• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.749-756
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• 2019

Big data is structured and unstructured data that is so difficult to collect, store, and so on due to the huge amount of data. Many institutions, including universities, are building student convergence systems to foster talents for data science and AI convergence, but there is an absolute lack of research on what kind of education is needed and what kind of education is required for students. Therefore, in this paper, after conducting the correlation analysis based on the questionnaire on basic surveys and courses to improve the curriculum by grasping the satisfaction and demands of the participants in the "2019 Big Data Youth Talent Training Course" held at K University, Regression analysis was performed. As a result of the study, the higher the satisfaction level, the satisfaction with class or job connection, and the self-development, the more positive the evaluation of program efficiency.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.237-238
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• 2023

2022 개정 교육과정은 미래 사회에 대응하기 위한 역량을 함양하는 것에 중점을 두고 있다. 특히 디지털 대전환에 중점을 두고 지능정보기술 활용과 디지털 학습 환경 구축을 강조하고 있다. 경상남도 교육청에서는 미래교육 환경 구축을 위해 빅데이터-AI 플랫폼 아이톡톡을 개발하여 이에 대응하고 있다. 본 연구에서는 2022 개정 교육과정의 교수학습 측면에서 아이톡톡의 활용을 살펴보았다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.191-200
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• 2024

The rapid advancement of computer technology and artificial intelligence has significantly impacted software education in Korea. Consequently, the 2022 revised curriculum demands personalized education. However, implementing personalized education in schools is challenging. This study aims to facilitate personalized education by utilizing incorrect codes and error information submitted by beginners to construct prompts. And the difference in the frequency of correct feedback generated by the generative AI model and the prompts was examined. The results indicated that providing appropriate error information in the prompts yields better performance than relying solely on the excellence of the generative AI model itself. Through this research, we hope to establish a foundation for the realization of personalized education in programming education in Korea.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.587-592
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• 2020

This paper analyzed the curriculum of computer and software-related majors educating the core IT-related skills needed for the 4th Industrial Revolution. The analysis was conducted on 158 majors classified as applied software, computer science and computer engineering according to the standard classification of university education units by the Standard Classification Committee of the Korean Council of University Education. The current status of introduction of curricular divided into the fields of Internet of Things(IoT) & mobile, cloud & big data, artificial intelligence(AI), and information security was analyzed among the contents of education in the relevant departments. According to the analysis, an average of 81.6% of the majors for each group of curricular organized related subjects into the curriculum. The Curriculum Response Index for the 4th industrial revolution(CRI4th) by major, calculated by weighting track operations by education sector, averaged 27.5 point out of 100 point. And the IoT & mobile sector had the highest score of 42.3 points.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1642-1648
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• 2021

We analyzes representative technologies of IoT patents and reflects these results in the curriculum of IoT. In order to identify the representative technologies, the IPC codes of the patents were analyzed. Among the main category IPC codes, the most used IPC codes were H04L in Single IPC Patent with 974 cases(32.0%) and G06Q in Multiple IPC Patent with 710 cases(29.2%). As a result of classifying the IPC code into the WIPO technology classification system, the most emphasized technologies are Digital Communication, accounting for about 60.5% in the Single IPC Patent and IT Methods for Management(710 cases, 29.2%) in Multiple IPC Patent. The main points to be considered when organizing the curriculum of IoT are: ∇Emphasis on Digital Communication, ∇Expansion of Education related to IT Methods for Management(Including entrepreneurship and patent application), and ∇Consideration of subjects related to the Convergence of IoT. This research can contribute to the curriculum design of new industrial technologies such as AI and Fintech.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.31-38
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• 2023

In this paper, a basic machine learning model learning and utilization education curriculum for non-majors is proposed, and an education method using Orange machine learning model learning and analysis tools is proposed. Orange is an open-source machine learning and data visualization tool that can create machine learning models by learning data using visual widgets without complex programming. Orange is a platform that is widely used by non-major undergraduates to expert groups. In this paper, a basic machine learning model learning and utilization education curriculum and weekly practice contents for one semester are proposed. In addition, in order to demonstrate the reality of practice contents for machine learning model learning and utilization, we used the Orange tool to learn machine learning models from categorical data samples and numerical data samples, and utilized the models. Thus, use cases for predicting the outcome of the population were proposed. Finally, the educational satisfaction of this curriculum is surveyed and analyzed for non-majors.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.87-103
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• 2024

The content system table of the subject-matter curriculum is considered important in the Korean national curriculum, textbook writing, and teaching and learning in the classroom. However, studies that comprehensively organize the issues concerning the format of the subject-matter curriculum content system have been scarce. This study scrutinized the evolution of the content system from its inception in The 6th Curriculum to the most recent 2022 Revised National Curriculum, focusing on science curricular. The following issues and suggestions were derived for the format of the subject content system. First, caution should be exercised in using terms such as "domain," "field," and "category," and it should be clarified whether these terms are intended simply for logical differentiation or to serve as a content organizer with a specific emphasis. Second, the nature of components such as "core ideas," which can serve as innovative content organizers, should be strictly defined. Third, while the introduction of three-dimensional content elements such as "knowledge and understanding," "process and skill," and "value and attitude" is viewed positively, it is suggested that a further delineation be made, elaborating how each can be utilized to form core competencies. Fourth, the construction of the subject-specific content system in national curriculum needs caution because whether it will resolve or exacerbate the 'disparity between general curriculum and subject-matter curriculums' is uncertain. Finally, as an apparent pendulum motion of the subject-matter content system is observed in national curriculum documents, efforts should be made to ensure that it does not result in meaningless repetition, but instead achieves meaningful dialectical progress.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• 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.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.227-237
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• 2021

In this thesis, a survey was conducted on elementary school teachers about the establishment of information subjects in elementary schools. As a result, the opinion that information subjects should be newly established for ICT literacy education and SW/AI education in elementary schools was very high. In addition, if it is difficult to establish a new information subject, opinions in favor of the organization of the information subject as an autonomous subject using the discretionary time of the principal were high. In light of the results of this analysis, it is judged that it is necessary to establish a new information subject for ICT literacy education and SW/AI education in the next elementary school curriculum. However, if it is difficult to establish a new information course, it is necessary to come up with a plan that can be operated in the form of autonomous subject for students wishing to learn SW/AI. And it is judged that the number of class hours should be secured for at least 1 hour or 2 hours per week in the 3rd grade and above.