The interest about 4th Industrial Revolution was impressively increased from newspapers, iindustry, government and academic sectors. Especially AI what could be felt by the skin of many peoples, already overpassed the ability of the human's even in creative areas. Namely, now many people start fo feel that the effect of the revolution is just infront of themselves. There were several issues in this trend, the ability of deep learning by machine, the identity of the human, the change of job environment and the concern about the social change etc. Recently many studies have been made about the 4th industrial revolution in many fields like as AI(artificial intelligence), CRISPR, big data and driverless car etc. As many positive effects and pessimistic effects are existed at the same time and many preventing actions are being suggested recently, these opinions will be compared and analyzed and better solutions will be found eventually. Several educational, political, scientific, social and ethical effects and solutions were studied and suggested in this study. Clear implication from the study is that the world we will live from now on is changing faster than ever in the social, industrial, political and educational environment. If it will reform the social systems according to those changes, a society (nation or government) will grasp the chance of its development or take-off, otherwise, it will consume the resources ineffectively and lose the competition as a whole society. But the method of that reform is not that apparent in many aspects as the revolution is progressing currently and its definition should be made whether in industrial or scientific aspect. The person or nation who will define it will have the advantage of leading the future of that business or society.
The era of the Fourth Industrial Revolution is increasingly demanding mathematical competencies for virtual reality (VR), artificial intelligence (AI) and the like. In this context, this study intended to identify the basic mathematical competency levels of university freshman students in radiology department and to provide basic data thereon. For this, the diagnostic assessment of basic learning competencies for the domain of mathematics was conducted from June 17, 2019 to June 28, 2019 among 78 freshman students of radiology department at S university and D university. As a result, the university students' overall basic mathematical competency levels were diagnosed to be excellent. However, their levels in the sectors of the geometry and vector and the probability and statistics were diagnosed to be moderate, with the mean scores of 2.61 points and 2.64 points, respectively, which were found to be lower than those of the other sections. As for basic mathematical competency levels according to genders, the levels of male students and female students were diagnosed to be excellent, with the mean scores of 17.48 points and 16.29 points, respectively, showing no statistically significant difference (p>0.05). Given the small number of subjects and regional restriction, there might be some limitations in the generalization of the findings of the present study to all university freshman students and all departments. The above results suggest that it is necessary to implement various programs such as student level-based special lectures for enhancing basic mathematical competencies relating to major in order to improve the basic mathematical competencies of freshman students in radiology department, and that it is necessary to increase the students' mathematical competencies by offering major math courses in the curriculum and applying teaching-learning methods matching students' levels.
As the utilization of chatbots grows and the AI market grows, many companies are interested. And everybody is spurring growth by offering chatbot build services so that they can create chatbots. This makes chatbots easier to service on the messenger platform, which is changing the existing application market. In this paper, we present a methodology for designing and implementing existing DB-based applications as instant messenger platform-based applications, and summarize what to consider in actual implementation to provide an optimal system structure. According to this methodology, we design and implement a chatbot that serves as an teaching advisor who provides information to the students in the curriculum. The implemented application objectively visualizes the user's desired information from the user's point of view and delivers it through the interactive interface quickly and intuitively. By implementing these services and real service, it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. Enterprise legacy application will take chatbot technology as one of important digital transformation initiative.
Journal of The Korean Association of Information Education
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v.24
no.5
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pp.473-481
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2020
Data science starts with small data analysis and includes machine learning and deep learning for big data analysis. Data science is a core area of artificial intelligence technology and should be systematically reflected in the school curriculum. For data science education, The Entry also provides a data analysis tool for elementary education. In a big data analysis, data samples are extracted and analysis results are interpreted through statistical guesses and judgments. In this paper, the big data analysis area that requires statistical knowledge is excluded from the elementary area, and data science education examples focusing on the elementary area are proposed. To this end, the general data science education stage was explained first, and the elementary data science education stage was newly proposed. After that, an example of comparing values of data variables and an example of analyzing correlations between data variables were proposed with public small data provided by Entry, according to the elementary data science education stage. By using these Entry data-analysis examples proposed in this paper, it is possible to provide data science convergence education in elementary school, with given data generated from various subjects. In addition, data science educational materials combined with text, audio and video recognition AI tools can be developed by using the Entry.
