• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.187-195
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• 2023

This study propose to develop artificial intelligence liberal arts courses for college students in the humanities and social sciences majors using the entry artificial intelligence model. A group of experts in computer, artificial intelligence, and pedagogy was formed, and the final artificial intelligence liberal arts course was developed using previous research analysis and Delphi techniques. As a result of the study, the educational topics were largely composed of four categories: image classification, image recognition, text classification, and sound classification. The training consisted of 1) Understanding the principles of artificial intelligence, 2) Practice using the entry artificial intelligence model, 3) Identifying the Ethical Impact, and 4) Based on learned, team idea meeting to solve real-life problems. Through this course, understanding the principles of the core technology of artificial intelligence can be directly implemented through the entry artificial intelligence model, and furthermore, based on the experience of solving various real-life problems with artificial intelligence, and it can be expected to contribute positively to understanding technology, exploring the ethics needed in the artificial intelligence era.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.13-23
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• 2021

This study requires SW education that can adapt to the advent of the fourth industrial revolution and the new normal environment of COVID-19 pandemic. Small and powerful smartphones, which have become a necessity in digital society, are designed and applied to create apps with useful apps or artificial intelligence modules that have been trained with data using the App Inventor program as a good teaching tool. After conducting the class in a blended method that combines face-to-face and non-face methods, the survey questioned the technical and cognitive maturity of artificial intelligence and the pros and cons of blended software classes. We also found changes in career orientation, which is intended to explore SW-related talent occupations that require a lot of demand in terms of national development before and after artificial intelligence classes. Significant results were reached in three of the sub-elements. Even in non-face-to-face situations, it is expected that an app vendor software education program using artificial intelligence will be provided to the actual site.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.97-104
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• 2018

The purpose of this study was to investigate the expectation toward medical artificial intelligence(AI) of students in majoring health, and to utilize it as a basic data for widespread use of medical AI for 500 students majoring in health science at Cheonan city. The awareness of AI was 18.6%, the reliability of AI was 24.8%, and agreement to use of medical AI was 38%. Also, the higher the awareness and reliability of AI were, the higher the expectation of AI was. As a result, education on medical AI in the major field should be a cornerstone for the development of an effective healthcare environment utilizing medical AI by raising awareness, reliability and expectation of AI.

• The Journal of Korean Association of Computer Education
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• v.23 no.4
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• pp.1-11
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• 2020

The purpose of this study is to propose the direction of AI education in K-12 education through investigating and analyzing aspects of the purpose, content, and methods of AI education as the curriculum and teacher training factors. We collected and analyzed 9 papers as the primary literature and 11 domestic and foreign policy reports as the secondary literature. The collected literatures were analyzed by applying a descriptive reviews, and the implications were derived by analyzing the curriculum components and TPACK elements for multi-dimensional analysis. As a result of this study, AI education targets were divided into three steps: AI users, utilizer, and developers. In K-12 education, the user and utilizer stages are appropriate, and artificial intelligence literacy must be included for user education. Based on the current computing thinking ability and coding ability for utilizer education, the implication was derived that it is necessary to target the ability to create creative output by applying the functions of artificial intelligence. In addition to the pedagogical knowledge and the ability to use the platform, The teacher training is necessary because teachers need content knowledge such as problem-solving, reasoning, learning, perception, and some applied mathematics, cognitive / psychological / ethical of AI.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.168-175
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• 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
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• v.23 no.6
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• pp.675-687
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• 2019

