• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.238-250
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• 2018

The 2015 revised curriculum includes 'informatics' course including the process of building software aiming at cultivating creative and convergent ability. This study analyzes the competencies pursued in the revised curriculum and defines computational thinking as the main competency. The subjects of the study were the first grade of a middle school in the first semester of the 2018 school year. Of the 95 collected data, 83 data were used for analysis and the significance was confirmed by the paired t-test. Also, computational concept, computational practice and computational perspectives were confirmed through artifact-based interviews. As a result of statistical analysis, critical thinking, creativity, algorithmic thinking, and problem-solving significantly increased among sub-variables of computational thinking. Statistical results and interview results were analyzed to provide implications for design and implementation of software education in 'informatics' course.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.423-436
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• 2021

In the future, artificial intelligence (AI) technology is expected to become a general-purpose technology (GPT), and it is predicted that AI competency will become an essential competency. Several nations around the world are fostering experts in the field of AI to achieve technological proficiency while working to develop the necessary infrastructure and educational environment. In this study, we investigated the status of software education at the liberal arts level at 31 universities in Seoul, along with precedents from domestic and foreign AI education research. Based on this, we concluded that an AI literacy education model is needed to link software education at the liberal arts level with professional AI education. And we classified 20 AI-related lectures released in the KOCW according to the AI literacy competencies required; based on the results of this classification, we propose a model for AI literacy education in the liberal arts for undergraduate students. The proposed AI literacy education model may be considered as AI·SW convergence to experience AI along with literacy in the humanities, deviating from the existing theoretical and computer-science-based approach. We expect that our proposed AI literacy education model can contribute to the proliferation of AI.

• 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.5 no.2
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• pp.183-191
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• 2019

The purpose of this paper is to develop an unplugged education program that develops the 4C (Creativity, Critical thinking, Communication ability, Collaboration) and CT (Computational Thinking) competencies required in modern society. This study discovered "Fine Dust Robot" as a theme suitable for the unplugged education program, and designed the Unplugged 4-hour education program which can develop 4C and CT competencies. The first stage motivates learning, and the second and third stages develop unplugged activity to develop CT. In the fourth stage, the algorithms created through unplugged activities were programmed through the natural language instruction card and produced the output. We developed educational materials that can be utilized in the unplugged education program. Finally, education programs were conducted for elementary school students, and pre- and post-tests of computational thinking were conducted for general students and gifted students. Educational effective was found in both groups.

• The Journal of Korean Association of Computer Education
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• v.18 no.3
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• pp.105-114
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• 2015

A SW competency based on computational thinking is considered as one of the core competencies in the future society. However, the concept of computational thinking is difficult to be introduced to the class because of the lack of appropriate educational program and the shortage of proper understandings of students and teachers. Thus, we have applied computational thinking based STEAM program and analyzed its effectiveness to explore the educational possibilities of computational thinking. The 49 samples were selected, 23 for the experimental group, and 26 for the control group. Pre-post tests for integrated thinking abilities and computational thinking were done to explore the CT-STEAM program's effectiveness. As a result, the components of integrated thinking abilities, science preference and self-directed learning abilities were enhanced after CT-STEAM instruction. In addition, computational thinking assessment score was statistically significant. We expect new STEAM programs using various computing tools to be developed in the future.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.285-293
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• 2021

With the advent of the 4th Industrial Revolution, AI utilization capabilities are being emphasized in various industries, but AI education design and curriculum research as universal education is currently lacking. This study offers a design for universal AI education to further cultivate its use in universities. For the AI basic education design, a questionnaire was conducted for experts three times, and the reliability of the derived design contents was verified by reflecting the results. As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived were data structure understanding and processing, visualization, word cloud, public data utilization, and machine learning concept understanding and utilization. The educational design content derived through this study is expected to increase the value of competency-centered AI universal education in the future.

• Journal of The Korean Association of Information Education
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• v.22 no.5
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• pp.519-533
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• 2018

This study aims to classify the types of instructional expertise development activities of teachers who teach subjects related to software education in primary schools. To this end, the study analyzes their participation in expertise development activities over the recent three years, outcomes from these activities, and forms and characteristics of expertise development activities. In the questionnaire survey conducted for this study, 276 primary school teachers participated. According to the survey, the same largest proportion of them participated in collective job training (96%) and distant job training (96%), followed by consulting, instruction supervision, mentoring, and peer observation (82%), lectures, workshops, and seminars held by related government ministries and the provincial and municipal offices of education (69%), and teachers' study communities (66%). Among informal activities, reading accounted for the highest portion of the activities (88%), followed by the use of information on Websites including YouTude and GitHub (80%), and teachers' expertise development networks (76%). The reasons for their participation in the activities were mostly to improve their instructional expertise (80%). Their participation in the activities had an impact on usefulness to enhance instructional expertise, improvement of job competencies, application to current jobs, sense of instructional efficacy, and positive effect. These results of the study are expected to provide a foundation for preparing continued expertise development plans that can promote the educational value of primary school teachers' instructional expertise development activities for teaching subjects related to software education.

• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.141-151
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• 2022

Recently, basic literacy education related to digital literacy and data literacy has been emphasized for students who will live in a rapidly developing future digital society. Accordingly, demand for education to improve big data and data literacy is also increasing in general universities and universities of education as basic knowledge. Therefore, this study designed and applied big data analysis courses for pre-service teachers and analyzed the impact on data literacy. As a result of analyzing the interest and understanding of the input program, it was confirmed that it was an appropriate form for the level of pre-service teachers, and there was a significant improvement in competencies in all areas of 'knowledge', 'skills', and 'values and attitudes' of data literacy. It is hoped that the results of this study will contribute to enhancing the data literacy of students and pre-served teachers by helping with systematic data literacy educational research.

• 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.

• 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.