• Title/Summary/Keyword: education using AI

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In the Digital Big Data Classroom Reality and Application of Smart Education : Learner-Centered Education using Edutech (디지털 빅데이터 교실에서 스마트교육의 실제와 활용 : 에듀테크를 활용한 학습자 중심 교육)

  • Kim, Seong-Hee
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.4
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    • pp.279-286
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    • 2021
  • In this study, we looked at the appearance of Edutech, which is being put into the educational field after Corona 19, with the advent of the 4th industrial revolution. In the era of the 4th industrial revolution, the infrastructure, data, and service of Smart Stick that actively utilized ICT became the main pillars of smart education. In particular, smart education is being implemented through e-learning, smart learning, and edutech, and on this basis, it has become possible through the expansion and use of the Internet and computers, the dissemination of smart devices, and a software foundation using big data. Based on this, it was confirmed that Edutech is being implemented through the establishment of a quarantine safety net, a learning safety net, and a care safety net for individual learners and safe life based on artificial intelligence. Lastly, in order for edutech education using big data to become a discourse for everyone, it is necessary to consider artificial intelligence and ethics in the use and application of edutech.

Pattern Recognition and AI Education System Design Proposal for Improving the Achievement of Non-face-to-face (E-Learning) Education (비대면(이러닝) 교육 성취도 향상을 위한 패턴인식 및 AI교육 시스템 설계 구축)

  • Lee, Hae-in;Kim, Eui-Jeong;Chung, Jong-In;Kim, Chang Suk;Kang, Shin-Cheon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.280-283
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    • 2022
  • This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

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Dynamic performance using artificial intelligence techniques and educational assessment of nanocomposite structures

  • Han Zengxia;M. Nasihatgozar;X. Shen
    • Steel and Composite Structures
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    • v.53 no.1
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    • pp.115-121
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    • 2024
  • The present paper deals with a comprehensive study about dynamic performance and educational economic assessment of nanocomposite structures, while it focuses on truncated conical shells. Advanced structure dynamic behavior has been analyzed by means of AI techniques, which allow one to predict and optimize their performances with good accuracy for different loading and environmental conditions. The incorporation of the AI method significantly enhances the computational efficiency and is a powerful tool in designing nanocomposites and for their structural analysis. Further, an educational assessment is provided in the context of cost and practicality related to such structures in engineering education. This study showcases the capabilities of AI-enabled methods with regard to cost reduction, improvement of structural efficiency, and enhancement of learning engagement for students through certain practical examples on state-of-the-art nanocomposite technology. The results also confirm a remarkable capability of artificial intelligence regarding the optimization of both dynamic and economic aspects, which could be highly valued for further development of nanocomposite structures.

A Study on Public Library Book Location Guidance System based on AI Vision Sensor

  • Soyoung Kim;Heesun Kim
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.3
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    • pp.253-261
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    • 2024
  • The role of the library is as a public institution that provides academic information to a variety of people, including students, the general public, and researchers. These days, as the importance of lifelong education is emphasized, libraries are evolving beyond simply storing and lending materials to complex cultural spaces that share knowledge and information through various educational programs and cultural events. One of the problems library user's faces is locating books to borrow. This problem occurs because of errors in the location of borrowed books due to delays in updating library databases related to borrowed books, incorrect labeling, and books temporarily located in different locations. The biggest problem is that it takes a long time for users to search for the books they want to borrow. In this paper, we propose a system that visually displays the location of books in real time using an AI vision sensor and LED. The AI vision sensor-based book location guidance system generates a QR code containing the call number of the borrowed book. When the AI vision sensor recognizes this QR code, the exact location of the book is visually displayed through LED to guide users to find it easily. We believe that the AI vision sensor-based book location guidance system dramatically improves book search and management efficiency, and this technology is expected to have great potential for use not only in libraries and bookstores but also in a variety of other fields.

A Study of AI Education Program Based on Big Data: Case Study of the General Education High School (빅데이터 기반 인공지능 교육프로그램 연구: 일반계 고등학교 사례를 중심으로)

  • Ye-Hee, Jeong;Hyoungbum, Kim;Ki Rak, Park;Sang-Mi, Yoo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.1
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    • pp.83-92
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    • 2023
  • The purpose of this research is to develop a creative education program that utilizes AI education program based on big data for general education high schools, and to investigate its effectiveness. In order to achieve the purpose of the research, we developed a creative education program using artificial intelligence based on big data for first-year general high school students, and carried out on-site classes at schools and a validation process by experts. In order to measure the creative problem-solving ability and class satisfaction of high school students, a creative problem-solving ability test was conducted before and after the program application, and a class satisfaction test was conducted after the program. The results of this study are as follows. First, AI education program based on big data were statistically effective to improve the creative problem solving ability according to independent sample t test about 'problem discovery and analysis', 'idea generation', 'execution plan', 'conviction and communication', and 'innovation tendency' except 'execution', 'the difference between pre- and post-scores of male student and female student' on first year high school students. Secondly, in satisfaction conducted after classes of AI education program based on big data, the average of 'Satisfaction', 'Interest', 'Participation', 'Persistence' were 3.56 to 3.92, and the overall average was 3.78. Therefore, it was investigated that there was a lesson effect of the AI education program based on big data developed in this research.

