• Title/Summary/Keyword: AI, Education

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Job Counselor's Experience and Perception of Generative AI (직업상담사의 생성형 AI 활용경험 및 인식)

  • Sang-ho Bae;Hye-young Kang
    • 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.

Software Education Class Model using Generative AI - Focusing on ChatGPT (생성형 AI를 활용한 소프트웨어교육 수업모델 연구 - ChatGPT를 중심으로)

  • Myung-suk Lee
    • Journal of Practical Engineering Education
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    • v.16 no.3_spc
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    • pp.275-282
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    • 2024
  • This study studied a teaching model for software education using generative AI. The purpose of the study is to use ChatGPT as an instructor's assistant in programming classes for non-major students by using ChatGPT in software education. In addition, we designed ChatGPT to enable individual learning for learners and provide immediate feedback when students need it. The research method was conducted using ChatGPT as an assistant for non-computer majors taking a liberal arts Python class. In addition, we confirmed whether ChatGPT has the potential as an assistant in programming education for non-major students. Students actively used ChatGPT for writing assignments, correcting errors, writing coding, and acquiring knowledge, and confirmed various advantages, such as being able to focus on understanding the program rather than spending a lot of time resolving errors. We were able to see the potential for ChatGPT to increase students' learning efficiency, and we were able to see that more research is needed on its use in education. In the future, research will be conducted on the development, supplementation, and evaluation methods of educational models using ChatGPT.

The Utilization and Impact of ChatGPT in Engineering Education: A Learner-Centered Approach (공학교육에서 ChatGPT 활용의 실태 및 영향: 학습자 중심의 접근)

  • Wang, Bi;Bae, So-hyeon;Buh, Gyoung-ho
    • Journal of Engineering Education Research
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    • v.27 no.3
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    • pp.3-13
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    • 2024
  • Since the launch of ChatGPT, many college students used it extensively in various ways in their curricular learning activities. This study investigates the utilization of ChatGPT in the curriculum of first and second-year engineering students, aiming to examine its influence from a learner perspective. We explored how ChatGPT is used in each subject and learning activity to understand how learners perceive the use of ChatGPT. From the survey data on engineering college students at E university, we examined students' perception on 'shortening time to perform tasks' through ChatGPT, 'dependence on ChatGPT', 'their contribution to individual capacity building', and 'their influence on academic grade'. The majority of students reported extensive use of ChatGPT for learning activities, particularly showing high dependency in liberal arts subjects and coding-related activities. While the use of ChatGPT in liberal arts was seen as not contributing to the enhancement of individual capacity, its use in coding was positively evaluated. Furthermore, the contribution of ChatGPT to the creativity in report writing tasks was highly rated. These findings offer several important implications for the use of AI tools like ChatGPT in engineering education. Firstly, the positive impact of ChatGPT's high usability and individual-capacity enhancement in coding should be expanded to other areas of learning. Secondly, as AI technology progresses, the contribution of AI tools compared to learners is expected to increase, suggesting that students should be encouraged to effectively use AI tools to achieve their learning objectives while maintaining a balanced approach to avoid overreliance on AI.

The Necessity of an Elementary School Information Curriculum based on the Analysis of Overseas SW and AI Education (해외 SW·AI 교육 현황 분석을 통한 초등학교 정보 교과의 필요성)

  • Song, Ui-Sung;Rim, Hwa-Kyung
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.301-308
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    • 2021
  • In line with the social changes due to the Fourth Industrial Revolution, foreign countries are strengthening information education for the future of education. This study analyzed the current status of software (SW) and artificial intelligence (AI) education among different types of information education programs in elementary schools of major foreign countries, and compared them with the education provided in Korea. Compared to major foreign countries, Korea allocated very little time for software education in elementary schools, making it difficult to sufficiently cover all areas of the curriculum achievement standards. In addition, other countries recognized the importance of artificial intelligence, an important technology of the Fourth Industrial Revolution, and were providing artificial intelligence education on the basis of software education at the national level. The Korean government is also planning on providing the education at national level, but it was identified that the information education of elementary schools have many problematic issues. This study emphasized the need to establish an information curriculum for elementary schools as a way to address these issues.

Utilizing the Orange Platform for Enhancing Artificial Intelligence Education in the Department of Radiological Science at Universities (대학 방사선학과 인공지능 교육 활성화를 위한 Orange 플랫폼 이용 사례)

  • Kyoungho Choi
    • Journal of radiological science and technology
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    • v.47 no.4
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    • pp.255-262
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    • 2024
  • Although a universally accepted definition of artificial intelligence (AI) remains elusive, the terminology has gained widespread familiarity owing to its pervasive integration across diverse domains in our daily lives. The application of AI in healthcare, notably in radiographic imaging, is no longer a matter of science fiction but a reality. Consequently, AI education has emerged as an indispensable requirement for radiological technologists responsible for the field of radiology. This paper underscores this imperative and advocates for the incorporation of AI education, using the Orange platform in university radiology department as part of the solution. Furthermore, this paper presents a case study featuring machine learning analysis using structured data on exposure doses for radiation related workers and unstructured data consisting of X-ray data encompassing 69 COVID-19-infected cases and 25 individuals with normal findings. The emphasized importance of AI education for radiology professionals in this research is expected to contribute to the job stability of radiologic practitioners in the future.

