of measurement results increases.

Development of checklist questions to measure AI capabilities of elementary school students (초등학생의 AI 역량 측정을 위한 체크리스트 문항 개발)

  • Eun Chul Lee;YoungShin Pyun
    • Journal of Internet of Things and Convergence
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    • v.10 no.3
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    • pp.7-12
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    • 2024
  • The development of artificial intelligence technology changes the social structure and educational environment, and the importance of artificial intelligence capabilities continues to increase. This study was conducted with the purpose of developing a checklist of questions to measure AI capabilities of elementary school students. To achieve the purpose of the study, a Delphi survey was used to analyze literature and develop questions. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements consisted of understanding artificial intelligence (6 elements), artificial intelligence thinking (4 elements), artificial intelligence ethics (4 elements), and artificial intelligence social-emotion (3 elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 19 questions were developed. The developed questions were verified through the first Delphi survey, and 7 questions were revised according to the revision opinions. The validity of 19 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the measurement results of competency are raised to a reliable level.

A Core Competency Model for Design Leadership Through Appreciative Inquiry (Appreciative Inquiry를 이용한 디자인 리더십 핵심역량 모델)

  • Lee, Han-Seung;Shin, Wan-Seon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.1
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    • pp.167-176
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    • 2019
  • The purposes of this study are first to identify the core competences of design leadership and second to propose the characteristic and effective leadership capabilities required in the design field. To propose the capabilities of reliable and meaningful core competency of design leadership, we identified core competencies through a group of experts from the top group of design leaders (Design executives, head of the design institute) rather than using a survey study based on unspecified designers. In addition, the unique interview method, AI (Appreciated Inquiry) was also used to share the actual experiences and philosophies of the interviewers, regardless of the core competencies. This study revealed that the core competences of design leadership were different from those of conventional general leadership and MOT (Management of Technology) leadership capabilities. Besides, it provided opportunities for leaders in other fields to understand and collaborate on characteristics of the design field, while demonstrating the necessity and justification of unique leadership traits in the field of design.

A Study on the Composition of Factors in Teaching Competence Using Artificial Intelligence of Pre-service Early Childhood Teachers (예비 유아 교사들의 인공지능 활용 교육역량 요인 구성 연구)

  • Eunchul Lee
    • Journal of Christian Education in Korea
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    • v.72
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    • pp.183-203
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    • 2022
  • The purpose of this study is to construct factors of AI education utilization competency. AI education utilization competency is used as basic data for education to enhance the AI education competency of pre-service early childhood teachers. To this end, 7 studies related to competency factors and models were selected by searching for previous studies. Seven preceding studies were analyzed. As a result, 18 competency factors were extracted, including understanding of artificial intelligence. The extracted competency elements were divided into six areas, which are divided into understanding subject knowledge through coding, class preparation, class management, class result feedback, class guidance, and self-development. And 15 factors were constructed. The draft formed through coding was improved through review by three early childhood education experts. Factors improved through expert review were structured by classifying them into knowledge, skills, and attitudes to organize the curriculum. The validity of the structured competency factor was verified through expert Delphi. As a result of the Delphi verification, all factors were converged in the first survey. Through this, 6 competency areas, 11 competency factors, and 19 competency factors were composed of knowledge, 10 skills, and 5 attitudes. The implication is that the competency factors presented as a result of this study can be used as basic data for organizing a curriculum to improve the ability of pre-service early childhood teachers to use artificial intelligence education.

A Study on the Understanding and Solving Tasks of AI Convergence Education (AI 융합교육의 이해와 해결 과제에 대한 고찰)

  • Sook-Young Choi
    • Journal of Industrial Convergence
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    • v.21 no.1
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    • pp.147-157
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    • 2023
  • In this study, we approached from the perspective of AI convergence education in elementary, middle and high schools to understand AI convergence education. We examined what capabilities AI convergence education ultimately seeks to pursue, and analyzed various examples of AI convergence education in three dimensions: core curriculum, convergence model, AI learning elements and learning activities. In addition, factors to be considered in order for AI convergence education to be actively carried out include the cultivation of AI convergence education capabilities of teachers, the development and dissemination of AI teaching and learning methods and teaching and learning models, and evaluation methods for AI convergence education.

