• Journal of Digital Convergence
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• v.19 no.9
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• pp.201-207
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• 2021

As artificial intelligence gradually expands into jobs, iIt is necessary to nurture talents with AI literacy capabilities required for non-majors. Therefore, in this study, based on the necessity and current status of AI education, AI literacy competency improvement education was conducted for non-majors so that AI learning could be sustainable in relation to future majors. For non-majors at University D, problem-solving solutions through project-based data analysis and visualization were applied over 15 weeks, and the AI ability improvement and effectiveness of learners before and after education were analyzed and verified. As a result, it was possible to confirm a statistically significant level of positive change in the learners' data analysis and utilization ability, AI literacy ability, and AI self-efficacy. In particular, it not only improved the learners' ability to directly utilize public data to analyze and visualize it, but also improved their self-efficacy to solve problems by linking this with the use of AI.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.59-67
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• 2021

The development of AI technology has brought about a big change in our lives. As AI's influence grows from life to society to the economy, the importance of education on AI and data is also growing. In particular, the OECD Education Research Report and various domestic information and curriculum studies address data literacy and present it as an essential competency. Looking at domestic and international studies, one can see that the definition of data literacy differs in its specific content and scope from researchers to researchers. Thus, the definition of major research related to data literacy was analyzed from various angles and derived from various angles. In key studies, Word2vec natural language processing methods, along with word frequency analysis used to define data literacy, are used to analyze semantic similarities and nominate them based on content elements of curriculum research to derive the definition of 'understanding and using data to process information'. Based on the definition of data literacy derived from this study, we hope that the contents will be revised and supplemented, and more research will be conducted to provide a good foundation for educational research that develops students' future capabilities.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.141-149
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• 2021

Due to the rapid rise of artificial intelligence technology around the world, SW education conducted in elementary and secondary schools is expanding including AI education. Therefore, this study aims to present an AI education system based on 4P(Play, Problem Solving, Product Making, Project) that can be applied from kindergarten to high school. The AI education system presented in this study is designed to be applied in 4P-based Play, Problem Solving, Product Making, and Project 4 stages so that it can be applied by school age and step by step. The level was presented by dividing it into two areas: AI literacy and AI development. In order to verify the validity of the developed AI education system, the Delphi method was applied to 15 experts who had experience in SW education or AI education. The AI education system derived as a result of the verification will be able to contribute to the development of a content system for AI education at each school level in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.225-238
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• 2022

Although the importance of literacy in Artificial Intelligence (AI) education is increasing, there is a lack of testing tools for measuring such competency. To address this gap, this study developed a testing tool that measures AI literacy among middle school students. This goal was achieved through the establishment of an expert group that was enlisted to determine the relevant factors and items covered by the proposed tool. To verify the reliability and validity of the developed tool, a field review, exploratory factor analysis, and confirmatory factor analysis were conducted. These procedures resulted in a testing tool comprising six domains that encompass 30 items. The domains are the social impact of AI (eight items), the understanding of AI (six items), AI execution plans (five items), problem solving with AI (five items), data literacy (four items), and AI ethics (two questions). The items are to be rated using a five-point Likert scale. The internal consistency of the tool was .970 (total), while that of the domains ranged from .861 to .939. This study can serve as reference for developing the analysis of AI literacy, teaching and learning, and evaluation in AI education.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.227-237
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• 2021

In this thesis, a survey was conducted on elementary school teachers about the establishment of information subjects in elementary schools. As a result, the opinion that information subjects should be newly established for ICT literacy education and SW/AI education in elementary schools was very high. In addition, if it is difficult to establish a new information subject, opinions in favor of the organization of the information subject as an autonomous subject using the discretionary time of the principal were high. In light of the results of this analysis, it is judged that it is necessary to establish a new information subject for ICT literacy education and SW/AI education in the next elementary school curriculum. However, if it is difficult to establish a new information course, it is necessary to come up with a plan that can be operated in the form of autonomous subject for students wishing to learn SW/AI. And it is judged that the number of class hours should be secured for at least 1 hour or 2 hours per week in the 3rd grade and above.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.131-140
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• 2018

