• Research in Mathematical Education
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• v.27 no.1
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• pp.49-73
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• 2024

This study aims to explore the direction of high school statistics education in Korea through a comparative analysis between the revised 2022 Korea mathematics curriculum and the IBDP Mathematics: Application & Interpretation Standard Level (IBDP AI SL) Curriculum and textbooks. The study seeks to investigate the Statistics unit of the two curricula, compare chapter structures and content elements of textbooks, and explore exercises on modeling and utilization of technology tools. The results are as follows: First, the IBDP AI SL statistics covered a broader range of topics. Second, exercises in Korean high school textbooks typically inquire about one or two questions in each topic, whereas the IBDP AI SL textbook's exercises present a real-life scenario on all relevant topics through sub-questions. Third, the Korean textbook guides the utilization of technology tools only in exercises presented after completing the entire chapter or where the calculation is complex. Also, there were only a handful of modeling exercises in the Korean textbook in contrast to most of the lessons and exercises were modeling exercises in the IBDP AI SL textbook. If these findings can be integrated into teaching practices in Korea, it will provide a direction for statistics education in Korean high schools.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.717-718
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• 2022

본 연구에서는 예비교사의 인공지능 융합교육 역량 강화를 위한 캡스톤 디자인 기법 활용 인공지능 융합교육 프로그램을 개발하고 효과를 검증하였다. 개발된 교육 프로그램은 예비교사들이 스크래치 프로그래밍과 머신러닝포키즈, 캡스톤 디자인의 이해를 바탕으로, 인공지능 활용 융합 수업을 위한 주제 선정, 수업 설계 및 개발 후, 마이크로티칭을 하고 동료 평가 및 피드백을 하도록 조직되었다. 이는 2022년 1학기 K대학의 교양 강좌를 수강하는 예비교사들에게 처치되었다. 그 결과, 실험 대상자들의 인공지능 교수효능감의 사전-사후 t-검정에서 통계적으로 유의한 효과가 있음을 확인되었다.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.269-274
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• 2021

With the development of artificial intelligence, society is moving to a different world. As a result, amid growing interest in artificial intelligence education, research on how to teach artificial intelligence is also being conducted more actively in Korea. However, a lot of research is being conducted around the upper grades of elementary school, and curriculum and programs for the lower grades are insufficient. Therefore, this study developed an artificial intelligence program for lower grades. Among them, it was developed focusing on artificial intelligence image recognition. It compares image recognition methods of people, animals, and computers, identifies the characteristics of fallen leaves, and helps them understand the image recognition process of artificial intelligence by classifying them according to the characteristics of fallen leaves. I hope this program will help elementary school students understand the image recognition principle of artificial intelligence in the future.

• The Mathematical Education
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• v.63 no.2
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• pp.209-231
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• 2024

The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).

• Journal of Korean Elementary Science Education
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• v.42 no.3
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• pp.467-479
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• 2023

For the successful implementation of education using artificial intelligence (AI) in schools, the perception of teachers is important. This study focuses on elementary school teachers and their perception of the need and teaching efficacy of science classes using AI before and after participating in a research school program. The analysis explores four key aspects, namely, learning, teaching, assessment, and communication. The study recruited 24 elementary school teachers from a school designated by the Gangwon Provincial Office of Education to participate in a year-long research school program. The study collected data using pre- and post-program surveys to explore changes in the perception of teachers regarding AI-based science classes. Furthermore, the researchers conducted individual in-depth interviews with four elementary school teachers to investigate the experience factors that influenced the changes in their perception of the aforementioned classes. The main findings were as follows. First, elementary school teachers were positively aware of the need for science classes using AI even prior to their research school experience; this perception remained positive after the research school program. Second, the science teaching efficacy of the elementary school teachers using AI was generally moderate. Even after the research school experience, the study found no statistically significant increase in efficacy in teaching science using AI. Third, by analyzing the necessity-efficacy as quadrants, the study observed that approximately half of the teachers who participated in the research school reported positive changes in learning, teaching, and assessment. Fourth, the study extracted four important experience factors that influenced the perception of the teachers of science classes using AI, namely, personal background and characteristics, personal class practice experience, teacher community activities, and administration and work of school. Furthermore, the study discussed the implications of these results in terms of the operation of research schools and science education using AI in elementary schools.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.301-304
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• 2021

In this study, we developed a module that can perform two functions at the same time through interworking between a personal recognition module and a heat detection module in the era of COVID-19. This can simultaneously solve the problem of compatibility of the personal recognition module that occurs in the existing system and the problem of secondary infection that can occur during congestion due to the separate implementation of heat detection. Therefore, in this study, NFC and Bluetooth motherboards were developed, and an array-type non-contact temperature sensor was applied to detect heat. The developed system is expected to be able to realize both access control of floating population and effective quarantine at the same time in public institutions or private companies that require AI automated access control. In addition, it is judged that it is possible to link the embedded programming and web programming implementation method using the module of the development system to the educational program.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.203-210
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• 2021

This study was conducted to develop a convergence education program using smart farms with both input data(temperature, humidity, etc.) and output data(vegetables, fruits, etc.) that are easily accessible in everyday life so that elementary school students can intuitively and easily understand the principles of artificial intelligence(AI) learning. In order to develop this program, we conducted a prior study analysis of a horticulture, software, robot units in the 2015 Practical Arts curriculum and artificial intelligence education. Based on this, 13 components and 16 achievement criteria were selected, and AI programs of 4 sessions(a total of 8 hours). This program can be used as a reference when developing various teaching materials for artificial intelligence education in the future.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.37-44
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• 2021

This study is to design and to develop the educational contents to enhance artificial intelligence literacy. First, we designed artificial intelligence education contents and constructed education programs. The contents are composed of a total of 15 lectures in 8 AI domains. The contents contain the elements of knowledge-skill-attitude, and 5 learning steps. The developed contents were organized in the form of online materials and included simulations and worksheets to directly manipulate and explore the concepts and algorithms of AI. In addition, we provided evaluation questions for each content. To examine the suitability of content, we conducted a validity test for experts. As a result of the content validity test, the overall average was .71 or higher, and the CVI value of the class suitability was .82, indicating a high validity. We are expected to use the contents developed in this study as an effective program to improve AI literacy in university liberal arts education.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.530-532
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• 2021

This paper deals with AI education service that enables developers who have completed basic programming education to program in C/C++ language in order to learn big data and artificial intelligence. In addition, a customized development environment configuration system according to the development environment and how the user implements and tests artificial intelligence are explained. And also it has a function to check the effect on artificial intelligence through manipulation of various internal parameters. It is expected that it will be possible to develop artificial intelligence education services without language restrictions through networks in the future.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.443-451
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• 2020

In elementary school software education, a programming process is experienced through a simple problem solving process. And even this experience emphasizes that the problem-solving process is a CS Unplugged activity. However, CS Unplugged has a disadvantage in that it only learns the principles of computing, and the learner cannot experience real problem solving. In this study, a learning program using artificial intelligence robots was developed with the goal of cultivating the ability to solve problems encountered in the real life of elementary school students. Students could solve complex problems in real life from the point of view of artificial intelligence through the developed program, and increase their interest and understanding of artificial intelligence education through robot control.