The purpose of this study is to investigate the effect of software education based on physical computing on the CT ability of elementary school students. To this end, previous studies related to physical computing software education and software education in the 2015 revised curriculum were analyzed. In addition, COBL was selected among many physical computing tools on the market in consideration of the level and characteristics of learners in the school to conduct the study, and 'Professor Lee Jae-ho's AI Maker Coding with COBL' was used as the textbook. This study was conducted for 10 sessions on 135 students in 6 classes in 6th grade of H Elementary School located in Pyeongtaek, Gyeong gi-do. The results of this study are as follows. First, it was confirmed that physical computing software education linked to real life was effective in improving the CT ability of elementary school students. Second, the change in competency of CT ability by sector improved evenly from 8 to 30 points in the pre-score and post-score of computing thinking ability. Third, in this study, it was confirmed that 87% of students were very positive as a result of a survey of satisfaction with classes after real-life physical computing software education. We hope that follow-up studies will help select various regions across cities and rural areas, and prove that real-life physical computing software education for various learner members, including large and small schools, will help elementary school students improve their CT ability.
To participate in global carbon neutrality, the Korean government is also planning to carry out zero-energy building certification for all buildings by 2030 through the enforcement decree of the 'Green Building Support Act'. Accordingly, the government is providing various projects related to solar power generation, which are relatively close to life. In particular, roof-mounted photovoltaic power generation systems are attracting attention in terms of using unused space to produce energy without destroying the environment, but low power generation efficiency compared to other photovoltaic power generation facilities is pointed out as a disadvantage. Therefore, in this paper, to solve this problem, we propose an efficient solar panel angle variable system through research on the solar panel structure for single-axial solar tracking, and also consider the application environment of the roof-mounted solar power generation system. Suggests measures to prevent damage and secondary damage. In addition, it is judged that it is possible to control the solar panel based on ICT convergence and configure the accident prediction safety system to link the project-based education program.
The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.
Journal of The Korean Association of Information Education
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v.26
no.6
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pp.567-577
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2022
Interest in AI and SW education is growing as digital literacy is emphasized in the revised elementary school curriculum for 2022. There are numerous restrictions on how pupils can enhance their digital literacy because there are only 34 class hours available for information education in elementary schools. Therefore, other subjects and information education must be blended in order to ensure class hours for AI and SW instruction. In this study, we investigated the impact of S-PUMA reading instruction on the literary imagination and computational thinking of elementary school pupils. To conduct this study, two classes of sixth graders in an elementary school were chosen and split into an experimental group and a control group. Over the course of five sessions, only the experimental group received reading instruction using the S-PUMA teaching approach. It was discovered that reading instruction with the S-PUMA teaching methodology enhanced literary imagination and computational thinking. Further study is required to identify whether the improvement in creative imagination, a component of literary imagination, is a result of the S-PUMA teaching approach or a natural result of the subject matter of the lesson.
Park, Jeryang;Jung, Jinho;Nam, Kyoungphile;Lee, Ai-Ran;Cho, Kang-Hyun
Ecology and Resilient Infrastructure
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v.2
no.1
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pp.12-21
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2015
Social demand for ecological engineering and technology has increased in tandem with national economic growth in order to improve the environmental capacity of civil infrastructures. To meet this demand, the Korean Society of Ecology and Infrastructure Engineering (KSEIE) was established in January 2013 and has contributed to the development of ecological engineering technologies. However, the establishment of an educational system for human resources training in ecological engineering is still at an early stage, and it is imperative to develop a curriculum for producing the human resources that can understand and apply ecological principles and functions and that is equipped with the abilities required for ecological conservation, restoration, and creation. As part effort, the KSEIE held a forum, entitled Founding the Education for Ecological Engineering, to discuss the establishment of the education system for ecological engineering in Korea. In this paper, based on the discussions and suggestions made during the forum, we analyzed the current status of ecological engineering education in various disciplines - civil and construction engineering, biology and environment, and landscape planning - in domestic universities, and attempted to seek possible solutions based on the cases of foreign universities. Generally, ecology and other application curricula are taught as fragmented subjects and fields in domestic universities. The development of new education strategies and systematic curricula for multidisciplinary education, ecological response to climate change, and the expansion of research fields is required.
Journal of the Korea Institute of Information and Communication Engineering
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v.22
no.6
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pp.855-860
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2018
The IT technologies applying to IoT(Internet of Things), Big Data, and AI(Artificial Intelligence) are needed in the era of 4th industrial revolution. So, the IT convergence courses of computer science major which will be required in the companies in order to prepare the crises of 4th industry revolution are necessary. And, one approach to cope with this problem is the training of IT convergence man power based on NCS(National Competency Standard) education. In this paper, we propose and analyze the NCS education courses for computer science major in order to teach the students who are needed in the Korean domestic companies preparing the 4th industrial revolution. The skills and applications of Chatbot, Blockchain, and CPS(Cyber Physical System) for the post mobile and post Internet technologies are included in the proposed courses.
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