A Case Study on Growth Through Coupled Process Open Innovation Open Innovation in the Faculty Startup Ecosystem: From the Perspective of Core Competency Theory (교원창업 생태계에서 결합형 오픈이노베이션을 통한 성장 사례 연구: 핵심역량이론 관점에서)

  • Changwon Yoon;Jeahong Park;Youngwoo Sohn;Youngjin Kim;Yeoungho Seo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.173-186
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    • 2024
  • This paper analyzes a case of successful faculty entrepreneurship through a coupled process of open innovation in a university context, using the core competency theory perspective. Initially, the current state of faculty entrepreneurship is examined, and the effects of interdisciplinary coupled processes of open innovation are explored, focusing on the case of 'Omotion Inc.,' a startup utilizing generative AI technology for hyper-realistic 3D virtual human experiences. The research methodology involves in-depth interviews with Omotion Inc.'s co-founders, technology commercialization professionals, and experts in the field, followed by analysis based on foundational theories. Applying the core competency theory, this paper scrutinizes the process of integrating diverse expertise and technologies from various academic disciplines. The analysis goes beyond the limitations of faculty entrepreneurship confined to a single technology-centric research domain. Instead, it explores the possibilities of enhancement and value creation through coupled processes, providing practical implications for the university entrepreneurial ecosystem. The aim is to extend the traditional roles of education and research within the university, presenting a role in economic value creation beyond the boundaries of conventional faculty entrepreneurship. Through the collaboration of two faculty members, this study showcases the creation of novel technology and business models. It establishes that successful coupled processes of open innovation in faculty entrepreneurship, from a core competency theory perspective, require the entrepreneurial firm to possess (1) entrepreneurial capabilities, (2) technological capabilities, and (3) networking capabilities. The implications of this research highlight the positive impact of coupled processes of open innovation in faculty entrepreneurship, as evidenced by the Omotion Inc. case, offering guidance on entrepreneurial directions for university members preparing for entrepreneurship.

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Evolution of Business Model: From Plug To Platform - Dawon DNS Business Case- (비즈니스 모델의 진화: 플러그에서 플랫폼으로 -다원 DNS IoT 기술의 사례-)

  • Park, MinHyuk;Yeo, Unnam;Lee, Jungwoo
    • Journal of Information Technology Services
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    • v.20 no.5
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    • pp.105-118
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    • 2021
  • As we enter the era of the 4th industrial revolution, information and communication technologies, including artificial intelligence and big data, are converging throughout society. Especially, as the importance of the social foundation of hyper-connection grows, the social influence of IoT, a network of connecting objects, people, and various entities, is also gradually expanding. In addition, as a pandemic, COVID-19, continues, interests in untact-oriented technology and service development are growing more than ever, and each company is trying to establish a core competency strategy to gain an edge in competition in the changing society. This study is a case study centered on Dawon DNS, a company that provides an IoT-based AI smart plug platform. Dawon DNS is broadening its services while developing products by applying advanced technologies, and this study is aiming to investigate the core competencies of the business evolution process. The obtained result of this study will provide implications for companies to become more competitive by suggesting the attitudes and strategies that startups should have during the transforming business environment.

Digital Human Empathy Index (DHEI) for the Era of Human-AI Symbiosis (AI와 인간 공생의 시대를 위한 디지털휴먼공감지표 개발)

  • Rhee, Hyunjung
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.1-16
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    • 2022
  • The current AI technology has been developing rapidly enough to realize or even exceed the level of abilities that only humans had in the past. In the near future, it is predicted that humans and AI will influence each other as members of the metaverse society. Therefore, this study emphasizes the importance of empathy as a core competency for humans to pursue happiness while maintaining the dignity of humans in the era when AI and humans will coexist in the metaverse. In this study, 'Digital Human Empathy Index (DHEI)' is developed that reflects the social nature of computer-mediated communication in the metaverse As a result, DHEI consisted of a total of 7 factors, which are Perspective Taking, Self/Other Awareness, Contextual Understanding of Systemic Barriers, Impact Assessment, Solidarity, Being Peaceful, and Anthropomorphism. This study is expected to contribute to setting the direction of future education by suggesting a new measure of empathy.