• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.1-13
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• 2020

With the advent of an intelligent information society, research toward artificial intelligence education was conducted. In previous studies, the subject of research is biased, and studies that analyze attitudes toward artificial intelligence are insufficient. So, in this study developed a test tool to measure the artificial intelligence of high school students and analyze their attitudes toward artificial intelligence. To develop the test tool, 229 high school students completed a preliminary test, of which the results were analyzed via exploratory factor analysis. To analyze the students' attitudes toward artificial intelligence, the resulting test tool was applied to 481 high school students, and their test results were analyzed according to factors. From the study's results, there was no difference according to gender in the students' attitudes toward artificial intelligence, but there was a significant difference per grade. In addition, there was a significant difference in attitudes according to artificial intelligence-related experiences: the high school students who had direct and indirect experience with artificial intelligence, programming, and more frequently used it had more positive attitudes toward artificial intelligence than students without this experience. However, artificial intelligence education experience negatively influenced the students' attitudes toward artificial intelligence. Overall, the higher their interest in artificial intelligence, the more positive the high school students' attitudes toward artificial intelligence.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.695-702
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• 2023

The purpose of this study is to develop an early childhood artificial intelligence education programs in kindergartens. In order to achieve the purpose of the study, a four-step program development procedure was taken: documentary analysis, program design and development, execution, and assessment. This study presented the purpose and goals, educational content, teaching-learning methods, and evaluation of the early childhood artificial intelligence education program in kindergarten. By implementing an artificial intelligence education in the process of developing the program, the practicality and utilization of the program were secured. This study is meaningful in that it derives practical support measures to apply and activate artificial intelligence education programs in the field of early childhood education.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.961-972
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• 2021

In this study, an educational program was developed so that artificial intelligence could be used as a transdisciplinary convergence education with other disciplines. The main educational content is designed for 8 hours using machine learning to help students understand the molecular structure dealt with in high school chemistry. The program developed in this study calculated the I-CVI (Item Content Validity Index) value through expert review, and as a result, none of the items were rejected with a score of .80 or higher. Because the program of this study combines the content elements of the chemistry subject and the information (artificial intelligence) subject academically, it is expected that the learner will be able to increase the convergence talent literacy. In addition, since it is not required to secure a additional number of hours for this educational program, the burden on teachers may be low.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.397-406
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• 2022

In this study, We confirmed the three major policy directions presented in "Educational Policy Direction and Core Tasks in the Age of Artificial Intelligence" announced by the government in 2020, and analyzed how the direction and key tasks are reflected in the policy from keywords selected from government policy data related to artificial intelligence education published between '20 and '22. It was extracted and analyzed how the direction and key tasks are reflected in the policy. As a result of text mining and the topic analysis, the direction of education set was analyzed and various types of activities for nurturing talents in the field of artificial intelligence were confirmed. Ultimately, the government's policy direction is to apply the '25 revised curriculum in earnest, while advancing and activating the AI education policy and allowing it to settle naturally in the field. It could be predicted that related policies and tasks would appear more and more.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.49-53
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• 2004

최근 로봇의 형태는 인간의 명령을 이행하고 스스로 학습하며, 감정을 지닐 수 있는 인공지능을 내장한 로봇이다 이와 같은 특징을 지닌 로봇의 용도는 조립, 도장, 용접 둥 단순 반복 작업이나 위험한 산업현장에서 벗어나 좀더 다양한 분야로 그 범위가 확대되고 있다. 활용의 예는 '가족 도우미'의 역할을 수행하는 로봇으로써 가사, 방범, 오락 그리고 교육 등의 기능을 담당하는 형태로써 보다 다양화되고 향후 가정의 필수품으로 자리 잡을 전망이다. 이러한 로봇의 구현에 인공지능의 요소를 활용해야 하는 것은 당연하며 그 범위 또한 광범위하다. 로봇이 여러 가지의 기능을 수행하기 위해서는 환경 정보를 받아들이는 센서의 역할이 크며 이런 센서를 사용조건에 맞게 활용하는 것도 중요하다. 본 논문에서는 로봇에 부착된 센서의 환경 정보값을 적절히 활용하여 로봇의 다양한 기능을 구현할 수 있는 가정용 지능형 서비스 로봇을 구현하고자 한다. 센서 정보는 지능 기법으로 널러 알려진 소프트 컴퓨팅 기법을 사용한다.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.947-960
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• 2021

In this study, we examine the AI ethics perception of university students to explore the direction of AI ethics education. For this, 83 students wrote their thoughts about 5 discussion topics on online bulletin board. We analyzed it using language networks, one of the text mining techniques. As a result, 62.5% of students spoke the future of the AI society positively. Second, if there is a self-driving car accident, 39.2% of students thought it is the vehicle owner's responsibility at the current level of autonomous driving. Third, invasion of privacy, abuse of technology, and unbalanced information acquisition were cited as dysfunctions of the development of AI. It was mentioned that ethical education for both AI users and developers is required as a way to minimize malfunctions, and institutional preparations should be carried out in parallel. Fourth, only 19.2% of students showed a positive opinion about a society where face recognition technology is universal. Finally, there was a common opinion that when collecting data including personal information, only the part with the consent should be used. Regarding the use of AI without moral standards, they emphasized the ethical literacy of both users and developers. This study is meaningful in that it provides information necessary to design the contents of artificial intelligence ethics education in liberal arts education.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.639-653
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• 2019

The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.231-263
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• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.1-2
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• 2022

본 논문은 4차 산업혁명의 핵심기술인 인공지능과 IoT를 피지컬 컴퓨팅을 이용해 교육을 할 수 있는 플랫폼을 설계하였다. 플랫폼은 파이썬 비주얼 블록 프로그래밍을 기반으로 사용자의 코딩 언어의 구문적인 어려움을 감소시키며 데이터 분석과 머신러닝을 쉽게 응용할 수 있다. 피지컬 컴퓨팅을 위한 AIoT 타겟 보드로는 라즈베리파이를 활용하였으며 타겟보드의 하드웨어에 대한 선수 지식을 최소화해서 원하는 시스템을 개발할 수 있다. 응용에서는 센서로 수집한 데이터를 분석하고 인공지능 모델 생성을 할 수 있으며 학습된 모델을 액추에이터 제어에 활용하는 등 AIoT 피지컬 컴퓨팅 교육에 여러 장벽을 낮추었다.