• International journal of advanced smart convergence
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• v.8 no.4
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• pp.113-120
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• 2019

Recently, the artificial intelligence(AI) is used in various environments in life, and research on this is being actively conducted in education. In this paper, we designed a Design-Based Research(DBR)-based AI programming education program and analyzed the application of the program for the improvement of understanding of AI in elementary school. In the artificial intelligence education program in elementary school, we should considerthat itshould be used in conjunction with software education through programming activities, rather than creating interest through simple AI experiences. The designed education program reflects the collaborative problem-solving procedures following the DBR process of analysis - design - execution - redesign, allowing the real-world problem-solving activities using AI experiences and block-type programming language. This paper also examined the examples of education programs to improve understanding of AI by using Machine Learning for Kids and to draw implications for developing and operating such a program.

• The Mathematical Education
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• v.63 no.2
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• pp.387-392
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• 2024

The use of artificial intelligence (AI) in mathematics education has advanced as a means for promoting understanding of mathematical concepts, academic achievement, computational thinking, and problem-solving. From a total of 13 studies in this special issue, this editorial reveals threads of potential and future directions to advance mathematics education with the integration of AI. We generated five themes as follows: (1) using ChatGPT for learning mathematical content, (2) automated grading systems, (3) statistical literacy and computational thinking, (4) integration of AI and digital technology into mathematics lessons and resources, and (5) teachers' perceptions of AI education. These themes elaborate on the benefits and opportunities of integrating AI in teaching and learning mathematics. In addition, the themes suggest practical implementations of AI for developing students' computational thinking and teachers' expertise.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.513-520
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• 2024

This study investigates the changes in teachers' roles as the impact of AI on school education expands. Traditionally, teachers have been responsible for core aspects of classroom instruction, curriculum development, assessment, and feedback. AI can automate these processes, particularly enhancing efficiency through personalized learning. AI also supports complex classroom management tasks such as student tracking, behavior detection, and group activity analysis using integrated camera and microphone systems. However, AI struggles to automate aspects of counseling and interpersonal communication, which are crucial in student life guidance. While direct conversational replacement by AI is challenging, AI can assist teachers by providing data-driven insights and pre-conversation resources. Key competencies required for teachers in the AI era include expertise in advanced instructional methods, dataset analysis, personalized learning facilitation, student and parent counseling, and AI digital literacy. Teachers should collaborate with AI to emphasize creativity, adjust personalized learning paths based on AI-generated datasets, and focus on areas less amenable to AI automation, such as individualized learning and counseling. Essential skills include AI digital literacy and proficiency in understanding and managing student data.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.315-320
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• 2021

In order to prepare for future social changes, SW·AI education is essential. In this paper, after conducting non-face-to-face SW·AI education for pre-service teachers, the effectiveness of SW education before and after education was measured using the measurement tool on the software educational effectiveness. As a result of the analysis, the overall average and the average of the 'computational thinking' and 'SW literacy' domains increased significantly, and the difference between the averages before and after education was statistically significant in decomposition, pattern recognition, abstraction, and algorithm, which are sub domains of 'computational thinking'. Through SW·AI education, students not only recognize the necessity of SW education and the importance of computational thinking, but also understand the process of decomposing information, recognizing and extracting patterns, and expressing problem-solving processes. It can be seen that non-face-to-face SW·AI education has the effect of improving computational thinking and SW literacy beyond recognizing the importance of SW.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.21-26
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• 2022

This study aims to enhance the cultivation of SW·AI basic competencies of middle school students by forming and distributing SW·AI education programs for middle school students who form the basis of their lives. In addition, by planning SW·AI education programs in connection with the regular curriculum, it is intended to serve as a cornerstone for the public education of SW·AI education that will be implemented from 2025. To this end, the concept of SW and AI in middle school was first defined and a plan to link software/artificial intelligence learning factors to the regular curriculum was proposed, and based on this, SW·AI education programs for middle school students were prepared. Based on literature research, the understanding of artificial intelligence technology, the value of data, and the use of artificial intelligence technology in real life were set as SW·AI education contents, and educational programs were organized by linking them with the current middle school curriculum. All SW·AI education was organized in the form of practice rather than theory so that classes could be conducted centered on participants, and the purpose of the course was to cultivate the ability to use artificial intelligence technology in real life based on understanding artificial intelligence technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.188-190
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• 2022

We propose how to configure the AI education system based on the purpose of hybrid learning and the teaching-learning principle. Based on the four components of hybrid learning, we have designed the system conceptual diagram and DB configuration diagram for on-line and offline learning environments for effective AI education. The proposed AI education system model in this paper is expected to be a foundation for maximizing the effectiveness of AI education according to the level and needs of learners and building a more effective learner-centered learning environment in cultivating computational thinking in AI education.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.377-383
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• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• Education of Primary School Mathematics
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• v.26 no.3
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• pp.163-180
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• 2023

This study aimed to investigate the factors influencing the intentions of elementary school teachers to use artificial intelligence (AI) in mathematics lessons and to identify the essential prerequisites for the effective implementation of AI in mathematics education. To achieve this purpose, we examined the structural relationship between elementary school teachers' TPACK(Technological Pedagogical Content Knowledge) and the TAM(Technology Acceptance Model) using structural equation model. The findings of the study indicated that elementary school teachers' TPACK regarding the use of AI in mathematics instruction had a direct and significant impact on their perceived ease of use and perceived usefulness of AI. In other words, when teachers possessed a higher level of TPACK competency in utilizing AI in mathematics classes, they found it easier to incorporate AI technology and recognized it as a valuable tool to enhance students' mathematics learning experience. In addition, perceived ease of use and perceived usefulness directly influenced the attitudes of elementary school teachers towards the integration of AI in mathematics education. When teachers perceived AI as easy to use in their mathematics lessons, they were more likely to recognize its usefulness and develop a positive attitude towards its application in the classroom. Perceived ease of use, perceived usefulness, and attitude towards AI integration in mathematics classes had a direct impact on the intentions of elementary school teachers to use AI in their mathematics instruction. As teachers perceived AI as easy to use, valuable, and developed a positive attitude towards its incorporation, their intention to utilize AI in mathematics education increased. In conclusion, this study shed light on the factors influencing elementary school teachers' intentions to use AI in mathematics classes. It revealed that teachers' TPACK plays a crucial role in facilitating the integration of AI in mathematics education. Additionally, the study emphasized the significance of enhancing teachers' awareness of the advantages and convenience of using AI in mathematics instruction to foster positive attitudes and intentions towards its implementation. By understanding these factors, educational stakeholders can develop strategies to effectively promote the utilization of AI in mathematics education, ultimately enhancing students' learning outcomes.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.391-400
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• 2020

While artificial intelligence (AI) is attracting attention as a core technology in the era of the 4th industrial revolution, needs for artificial intelligence education to cultivate AI literacy is emerging. In this regard, we developed and applied a project-based AI education program for elementary and middle school students, and analyzed its effects. Participants were assigned into teams with three members, and each team engaged in a project-based AI education program for two nights and three days. In the project, they selected an real-world problem they wanted and devised an AI-enabled artifact to solve it. The effectiveness of the program was investigated with the changes in attitude and efficacy of learners toward artificial intelligence. The results showed that the AI project learning positively changed both attitudes and efficacy toward artificial intelligence at a statistically significant level. This change was more pronounced as the level of perceived programming skills increased, and the level of interest in the project learning increased.