• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.353-360
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• 2022

The purpose of this study is to verify the effect of artificial intelligence storytelling education program designed to help learning artificial intelligence based on storytelling, the most important element of human intelligence, on learning flow. To this end, a 16-hour artificial intelligence education program was designed and developed, and applied over 8 weeks to 19 gifted students in 5th and 6th grades of elementary school. Artificial intelligence storytelling education program was developed in the form of teaching and learning course plans for each class and storybooks. Artificial intelligence storytelling education program application results showed significant improvements in average scores in all 9 sub-factors of learning flow, including combination of challenges and abilities, integration of behavior and consciousness, clear goal, concrete feedback, focus on task, sense of control, loss of self-consciousness, Distortion of the sense of time, and self-purpose experience. In other words, it was confirmed that artificial intelligence storytelling education program was effective in improving learning flow.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.449-457
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• 2021

Ministry of education recently announced to implement AI curriculum in elementary, middle school and highschool from 2025 which will include programing, basic AI principal and AI Ethics, and the media is releasing articles that have reservations on it. This study is focused on analyzing the perspective of elementary teachers - who are going to be in charge of AI education - on the implementation of AI education in elementary schools and the teachers are divided into two groups of 'software-experienced' and 'software-inexperienced' in relation to software training background. The results showed that 100% of the 'software-experienced' teachers agreed on implementing AI education and 80% of 'software-inexperienced' teachers also showed positive perspective on it. Among the reasons that 20% of 'software-inexperienced' teachers had negative perspective on AI education, it was highly rated that existing home economics subject covers fulfilling amount of software education. Both 'software-experienced' and 'software-inexperienced' teachers chose grade 5 and 6 as the most appropriate age for software education and considered one class per a week as the most appropriate amount of AI class. In terms of the subject format, 75% of the 'software-experienced' teachers chose the idea that software education has to be an independent school subject which will include AI education. Also, 54% of the 'software-inexperienced' teachers chose the ideas either AI education should be an independent subject or software education should be an independent subject which will include AI education. The preference of the content of AI education appeared in order of basic AI programing, principles of AI and AI Ethics.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.63-66
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• 2022

본 논문에서는 분자의 특성을 정확하게 예측하기 위해 효과적인 사전학습(pretraining) 전략과 트랜스포머(Transformer) 모델을 활용한 방법을 제시한다. 딥러닝을 활용한 분자의 성능을 예측하는 연구는 그동안 레이블이 부족한 분자데이터의 특성에 의해 학습 때 사용된 데이터이외의 분자데이터에 대해 일반화 능력이 떨어지는 어려움을 겪었다. 이 논문에서 제시한 모델은 사전학습(pretraining)을 수행할 때 자기지도학습(self-supervised training)을 사용하여 부족한 레이블에 의한 문제점을 피할 수 있다. 대규모 분자 데이터셋으로부터 학습된 이 모델은 4가지 다운스트림 데이터셋에 대해 모두 우수한 성능을 보여주어 일반화 성능이 뛰어나며 효과적인 분자표현을 얻을 수 있음을 보인다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.693-696
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• 2021

There are various algorithms in reinforcement learning, and the algorithm used differs depending on the field. Even in games, specific algorithms are used when developing AI (artificial intelligence) using reinforcement learning. Different algorithms have different learning methods, so artificial intelligence is created differently. Therefore, the developer has to choose the appropriate algorithm to implement the AI for the purpose. To do that, the developer needs to know the algorithm's learning method and which algorithms are effective for which AI. Therefore, this paper compares the learning methods of three algorithms, SAC, PPO, and POCA, which are algorithms used to implement game AI. These algorithms are practical to apply to which types of AI implementations.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.253-261
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• 2022