The KAIE computing system curriculum consists of information equipment, operating systems, and information and communication fields, and covers basic understanding and principles of computer science. The role of the teacher is important to achieve the curriculum achievement standards. Therefore, we examined the factors affecting the teaching capacity of the KAIE computing system curriculum. The results of this study show that the teaching methods of teachers through the literacy of information and communication technology have a statistically significant effect on the teaching competency of the computing system curriculum. Also, male teachers perceived higher perceived factors than female teachers. The differences in teaching competency between teacher groups of less than 5 years and less than 5~10 years were significant. Based on these results, it is necessary to develop collaborate SW teaching strategies and mentor - centered training programs that can strengthen ICT and SW professors' competence and encourage participation of low - career teachers and female teachers.

• The Journal of Korean Association of Computer Education
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• v.18 no.1
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• pp.45-54
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• 2015

A whole society has become software-driven and each independent fields has become convergence based on computing as the new digital economy era has come. This change affect computational literacy using computational thinking is emphasized the importance as the core competence for the future living. It means that supply of manpower with understanding software principle will decide the fate of the country. For this reason, each country are reinforcing computer science education or computing education. In this paper, we researched and analysed on new global trends of computer education in school especially focused on national curriculum and policy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.151-160
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• 2019

With the advent of the Fourth Industrial Revolution, software(SW) education has become a necessity, not a choice of those who live in the digital age. Recently, many countries around the world have been actively promoting software education based on Computational Thinking(CT) for K-12 students, so software education in schools has bigger meaning as basic literacy education of future digital generation rather than coding skills. However, the integration of software education as a formal curriculum in schools is still ongoing in even other countries. Korea is also pursuing software education, but it is in the beginning stage. Therefore, we need to study the cases of other countries that have already started software education at the national level. In this paper, we first investigate the software education cases of three countries, e.g., UK, France and China with a respect of background & educational objective, development stage, and curriculum and we suggest education policies that software education can settle in Korea schools to foster a creative talented people.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.169-175
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• 2017

In this paper, we propose the elementary school teacher's training direction for effective SW education. In an effort to better understand the efficient SW training contents and methods for teachers, 200 of elementary teachers had been selected from different places in South Korea. The results showed that 1)it should be operated by focusing on the training of female teachers, especially, strengthening the contents of SW ethics. 2)It will need to actively operate the teacher training program to foster the necessary computational thinking and programing for elementary school teacher who work in big cities. 3)It need to create a training program for expanding the SW studying groups. 4)In order to improve the effectiveness of training courses in the development of in-service training programs, the SW ethics contents need to be coordinated with the link the computational thinking and programing. These results are expected to provide the efficient methods to design the future SW training programs.

• The Journal of Economics, Marketing and Management
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• v.11 no.6
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• pp.1-8
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• 2023

Purpose: In the era of the Fourth Industrial Revolution, individuals equipped with fundamental understanding and practical skills in artificial intelligence (AI) are essential. This study aimed to validate the effectiveness of AI education for enhancing AI literacy among business major student. Research design, data and methodology: Data for analyzing the effectiveness of the AI Fundamental Education Program for business major students were collected through surveys conducted at the beginning and end of the semester. Structural equation modeling was employed to perform basic statistical analyses regarding gender, grade, and prior software (SW) education duration. To validate the effectiveness of AI education, seven variables - AI interest, AI perception, data analysis/utilization, AI projects, AI literacy, AI self-efficacy, and AI learning persistence - were defined and derived. Results: All seven operationally defined variables showed statistically significant positive changes. The average differences were observed as follows: 0.47 for AI interest, 0.32 for AI perception, 0.37 for data analysis/utilization, 0.27 for AI projects, 0.25 for AI literacy, 0.39 for AI self-efficacy, and 0.41 for AI learning persistence. Statistically, AI interest exhibited the most substantial average difference. Conclusions: Through this study, the applied AI education was confirmed to enhance learners' overall competencies in AI, proving its utility and effectiveness in AI literacy education for business major students. Future research endeavors should build upon these results, focusing on ongoing studies related to AI education programs tailored to learners from diverse academic backgrounds and conducting continuous efficacy evaluations.