Study on the Perception of Workers and Supervisors about AI Assistants (AI 비서에 대한 직무 종사자와 관리자의 인식 유형 연구)

  • Lee, Seon Mi;Yun, Haejung
    • Knowledge Management Research
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    • v.19 no.2
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    • pp.187-203
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    • 2018
  • The purpose of this study was to investigate the perception about AI assistants and the differences between two groups, workers(secretaries) and supervisors(bosses), using the Q-methodology which has an advantage in understanding the types of subjective perceptions. Through literature reviews and interviews, 34 Q-samples were extracted, and then Q-sorting was conducted by P-samples(20 workers and 15 supervisors). As a result of Q-sorting, the types and characteristics of AI assistants perceived by each P-sample were explained. The perception of the workers divided into five distinct types, and the perception of the supervisors was divided into three distinct types. The most crucial factors in distinguishing between workers and supervisors' perceptions depend on whether they are capable of performing certain tasks and whether they can replace existing secretarial jobs. This study, as the primary research on AI assistants, can help to redefine the work that can be replaced by AI and the work that only people can do, and thus to establish education, recruitment, and training plans.

The Perception of Pre-service English Teachers' use of AI Translation Tools in EFL Writing (영작문 도구로서의 인공지능번역 활용에 대한 초등예비교사의 인식연구)

  • Jaeseok Yang
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.121-128
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    • 2024
  • With the recent rise in the use of AI-based online translation tools, interest in their methods and effects on education has grown. This study involved 30 prospective elementary school teachers who completed an English writing task using an AI-based online translation tool. The study focused on assessing the impact of these tools on English writing skills and their practical applications. It examined the usability, educational value, and the advantages and disadvantages of the AI translation tool. Through data collected via writing tests, surveys, and interviews, the study revealed that the use of translation tools positively affects English writing skills. From the learners' perspective, these tools were perceived to provide support and convenience for learning. However, there was also recognition of the need for educational strategies to effectively use these tools, alongside concerns about methods to enhance the completeness or accuracy of translations and the potential for over-reliance on the tools. The study concluded that for effective utilization of translation tools, the implementation of educational strategies and the role of the teacher are crucial.

Development of Artificial Intelligence Convergence Education Program for Elementary Education Using Decision Tree (의사 결정 나무를 활용한 초등 인공지능 융합 교육 프로그램 개발)

  • Hyunwoo Moon;Youngjun Lee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.227-228
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    • 2023
  • 정부의 인공지능 국가전략을 통해 인공지능 교육은 초등학교에서도 필수교육으로 대두되고 있다. 또한 인공지능 소양을 습득하기 위해 타 교과와 융합한 인공지능 융합 교육의 필요성이 증가하고 있고, 인공지능 발달에 대한 수학의 역할을 고려하여 수학 교과를 통해 인공지능의 이해를 기르는 것이 강조되고 있다. 따라서 본 연구에서는 수학 교과와 인공지능 교과가 융합한 인공지능 융합 교육 프로그램을 개발하기 위해 초등학교 3~4학년 수학 교과의 도형 분류를 의사 결정 나무 모델을 활용하여 가르치는 인공지능 융합 교육 프로그램을 개발하였다. 본 연구를 통해 개발된 프로그램은 초등학생의 인공지능 개념학습을 통한 인공지능 기초소양 함양뿐만 아니라 수학 교과의 이해 및 성취도 향상에 도움이 될 것으로 기대된다.

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Development and Application of Ethics Education STEAM Projects using DeepFake Apps (딥페이크 앱 활용 윤리교육 융합 프로젝트의 개발 및 적용)

  • Hwang, Jung;Choe, Eunjeong;Han, Jeonghye
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.405-412
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    • 2021
  • To prevent problems such as portrait rights, copyright, and cyber violence, an ethics education STEAM projects using deepfake apps using AI technology were developed and applied. The Deepfake apps were screened, and the contents of the elementary school curriculum were reconstructed. The STEAM project as creative experiential activities was mainly operated by the UCC activities, and applied the info-ethics awareness measurement test based on the planned behavior theory. The social STEAM project as money (financial) education was qualitatively analyzed. It was found that this STEAM classes using AI technology app significantly enhances the ethical awareness of information communication.

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology

  • Eui Jin Hwang;Ji Eun Park;Kyoung Doo Song;Dong Hyun Yang;Kyung Won Kim;June-Goo Lee;Jung Hyun Yoon;Kyunghwa Han;Dong Hyun Kim;Hwiyoung Kim;Chang Min Park;Radiology Imaging Network of Korea for Clinical Research (RINK-CR)
    • Korean Journal of Radiology
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    • v.25 no.7
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    • pp.613-622
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    • 2024
  • Objective: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). Materials and Methods: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. Results: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. Conclusion: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.