• Journal of Convergence for Information Technology
• /
• v.11 no.12
• /
• pp.168-175
• /
• 2021

In this study, a transdisciplinary convergence education program was developed to enhance the understanding for classification of reptiles and amphibians in biology education and also to increase AI (Artificial Intelligence) capability by using artificial intelligence education. The main content is to solve the classification of reptiles and amphibians that has been dealt with for a long time in biology education, using a decision tree and ML4K (Machine Learnig for Kids), it was designed for a total of 3 lessons. Experts review was conducted on the developed education program, as a result, the I-CVI(Item Content Validity Index) value was .88~1.00 so that can secure content validity. This education program has the advantage of being able to simultaneously learn about the learning contents of artificial intelligence in informatics and the classification of vertebrates in the biological education. In addition, since it is configured to minimize the cognitive load in the AI using part, it is characterized by the fact that all of any teachers can apply it their lesson easily.

• Journal of The Korean Association of Information Education
• /
• v.25 no.2
• /
• pp.405-412
• /
• 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.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.1039-1040
• /
• 2023

본 논문에서는 무형 유산 DX 플랫폼의 AR(Augmented Reality) 기술과 ChatGPT 를 결합하여 전문가들의 지식을 보존하고 효과적으로 전달하는 시스템을 제안한다. 특히, 고령화 사회에서 은퇴한 전문가들의 지식이 소실될 위험을 방지하며, 사용자들의 교육 경험을 향상시키는 방법을 모색한다.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.67-78
• /
• 2024

Amidst the onset of the Fourth Industrial Revolution and the prominence of artificial intelligence, societal structures are undergoing significant changes. There is a heightened global interest in AI education for nurturing future talents. Consequently, this research aims to develop an AI-integrated Korean language curriculum for first-year high school students, utilizing the ADDIE model for instructional program development. To assess the program's effectiveness, pre-post assessments were conducted on future core competencies (Collaboration, Communication, Critical Thinking, Creativity) and knowledge information processing skills. The curriculum, spanning nine sessions and incorporating four small projects, sought to provide students with a new experience of AI-integrated Korean language education. As a result, students who participated in the program demonstrated improvement in future core competencies across all areas, and positive outcomes were observed in satisfaction levels and qualitative analysis. Through these findings, it is suggested that this program successfully integrates artificial intelligence into high school Korean language education, potentially contributing to the cultivation of future talents among students.

• Journal of Convergence for Information Technology
• /
• v.12 no.2
• /
• pp.157-162
• /
• 2022

In a society full of knowledge and information, digital literacy and artificial intelligence (AI) education that can utilize AI technology is needed to solve numerous everyday problems based on computational thinking. In this study, data-centered AI education was conducted while teaching computer programming to non-computer programming students at universities, and the correlation between major factors related to academic performance was analyzed in addition to student satisfaction surveys. The results indicated that there was a strong correlation between grades and problem-solving ability-based tasks, and learning satisfaction. Multiple regression analysis also showed a significant effect on grades (F=225.859, p<0.001), and student satisfaction was high. The non-computer programming students were also able to understand the importance of data and the concept of AI models, focusing on specific examples of project types, and confirmed that they could use AI smoothly in their fields of interest. If further cases of AI education are explored and students' AI education is activated, it will be possible to suggest its direction that can collaborate with experts through interest in AI technology.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.8
• /
• pp.13-21
• /
• 2021

In this paper, we developed an artificial intelligence literacy education program to strengthen the AI convergence education capacity and cultivate literacy of in-service elementary and secondary teachers, and verify the effect on the degree of interest in artificial intelligence convergence education by applying it. As a test tool, the level of interest questionnaire scale developed by George, Hall & Stiegelbauer(2006) was used based on the center of interest acceptance model of Hall et al.(1979). As a result of analyzing the degree of interest in artificial intelligence convergence education before and after the application of the artificial intelligence literacy education program, the types of non-users were found both before and after the application of the program, but the overall degree of interest increased compared to before application. As a result of analyzing the satisfaction result of the artificial intelligence literacy education program, a response that was satisfied in most areas was derived, but there was a tendency to be somewhat less satisfied with the case of convergence and application of artificial intelligence and industry.

• Journal of Convergence for Information Technology
• /
• v.12 no.5
• /
• pp.139-149
• /
• 2022

The purpose of this study is to develop and analyze the effects of an educational program that can cultivate artificial intelligence(AI) convergence education competency for future education and enhance students' understanding of pre-service teachers. For this end, an AI convergence education program using Machine Learning for Kids and Scratch 3 was developed for 15 weeks under the theme of classifying the state of matter. The developed program were treated by K University pre-service teachers who participated voluntarily. As a result, pre-service teachers were able to metaphorically understand the learning process of students through understanding of machine learning training process. In addition, the pre-post t-test result of AI teaching efficacy showed a statistically significant improvement with t=-7.137 (p<.000). Therefore, it is suggested that the AI convergence education program developed in this study can help to increase the understanding of the pre-service teacher's students in an indirect way other than practice teaching, and can contribute to foster AI education competency.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.113-121
• /
• 2021

This study was intended to present an online survey and analysis of the survey results after the operation of the AI education leading school initiation workshop consulting training and the creative convergence type information education room consulting training. Through this, it was confirmed that there is a perception that support such as AI education leading school consulting training is necessary, and the network should be activated to share best practices and an efficient and flexible operating system in terms of operation of leading schools nationwide. could In addition, while the subjects of the survey recognized the importance of AI education-related competency, it was identified that they had low awareness of their AI education-related competency, and recognized the need for various support for systematic and customized AI education-related competency reinforcement.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.197-209
• /
• 2024

This study aimed to analyze recent research trends in Artificial Intelligence (AI) education within South Korea with the overarching objective of exploring the future direction of AI education. For this purpose, an analysis of 697 papers related to AI education published in Research Information Sharing Service (RISS) from 2016 to November 2023 were analyzed using word cloud and Latent Dirichlet Allocation (LDA) topic modeling technique. As a result of the analysis, six major topics were identified: generative AI utilization education, AI ethics education, AI convergence education, teacher perceptions and roles in AI utilization, AI literacy development in university education, and AI-based education and research directions. Based on these findings, I proposed several suggestions, (1) including expanding the use of generative AI in various subjects, (2) establishing ethical guidelines for AI use, (3) evaluating the long-term impact of AI education, (4) enhancing teachers' ability to use AI in higher education, (5) diversifying the curriculum of AI education in universities, (6) analyzing the trend of AI research, and developing an educational platform.

• Journal of the Korean Chemical Society
• /
• v.68 no.3
• /
• pp.160-175
• /
• 2024

The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.