A comparative study of the revised 2022 Korea mathematics curriculum and the international baccalaureate diploma program mathematics: Applications and interpretation standard level - focusing on high school statistics area

  • Soo Bin Lee;Ah Ra Cho;Oh Nam Kwon
    • Research in Mathematical Education
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    • v.27 no.1
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    • pp.49-73
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    • 2024
  • This study aims to explore the direction of high school statistics education in Korea through a comparative analysis between the revised 2022 Korea mathematics curriculum and the IBDP Mathematics: Application & Interpretation Standard Level (IBDP AI SL) Curriculum and textbooks. The study seeks to investigate the Statistics unit of the two curricula, compare chapter structures and content elements of textbooks, and explore exercises on modeling and utilization of technology tools. The results are as follows: First, the IBDP AI SL statistics covered a broader range of topics. Second, exercises in Korean high school textbooks typically inquire about one or two questions in each topic, whereas the IBDP AI SL textbook's exercises present a real-life scenario on all relevant topics through sub-questions. Third, the Korean textbook guides the utilization of technology tools only in exercises presented after completing the entire chapter or where the calculation is complex. Also, there were only a handful of modeling exercises in the Korean textbook in contrast to most of the lessons and exercises were modeling exercises in the IBDP AI SL textbook. If these findings can be integrated into teaching practices in Korea, it will provide a direction for statistics education in Korean high schools.

Analysis of Generative AI Technology Trends Based on Patent Data (특허 데이터 기반 생성형 AI 기술 동향 분석)

  • Seongmu Ryu;Taewon Song;Minjeong Lee;Yoonju Choi;Soonuk Seol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.1
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    • pp.1-9
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    • 2024
  • This paper analyzes the trends in generative AI technology based on patent application documents. To achieve this, we selected 5,433 generative AI-related patents filed in South Korea, the United States, and Europe from 2003 to 2023, and analyzed the data by country, technology category, year, and applicant, presenting it visually to find insights and understand the flow of technology. The analysis shows that patents in the image category account for 36.9%, the largest share, with a continuous increase in filings, while filings in the text/document and music/speech categories have either decreased or remained stable since 2019. Although the company with the highest number of filings is a South Korean company, four out of the top five filers are U.S. companies, and all companies have filed the majority of their patents in the U.S., indicating that generative AI is growing and competing centered around the U.S. market. The findings of this paper are expected to be useful for future research and development in generative AI, as well as for formulating strategies for acquiring intellectual property.

Application of artificial intelligence in medical education: focus on the application of ChatGPT for clinical medical education (의학 교육에서 인공지능의 응용: 임상의학 교육을 위한 ChatGPT의 활용을 중심으로)

  • Hyeonmi Hong;Youngjoon Kang;Youngjon Kim;Bomsol Kim
    • Journal of Medicine and Life Science
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    • v.20 no.2
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    • pp.53-59
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    • 2023
  • This study explores the potential use of artificial intelligence (AI)-based services, specifically ChatGPT-3.5, in medical education. The application of this technology is acknowledged as a valuable tool for simulating authentic clinical scenarios and enhancing learners' diagnostic and communication skills. To construct a case, students received ChatGPT training using a clinical ethics casebook titled "Clinical Ethics Cases and Commentaries for Medical Students and Physicians." Subsequently, a role-play script was generated based on this training. The initial draft of the script was reviewed by two medical professors and was further optimized using ChatGPT-3.5. Consequently, a comprehensive role-play script, accurately reflecting real-world clinical situations, was successfully developed. This study demonstrates the potential for effectively integrating AI technology into medical education and provides a solution to overcome limitations in developing role-play scripts within conventional educational settings. However, the study acknowledges that AI cannot always generate flawless role-play scripts and recognizes the necessity of addressing these limitations and ethical concerns. The research explores both the potential and limitations of employing AI in the early stages of medical education, suggesting that future studies should focus on overcoming these limitations while further investigating the potential applications of AI in this field.

Generative Artificial Intelligence for Structural Design of Tall Buildings

  • Wenjie Liao;Xinzheng Lu;Yifan Fei
    • International Journal of High-Rise Buildings
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    • v.12 no.3
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    • pp.203-208
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    • 2023
  • The implementation of artificial intelligence (AI) design for tall building structures is an essential solution for addressing critical challenges in the current structural design industry. Generative AI technology is a crucial technical aid because it can acquire knowledge of design principles from multiple sources, such as architectural and structural design data, empirical knowledge, and mechanical principles. This paper presents a set of AI design techniques for building structures based on two types of generative AI: generative adversarial networks and graph neural networks. Specifically, these techniques effectively master the design of vertical and horizontal component layouts as well as the cross-sectional size of components in reinforced concrete shear walls and frame structures of tall buildings. Consequently, these approaches enable the development of high-quality and high-efficiency AI designs for building structures.

Evaluating Conversational AI Systems for Responsible Integration in Education: A Comprehensive Framework

  • Utkarch Mittal;Namjae Cho;Giseob Yu
    • Journal of Information Technology Applications and Management
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    • v.31 no.3
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    • pp.149-163
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    • 2024
  • As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.