As interest in artificial intelligence increases, each university has been establishing a special graduate school with artificial intelligence major, and recently, the Korea government has established various support policies for artificial intelligence education. However, each university has a lot of difficulties because it has little experience in operating graduate education with the latest field of artificial intelligence and it is not easy to find experts. In this study, the response of graduate school students majoring in artificial intelligence was analyzed using IPA technique, and the direction of education of graduate school artificial intelligence major was searched. Among the 40 items surveyed by IPA, 12 items such as systematization of artificial intelligence curriculum, progress of class considering learning level, improvement of academic relations with guidance professors were extracted as items to be improved first. On the other hand, 8 items such as assistant capacity, and relationship with colleagues were overloaded, and twelve items such as instructor's lecture competency, appropriateness of educational contents, learner's artificial intelligence skills and knowledge, and attitude acquisition were to be maintained. In addition, eight items such as convergence education curriculum and diversity of education methods were all low in importance and performance. It is suggested that AI graduate school should be divided into two tracks(technical specialization, convergence expansion) by educational goal, and each track should be conducted by level-specific educational contents and methods suitable for student level. The curriculum should be elaborate and systematic to acquire AI knowledge, skills, and attitudes, and should have an individualized guidance system centered on excellent faculty members.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.69-76
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• 2022

In this paper, we presented the contents and methods of AI classes using AI platforms. First, we extracted the content elements of each stage of the AI class using the AI education platform from experts. Classes using the AI education platform were divided into 5 stages and 25 class elements were selected. We also conducted a survey of 82 teachers and analyzed the factors that they acted importantly at each stage of the AI platform class. As a result of the analysis, teachers regarded the following contents as important factors for each stage that are AI model preparation stage (the learning stage of the AI model), problem recognition stage (identification of problems and AI solution potential), data processing stage (understanding the types of data), AI modelingstage (AI value and ethics), and problem solvingstage (AI utilization in real life).

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.887-890
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• 2021

최근 AI 를 활용한 의료 진단 솔루션 시장이 크게 성장함에 따라 의료 인공지능 기술에 대한 대학 교육에 대한 수요가 증가하고 있지만, 개인정보 유출의 위험성 등으로 인하여 의료 데이터를 대학 교육에 활용하기 어려운 실정이다. 본 논문에서는 실제 의료 데이터 대신 생성적 적대 신경망(GAN)으로 합성된 흉부 X-ray 영상을 활용한 의료 인공지능 교육 모델의 사례를 제시한다. 프로메디우스(주)에 의해 제공받은 흉부 X-ray 합성영상을 사용하여, VGG-16 모델을 훈련하고 성능을 검증 및 평가하며 미세조정을 통해 성능을 개선하는 교육 모델을 구성하였다. 또한 교육모델이 의료 인공지능에 대한 학생들의 이해력 향상에 기여한 효과를 정량적으로 평가하였다.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.277-297
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• 2023

In mathematics, the concept of convolution is widely used. The convolution operation is required for understanding computer vision and deep learning in artificial intelligence. Therefore, it is vital for this concept to be explained in college mathematics education. In this paper, we present our new teaching and learning materials on convolution available for engineering mathematics. We provide the knowledge and applications on convolution with Python-based code, and introduce Convolutional Neural Network (CNN) used for image classification as an example. These materials can be utilized in class for the teaching of convolution and help students have a good understanding of the related knowledge in artificial intelligence.

• Communications of Mathematical Education
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• v.35 no.4
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• pp.445-473
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• 2021

The purpose of this study is to derive implications for the design of the next curriculum by analyzing the textbooks designed as a new subject in the 2015 revised curriculum. In the mathematics curriculum documents of , 'related learning elements' are presented instead of 'learning elements'. 'Related learning elements' are defined as mathematical concepts or principles that can be used in the context of artificial intelligence, but there are no specific restrictions on the amount and scope of dealing with 'related learning elements'. Accordingly, the aspects of 'related learning elements' reflected in the textbooks were analyzed focusing on the textbook format, the amount and scope of contents, and the ways of using technological tools. There were differences in the format of describing 'related learning elements' in the textbook by textbook and the amount and scope of handling mathematics concepts. Although similar technological tools were dealt with in each textbook so that 'related learning elements' could be used in the context of artificial intelligence, the focus was on computations and interpretation of results. In order to fully reflect the intention of the curriculum in textbooks, a systematic discussion on 'related learning elements' will be necessary. Additionally, in order for students to experience the use of mathematics in artificial intelligence, substantialized activities that can set and solve problems using technological tools should be included in textbooks.