• 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.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.199-204
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• 2021

Along with the development of technology in the fourth industrial revolution, the fields that can apply artificial intelligence technology are rapidly increasing. In order to improve computational thinking, overseas countries such as the U.S. and the U.K. are already using various AI education platforms to provide artificial intelligence education. Therefore, there is an increasing need for elementary school pre-service teachers in Korea to strengthen their AI education capabilities along with the existing software education. However, it may be difficult for learners with low levels of programming experience and AI education experience to choose an AI education platform that can sustain their learning motivation. Therefore, in this study, the factors related to learning motivation in the AI education platform were explored using the ARCS model. Through this, we present the factors required by the AI education platform for motivation and sustain of learning.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.227-235
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• 2024

In the era of the information revolution, the need for artificial intelligence convergence education is emerging in the trend of global change. Therefore, in this paper, a physical computing programming education method that combines artificial intelligence was developed and applied. The control group was provided with physical computing programming education that did not converge with artificial intelligence, and the experimental group developed and applied a physical computing programming education method that fused artificial intelligence to analyze the impact on elementary school students' computing thinking ability. As a result, it was confirmed that physical computing programming education fused with artificial intelligence had a more positive effect on enhancing elementary school students' computational thinking skills compared to physical computing programming education without artificial intelligence.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.719-722
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• 2021

최근 인공지능의 새로운 기술들이 하루가 다르게 발전하고 있다. 이에 본 연구에서는 인공지능 교육과 글쓰기 교육을 연계하여 초등학생들의 어휘력 향상을 위한 수업을 설계하고자 한다. 그 방법으로는 본 수업에 앞서 어휘 10문제를 테스트하여 실험에 참가하기 전의 어휘력을 점검한다. 그 후 머신러닝 포키즈를 이용하여 여러 감정에 해당되는 단어들을 다양하게 훈련하도록 하였고, 그 후 관련된 어휘 10문제를 다시 테스트 하였다. 실험 결과 실험에 참가하기 전에는 100점 만점에 58.8점으로 나왔으나 훈련 후의 결과는 평균 68점으로 모든 학생의 성적이 좋아지는 결과를 얻을 수 있었다. 어휘력 문항수가 적은 점과 10명의 실험참가자로 일반화할 수 없는 한계가 있다. 향후 초등교재 한권을 선정하여 어휘를 모두 분석한 후 가장 많이 등장하는 어휘를 골라내어 테스트하여 좀 더 통계적으로 의미 있는 분석을 하고자 한다.

• The Mathematical Education
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• v.63 no.2
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• pp.255-272
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• 2024

This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.301-308
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• 2020

There are concerns that the recent surge in multicultural families and the continuation of non-face-to-face education, such as remote classes caused by COVID-19, are causing educational gaps among lower grades in elementary school. In particular, the importance of reading, writing and listening to our language should be established in lower grades of elementary school. Therefore, the research has recently developed contents that can enhance understanding by utilizing highly interested artificial intelligence tools and provide interesting Korean language education through play. In the future, there will be various attempts for artificial intelligence tools to be used in lower-grade elementary school education.

• Journal of Science Education
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• v.45 no.1
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• pp.105-117
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• 2021

The purpose of this study is to analyze the gender differences of elementary, junior high, and high school students in the artificial intelligence ethics awareness (hereinafter referred to as AIEA). This is a study to investigate whether there is a gender difference in the AIEA, and if so, when the gender difference will occur. This study was conducted with 198 elementary school students (98 female students, 100 male students), 265 middle school students (166 female students, 99 male students), and 114 high school students (58 female students and 56 male students) in I Metropolitan City. The results are as follows: First, a gender difference in the AIEA between all boys and girls was confirmed. Second, the gender difference in the AIEA tended to be solidified as the school age increased from elementary school to middle school and high school. Third, female students at all stages of elementary school, junior high school, and high school are not yet very reliable in artificial intelligence, and there is a greater concern about non-discrimination than boys. It turns out that they have a negative position on permission to enter the territory. Fourth, the interaction effects of school age and gender have been identified in 'stability and reliability,' and in 'permit and limit' categories. Taken together, these results show that an educational strategy that approaches the gender equality perspective of the educational program is necessary so that there will be no gender difference in the AIEA during artificial intelligence education activities.

• 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.5
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• pp.803-812
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• 2021

This study explored the concept of artificial intelligence and the problem-solving process that can be explained through literature research. Through this study, the educational meaning and application plan of artificial intelligence that can be explained were presented. XAI education is a human-centered artificial intelligence education that deals with human-related artificial intelligence problems, and students can cultivate problem-solving skills. In addition, through algorithmic education, it is possible to understand the principles of artificial intelligence, explain artificial intelligence models related to real-life problem situations, and expand to the field of application of artificial intelligence. In order for such XAI education to be applied in elementary schools, examples related to real world must be used, and it is recommended to utilize those that the algorithm itself has interpretability. In addition, various teaching and learning methods and tools should be used for understanding to move toward explanation. Ahead of the introduction of artificial intelligence in the revised curriculum in 2022, we hope that this study will be meaningfully used as the basis for actual classes.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.61-71
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• 2021

In a situation where the online learning is expanding due to COVID-19, the current maker education has limitations in applying it to classes. This study is to design the class of online maker education using artificial intelligence tools in elementary school. Also, it is to identify the responses to it and to confirm whether it helps improve the learner's computational thinking and creative problem solving ability. The class was designed by the literature review and redesign of the curriculum. Using interveiw, the responses of instructor and learners were identified. Pre- and post-test using corresponding sample t-test was conducted. As a result, the class consisted of ten steps including empathizing, defining making problems, identifying the characteristics of material and tool, designing algorithms and coding using remixes, etc. For computing thinking and creative problem solving ability, statistically significant difference was found. This study has the significance that practical maker activities using educational artificial intelligence tools in the context of elementary education can be practically applied even in the online environment.