• 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 Korean Association of Information Education
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• v.26 no.1
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• pp.1-10
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• 2022

With the development of artificial intelligence, society is moving toward another world that has never existed before. As a result, interest in artificial intelligence education is also increasing, and research on artificial intelligence education is being conducted more actively in Korea. However, many studies have been conducted focusing on the upper grades of elementary school, and curriculum and programs for the lower grades are still insufficient. Therefore, in this study, a total of 6 sessions of artificial intelligence programs were developed to understand image recognition for the lower grades of elementary school. The validity was secured by conducting expert validity for 8 experts, and the effectiveness was verified through the pre-post-response sample t-test by applying it to the experimental group. As a result, both artificial intelligence understanding and artificial intelligence attitude showed statistically significant results, and both the interest and difficulty of educational programs were found to be suitable for lower grade students. Based on the contents of this study, it is necessary to review its application and effectiveness in various environments through follow-up studies in the future.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.573-584
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• 2020

This study is about the development of AI algorithm education program using cognition modeling to positively improve students' image on AI. First, we analyzed the concept of user-based collaborative filtering and developed the education program using the cognition modeling method. We checked the adequacy of program through the expert validity test. Both CVR values for the content development method of cognitive modeling and the developed program showed validity above .80. We applied the developed program to elementary school students in class. The test was conducted using a semantic discrimination to examine changes in students' perception of artificial intelligence before and after. We were able to confirm that the students' AI images were significant positive change in 12 of the 23 words in the adjective pair.

• Journal of The Korean Association of Information Education
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• v.21 no.5
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• pp.527-535
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• 2017

In this study, we analyzed the image of artificial intelligence recognized by elementary students using semantic differential scale. First, we extracted 23 pairs of image adjectives related to perception of artificial intelligence. Adjectives were classified into three types related to recognition, emotion and ability and 827 elementary students were examined. Image factors were classified into four factors: convenience, technological progress, human-friendliness, and concern. As a result, they showed a clear image that artificial intelligence is clever, new, and complex but exciting. In comparison with variables, female students, coding experience and older students thought that artificial intelligence was more human-friendly and technological progressive.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.23-29
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• 2023

For given the importance of elementary school students developing the ability to solve problems using artificial intelligence (AI), problem-solving abilities should be developed using AI along with education to develop problem-solving abilities. Such students need a form that allows them to understand the concepts and principles of AI and to be easily educated in a fun way to understand basic understanding of how AI works. To this end, this study planned an 8-hour AI convergence program and operated based on self-driving cars, demonstrating that it was effective in improving elementary school students' problem-solving abilities, creativity, and AI understanding. As a result of operating the camp, students' understanding of AI was 3.56 (standard deviation 0.85), 4.00 (standard deviation 0.71), and t-value was -5.412 (p<0.001), indicating statistically improved understanding of AI, and high satisfaction and interest of students. In the future, it will be necessary to develop an educational program that allows elementary school students to devise their own ideas and create products to which AI models can be applied.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.139-149
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• 2017

Artificial intelligence education is very important in the 21st century knowledge information society. Even if it is very important to understand artificial intelligence and practice computer programming in computer education in the fourth industrial revolution, but there is no teaching and learning model to understand artificial intelligence and computer programming education. In this paper, the proposed model consists of problem understanding step, data organizing step, artificial intelligence model setting step, programming step, and report writing step. At the program step, students can choose to copy, transform, create, and challenge steps to their level. In this study, the validity of the model was proved by the Delphi evaluation of elementary school teachers. The results of this study provide a good opportunity for elementary school students to practice artificial intelligence programs.

• Journal of Korean Elementary Science Education
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• v.41 no.3
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• pp.468-479
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• 2022

In this study, we developed an environmental education program for fine dust using artificial intelligence-based tools. We applied this program to elementary school students to investigate its effect on environmental sensitivity and self-efficacy. The study was conducted on 29 sixth-grade elementary school students. The analysis of the pre- and post-tests gave the following results. First, the fine dust environmental education program using artificial intelligence-based tools was effective in improving the environmental sensitivity of elementary school students. Second, it had a positive effect on improving the self-efficacy of elementary school students, and third, it had a positive effect on the elementary school students' perception of the environment. After applying the program, students became more interested in the environment and fine dust. Additionally, they had a sense of environmental protection practice in connection with their daily lives. As such, it is concluded that the fine dust environmental education program using artificial intelligence-based tools had a positive effect on the environmental sensitivity and self-efficacy of elementary school students.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.51-57
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• 2021

Quite a few elementary school teachers began to utilize AI technology in order to provide students with customized, intelligent information services in recent years. However, learning principles of AI may be as important as utilizing AI in everyday life because understanding principles of AI can empower them to buildup adaptability to changes in highly technological world. In the paper, 'Linear Regression Algorithm' is selected for teaching AI-based prediction system to solve real world problems suitable for elementary students. A simulation program written in Scratch was developed so that students can find a solution of linear regression model using the program. The paper shows that students have learned analyzing data as well as comparing the accuracy of the prediction model. Also, they have shown the ability to solve real world problems by finding suitable prediction models.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.723-731
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• 2021

In this study, the AI education program for elementary school students was developed and applied by introducing the design thinking process, which is attracting attention as a creative problem solving process. A design thinking-based AI education program was developed in the stages of Understanding AI, Identifying sympathetic problems, Problem definition, Ideate, Prototype, Test and sharing, and the development program was applied to elementary school students in 4th-6th grade. As a result of pre- and post-testing of students' computational thinking skills to confirm the effectiveness of the program, computational thinking skills increased by grade level, and students experienced a process of collaboration for creative problem solving based on insights gained from sympathetic problem finding. In addition, it was possible to get a glimpse of the attitude of using AI technology to solve problems, and it was confirmed that ideas were generated in the prototype stage and developed through communication between team members. Through this, the design thinking-based AI education program as one of the AI education for elementary school students guarantees the continuity of learning and confirms the possibility of providing an experience of the creative problem-solving process.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.449-455
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• 2022

The digital culture area is a field of artificial intelligence education and partially overlaps with information ethics, and this study proposed an elementary school-centered digital culture curriculum, a detailed area of artificial intelligence education. First, as a leading overseas case in the field of digital culture, we analyzed the secure online interaction, which is the core content of the K12CS framework in the United States and the UK's computing curriculum. We presented by categorizing it into four digital areas: content, communication method, copyright, and job exploration in accordance with the domestic educational environment and field conditions. In addition, educational goals were stated according to the level of kindergarten and elementary school, and the validity of a group of field teachers majoring in in information and artificial intelligence was investigated to confirm the validity. As a result of the analysis, it was found that all the contents set were suitable except for some of the detailed goals of the first grade elementary school stages. Accordingly, a digital culture curriculum for artificial intelligence education was presented by revising and supplementing the detailed goals of the first graders.