• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.65-73
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• 2022

In this study, by using Entry text model learning, educational contents for artificial intelligence education of elementary school students are developed and applied to actual classes. Based on the elementary and secondary artificial intelligence content table, the achievement standards of practical software education and artificial intelligence education will be reconstructed.. Among text, images, and sounds capable of machine learning, "production of emotion recognition programs using text model learning" will be selected as the educational content, which can be easily understood while reducing data preparation time for elementary school students. Entry artificial intelligence is selected as an education platform to develop artificial intelligence education contents that create emotion recognition programs using text model learning and apply them to actual elementary school classes. Based on the contents of this study, As a result of class application, students showed positive responses and interest in the entry AI class. it is suggested that quantitative research on the effectiveness of classes for elementary school students is necessary as a follow-up study.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.245-252
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• 2023

In this study, we analyzed elementary school teachers' perception and method of establishing a new subject according to their computing competency. First, we developed a survey on the need to establish a new elementary school informatics. We also collected data from 166 elementary school teachers. As a result of the analysis, opinions differed on the establishment of information subjects depending on teachers' computing competencies. Teachers also showed differences in the characteristics of their subjects, number of class hours, and methods of organizing classes. As the results, we found that in order to establish a new information subject, a plan must be prepared to raise awareness and the need for informatics subjects among teachers who have low computing compency or no major in computer-related fields. We hope that many elementary school teachers will recognize the necessity and importance of establishing a new information subject.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.197-206
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• 2021

This study is a case of convergence education using the AI model of entry in elementary schools. The subject is English, and the class was conducted based on the image learning model among the convergence activities with the art department drawing and the AI model of the entry. In order to effectively achieve the learning goals of speaking and writing in English education. The class was designed by combining art and SW. Students experienced communication using AI, improved confidence, and were able to improve creativity and communication skills by expressing not only listening and speaking but also expressing through various media such as pictures and photos. In addition, in order to find out the effectiveness of the class, a survey was conducted on students and the results were analyzed. As a result of the analysis, it was found that it had a positive effect on students' participation rate, degree of understanding AI after class, interest in AI, satisfaction with AI classes.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.62-68
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• 2022

Evaluation as learning is important for the learner competency test, and the applicable method is studied. Assessment is the role of diagnosing the current learner's status and facilitating learning through appropriate feedback. The system is insufficient to enable process-oriented evaluation in small educational institute. Focusing on becoming familiar with the AI through experience can end up simply learning how to use the tools or just playing with them rather than achieving ultimate goals of AI education. In a previous study, the experience way of AI education with PLAY model was proposed, but the assessment stage is insufficient. In this paper, we propose ELAS (Experiential K-12 AI education Learning Assessment System) for small educational institute. In order to apply the Assessment factor in in this system, the AI-factor is selected by researching the goals of the current SW education and AI education. The proposed system consists of 4 modules as Assessment-factor agent, Self-assessment agent, Question-bank agent and Assessment -analysis agent. Self-assessment learning is a powerful mechanism for improving learning for students. ELAS is extended with the experiential way of AI education model of previous study, and the teacher designs the assessment through the ELAS system. ELAS enables teachers of small institutes to automate analysis and manage data accumulation following their learning purpose. With this, it is possible to adjust the learning difficulty in curriculum design to make better for your purpose.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.253-259
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• 2021

In line with the modern society where artificial intelligence has spread throughout society, the Ministry of Education decided to provide AI education in kindergartens, elementary, middle and high school classes in 2025, and develop related learning materials and textbooks from 2021. Korea currently does not have state-led AI education for kindergarten and elementary school, so there is no systematic teaching material. Therefore, this study designed and presented textbooks for pattern analysis-based computational thinking development based on the GPS curriculum, a kindergarten SW curriculum studied by Y. S. Jeong and S. E. Lim (2020). Class procedures for using the textbooks were classified as introduction activities, development activities, and organization activities. Supplementary explanations were presented by presenting textbooks and teaching aids along with explanations of each activity. In order for this study to help AI education conducted in 2025, research must be conducted to demonstrate its effectiveness through actual application in the future.

• The Journal of Industrial Distribution & Business
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• v.12 no.8
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• pp.21-32
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• 2021

Purpose: With the advent of the era of the 4th industrial revolution, called a new technological revolution, the necessity of fostering future talents equipped with AI utilization capabilities is emerging. However, there is a lack of research on AI education design and competency-based education curriculum as education for business major. The purpose of this study is to design AI education to cultivate competency-oriented AI literacy for business major in universities. Research design, data and methodology: For the design of AI basic education in business major, three expert Delphi surveys were conducted, and a demand analysis and specialization strategy were established, and the reliability of the derived design contents was verified by reflecting the results. Results: As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived from this were data structure understanding and processing, visualization, web scraping, web crawling, public data utilization, and concept of machine learning and application. Conclusions: The educational design content derived through this study is expected to help establish the direction of competency-centered AI education in the future and increase the necessity and value of AI education by utilizing it based on the major field.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.463-471
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• 2020

Humanity faces the fourth industrial revolution, a time of technological revolution by the collaboration of various industries including the fields of artificial intelligence(AI) and big data. Many countries are focused on fostering AI talent to prevail in the coming technological revolution. While Korea also provides some strategies to enhance the cultivation of AI talent, it is still difficult for Korean undergraduate students to get involved in AI studies. Through on the implementation of 'Big data analysis based AI education', which allows an easier approach to AI education, this paper examined the changes in the attitudes of undergraduate students regarding general AI education. 'Big data analysis based AI education' was provided at undergraduate level for 5.5 weeks (15 hours). The attitudes of undergraduate students were analyzed by pre-postmortem. The results showed there was a significant improvement in confidence and self-directed in regard to receiving AI education. With these results, further active research to develop basic AI education that also increases confidence and self-initiative can be expected.

• 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.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Journal of Engineering Education Research
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• v.24 no.3
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• pp.50-57
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• 2021

Although the mathematics education process in AI education is a very important issue, little cases are reported in developing effective methods on AI and mathematics education at the university level. The universities cover all fields of mathematics in their curriculums, but they lack in connecting and applying the math knowledge to AI in an efficient manner. Students are hardly interested in taking many math courses and it gets worse for the students in humanities, social sciences and arts. But university education is very slow in adapting to rapidly changing new technologies in the real world. AI is a technology that is changing the paradigm of the century, so every one should be familiar with this technology but it requires fundamental math knowledge. It is not fair for the students to study all math subjects and ride on the AI train. We recognize that three key elements, SW knowledge, mathematical knowledge, and domain knowledge, are required in applying AI technology to the real world problems. This study proposes a modular approach of studying mathematics knowledge while connecting the math to different domain problems using AI techniques. We also show a modular curriculum that is developed for using math for AI-driven autonomous driving.