In this study, the educational effect were sought to be identified after developing and applying project learning for the artificial intelligence based liberal arts education for the non-computer majors. A paired-sample t-test was performed within each group to determine the extent of improvement in the learning flow and artificial intelligence efficacy in the experimental and control groups. After class, an independent sample t-test was performed to examine the statistical effects of pre-test and post-test on the learning flow and artificial intelligence efficacy in the experimental and control groups. The experimental group and control group demonstrated significant improvements in the learning flow and artificial intelligence efficacy before and after class, each respectively. There was no statistically significant difference in the learning flow between the experimental group for which the project learning method was applied and the control group for which only theory and practice were conducted in the artificial intelligence class. It was also confirmed that the experimental group for which the project learning method was applied improved the efficacy of artificial intelligence to a significant level compared to the control group which only proceeded with theory and practice.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.407-416
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• 2022

Although environmental education has been more important due to global extreme weather and natural desasters, environmental topics are covered by several other subjects because it is not an independent subject in elementary school and they need to distribute more class hours to cover proper amount of environmental content. This study is performed to develop method to integrate environmental education and software education in elementary school. This method helps students to learn topics about recycling by using Artificial Intelligence programming and Artificial Intelligence also helps students to practice recycling in virtual reality. A new teaching and learning module(Problem Recognition→Machine Learning↔Use of AI→Collaboration) is adopted for the learning procedure and more than 80 % of the students replied positively to the survey about the interest on integrated learning, understanding of environmental education, understanding of Artificial Intelligence, further learning on Artificial Intelligence programming.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.637-639
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• 2021

인공지능 기반의 생활폐기물의 인식 및 선별에서, 선별 정확도의 저하는 인식 대상의 형태적 다양성과 학습데이터 부족 및 불균등성에 기인한다. 본 연구에서는 비전 인공지능 기반의 효과적인 폐기물 선별을 위한 인식 시스템 및 감독학습 기반의 인공지능 학습 기법을 제안한다. 생활폐기물 중 순환자원적 가치가 높은 CAN, PET, 그리고 이와 형상적으로 유사한 폐기물에 대해 본 연구에서 제안된 시스템에서 물체원형 및 훼손된 형태의 총 18 종 이미지 데이터를 대상으로, 감독학습기반의 인공지능 모델 제작에서 최적의 데이터 레이블링을 위한 분류체계를 제시한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.99-107
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• 1999

인공지능(Artificial Intelligence : AI)이란 인간이 가지고 있는 지각, 인식, 이해, 기억, 판단, 학습, 사고, 발견, 창조 등과 같은 지적인 능력을 기계에 실현하고자 하는 분야이다. 즉 기계에 인간이 가진 지능을 복제하여 우리 인간이 소유하고 있는 추론과 학습 메커니즘 등을 이용하여 신속한 계산을 수행할 수 있도록 컴퓨터의 실제 능력을 향상시키는 것이다. 인공지능 분야는 다양한 분야에 응용되어 왔으며 수많은 기술들이 개발되었다. 석유 분야도 예외는 아니며 석유 지질, 탐사, 매장량 평가, 시추, 생산, 수송, 정제 등 다양한 분야에 걸쳐서 인공지능 분야가 활용되어 많은 문제 해결에 적용되고 있다. 이와 같은 취지에서 본 논문에서는 우선 석유 분야별로 활용되고 있는 인공 지능 분야들을 정리하고 그 후 인공지능 분야별로 실제 해결하고 있는 석유 분야의 문제들을 다시 한번 정리하였다. 그 후 특히 석유 분야가 있어서 실제 개발되어 사용중인 전문가 시스템들을 정리하였다. 마지막으로 향후 석유 분야의 전문가 시스템 발전 방향을 간략히 분석하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.99-100
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• 2022

본 논문에서는 유방암 초음파 이미지를 학습한 multi-modal 구조를 이용하여 유방암을 판별하는 인공지능을 제안한다. 학습된 인공지능은 유방암을 판별과 동시에, 설명 가능한 인공지능 기법과 ROI를 함께 사용하여 종양의 위치를 나타내준다. 시각적으로 판단 근거를 제시하기 때문에 인공지능의 판단 신뢰도는 더 높아진다.