• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.99-110
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• 2023

In this study, in order to strengthen the AI utilization competency of pre-service secondary science teachers, a project activity in which pre-service teachers directly create an 'AI-based molecular structure customized learning support tool' by using Google's teachable machine was developed and applied. To this end, the program developed for 26 third-grade pre-service teachers enrolled in the Department of Chemistry Education at H University in Chungcheongbuk-do was applied for 14 sessions during extracurricular activities. Then, the perceptions of 'understanding how AI works', 'efficacy of using AI in science classes', and 'plans to utilize AI in science classes' were investigated. As a result of the study, it was found that the program developed in this study was effective in helping pre-service teachers understand the operating principle of AI technology for machine learning at a basic level and learning how to use it. In addition, the program developed in this study was found to be effective in increasing the efficacy of pre-service teachers for the use of AI in science classes. And it was also found that pre-service teachers recognized the aspect of using AI technology as a new teaching·learning strategy and tool that can help students understand science concepts. Accordingly, it was found that the program developed in this study had a positive impact on pre-service teachers' AI utilization competency reinforcement and perception improvement at the basic level. Implications of this were discussed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.37-59
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• 2024

The current application of Generative AI in education requires enhancing skills and competencies for both instructors and students in the Age of Digital Formation. The knowledge, skills, and attitudes necessary for individualized education should be cultivated in schools, along with the ability to develop AI-compatible learning resources. Today's educational environment aligns with the demands of the Generative AI Era. Consequently, there is a need for an educational system that promotes critical thinking and creativity while connecting students to the global context. This study examined the teaching and learning processes, along with educational exploration, to understand the properties of light particles and waves within a competency-based science curriculum. The analysis and research findings aimed at devising a competency-based teaching-learning method for students' understanding of light particles and waves are as follows: First, unit analysis confirmed the significance of competency-oriented education and facilitated the structuring of units on light and waves. Second, qualitative content analysis outlined the procedures for applying conceptual knowledge and functions in experiential learning, as well as the process of feedback delivery. Third, the study highlighted the need for a meticulous approach to inducing problem recognition through inquiry and discussion activities, ensuring that students, when exploring and recognizing problems independently, do not develop misconceptions.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.567-575
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• 2024

This study was conducted to provide basic data on how to use Generative AI and education to strengthen Generative AI competency in vocational counseling by confirming the experience and perception of job counselors' use of Generative AI. A questionnaire was produced based on literature research and FGI preliminary surveys, and the main contents of the questionnaire were 'experience in using Generative AI (whether to have experience, type of tool, job, educational experience, etc.) and Generative AI recognition (recognition level, usefulness, availability, educational needs, etc.). An online survey was conducted for vocational counselors, and a total of 293 data were analyzed. As a result of major research, first, there were many counselors who had no experience in using Generative AI(60%), and the response that the reason for not using it was because they did not feel the need(28%). Second, the 'degree of recognition' in the Generative AI was somewhat low (M=2.77), and 'Generative AI usefulness' was found to be at a normal level (M=3.32), and it was recognized that it would be necessary mainly for jobs related to 'vocational information'. Third, 'tool (computer use, etc.) competency' (26%) was the highest as the competency required for future vocational counselors, and 'how to use Generative AI' (57%) accounted for a high proportion of the educational content necessary to improve these competencies.

• Informatization Policy
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• v.28 no.2
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• pp.34-56
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• 2021

According to the Fourth Industrial Revolution, demand for and interest in jobs in the field of AI and data science - such as artificial intelligence/data analysts - are increasing. In order to keep pace with this trend, and to supply human resources that can effectively perform such jobs in the relevant fields in a timely manner, job seekers must develop the competencies required by the companies, and universities must be in charge of training. However, it is difficult to devise appropriate response strategies at the level of job seekers, companies and universities, which are stakeholders in terms of supplying suitably competent personnel. Therefore, the purpose of this study is to determine which competencies are required in practice in order to cultivate and supply human talents equipped with the necessary job competencies, and to propose plans for the development of the required competencies at the university level. In order to identify the required competencies in the field of AI and data science, data on job postings on the LinkedIn site, the recruitment platform, were analyzed using text mining techniques. Then, research was conducted with the aim of devising and proposing concrete plans for competency development at the university level by comparing and verifying the results of the international graduate school curriculum in the field of AI and data science, and the interview results with the hiring managers, respectively, with the results of the topic model.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.425-431
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• 2021

In this study, in order to develop a manual for the AI convergence education competency strengthening project, project personnel were interviewed and an overall analysis of the business process was made. As a result of analysis, the manual includes methods to solve problems currently being raised in the field such as recruitment of graduate students, education program management, academic registration management, and budget management. In order to increase the continuity and efficiency of the project, it is necessary to build an administrative management site that provides information on the overall project, to strengthen publicity for general teachers about AI convergence education, and meet the educational needs and level of enrolled students.

• 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.

• 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.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.62-68
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• 2022

Evaluation as learning is important for the learner competency test, and the applicable method is studied. Assessment is the role of diagnosing the current learner's status and facilitating learning through appropriate feedback. The system is insufficient to enable process-oriented evaluation in small educational institute. Focusing on becoming familiar with the AI through experience can end up simply learning how to use the tools or just playing with them rather than achieving ultimate goals of AI education. In a previous study, the experience way of AI education with PLAY model was proposed, but the assessment stage is insufficient. In this paper, we propose ELAS (Experiential K-12 AI education Learning Assessment System) for small educational institute. In order to apply the Assessment factor in in this system, the AI-factor is selected by researching the goals of the current SW education and AI education. The proposed system consists of 4 modules as Assessment-factor agent, Self-assessment agent, Question-bank agent and Assessment -analysis agent. Self-assessment learning is a powerful mechanism for improving learning for students. ELAS is extended with the experiential way of AI education model of previous study, and the teacher designs the assessment through the ELAS system. ELAS enables teachers of small institutes to automate analysis and manage data accumulation following their learning purpose. With this, it is possible to adjust the learning difficulty in curriculum design to make better for your purpose.

• Educational Technology International
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• v.24 no.2
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• pp.143-168
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• 2023

This study aims to analyze the perceptions and educational needs of pre-service teachers for the use of Artificial Intelligence (AI) in education. To this end, we collected survey data from 25 undergraduate students who were enrolled in a teacher education college in Seoul. The purpose of the survey was to measure the importance and current performance for instructional AI use based on the technological, pedagogical, and content knowledge (TPACK) framework, and to explore the priority of educational needs using Borich's needs analysis and the Locus for Focus model. The results of the study confirmed that Ethics and TPK competencies are prioritized. Additionally, the results indicated a high demand for practical knowledge that can be implemented in the practice of education. Based on the results, it is necessary to develop a teacher education program that focuses on ethical aspects and teaching strategy competencies in AI-based education.