• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.451-460
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• 2024

This study aimed to analyze the AI and Digital education needs of students at 'C University of Education' for the development of a 'AI and Digital Education' course. To achieve this objective, Importance-Performance Analysis (IPA) was conducted with 79 fourth-year students from 'C University of Education,' focusing on 18 AI and digital education competencies. The paired sample t-test revealed significant differences between the importance and performance scores for all 18 competencies. Using the Borich needs assessment model, the results indicated that the 'Data Utilization Feedback Competency' had the highest demand. Additionally, applying The Locus for Focus model to prioritize needs, nine competencies were identified as having very high priority, including 'Data Utilization Feedback Competency,' 'Understanding Basic Knowledge Related to AI and Digital ,' and 'Practical Learning Design Based on AI and Digital.' The needs assessment results identified in this study should be actively reflected as foundational data for the development of the 'AI and Digital Education' course.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.597-603
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• 2023

This study evaluates the AI digital competencies of teachers and presents a step-by-step framework for teacher's AI digital competencies that can be utilized in training. To do this, AI digital competencies were analyzed from the perspective of utilization and disposition, linked with the Technological Pedagogical Content Knowledge (TPACK) perspective. Then, as a precedent for step-by-step teacher AI digital competencies, the 3-step competency of the British Education and Training Foundation and the UNESCO ICT Teacher Competency Framework were presented. In this study, teacher's AI digital competencies were divided into three stages: entry, adaptation, and leadership, considering precedent research and domestic conditions. The initial entry stage passed the validity test in the second round of the Delphi survey, and the other two stages passed in the first round. The final entry stage is described as a stage where teachers understand AI digital but have difficulty implementing it, the adaptation stage is a level applied to standard curricula, and the leadership stage is a level where AI digital is applied in advanced courses and teachers serve as models for others. Through the overall AI digital competencies presented in this study, detailed competency development is possible, and it can be used as a reference material for developing evaluation items.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.539-544
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• 2024

This paper examines the necessity and direction of digital literacy education as university education in the AI era. Digital literacy can be considered universal education about everyday culture in a digital environment, and its scope is expanding to cultivate the competencies necessary for citizens of a digital society, rather than simply the ability to use digital devices. In this paper, the university liberal arts curriculum has strengthened the information literacy area to reflect the changes of the times, but it is presented as a problem that it is still focused on the technical aspects of learning how to use digital devices and specific programs. It was suggested that the direction of digital literacy education in universities should not be limited to the technical and instrumental aspects of using digital devices, but that it would be desirable to focus on digital ethics considering the social impacts that may arise from the use of digital devices.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.341-352
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• 2022

The wave of a knowledge and information society led by AI, Big Data, and so on is having an all-round impact on our way of life. Therefore the Ministry of Education is in a hurry to strengthen Digital Literacy, including AI and SW Education, by improving the curriculum that can cultivate basic knowledge and capabilities to respond to changes in the future society. It can be seen that establishing a foundation for cultivating Digital Literacy through all subjects and improving basic and in-depth learning in new technology fields such as AI linked to the information curriculum is an essential part for future society. However, research on each content for cultivating Digital and AI literacy is relatively active, while research on teaching and learning strategies is insufficient. Therefore in this study, a CT-based Digital and AI teaching and learning strategy that can foster that was developed and Delphi expert verification was conducted, and the final teaching and learning strategy was completed after evaluating instructor usability and analyzing learner effectiveness.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.261-279
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• 2024

The purpose of this study is to examine the characteristics of AI courseware for mathematics learning based on Choppin et al.'s (2014) digital typology and to derive implications for directions for AI courseware development. For this purpose, 12 types of AI courseware actively used in domestic were selected for analysis, and the characteristics of these AI courseware in terms of program-student interaction, teacher' s lesson design, and evaluation system were analyzed. As a result, each AI courseware provided unique functional features for students, teachers, and evaluation, but the ability to modify and configure teaching and learning was limited. Based on these results, implications for the direction of development of AI courseware in mathematics education were presented.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.199-226
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• 2024

In response to the era of transformation necessitating the introduction of Artificial Intelligence (AI) and digital technologies, educational innovation is undertaken with the implementation of AI digital textbooks in Mathematics, English, and Information subjects by 2025 in Korea. Within this context, this study analyzed the perceptions and needs of elementary school teachers regarding mathematics AI digital textbook. Based on a survey conducted in November 2023, involving 132 elementary school teachers across the country, the analysis revealed that the majority of elementary school teachers had a low perception of the introduction and need for mathematics AI digital textbooks. However, some recognized the potential for personalized learning and effective teaching support. Furthermore, among the core technologies of the AI digital textbook, teachers highly valued the necessity of learning diagnostics and teacher reconfiguration functions and had the most positive perception of their usefulness in math lessons, while their perception of interactivity was relatively low. These findings suggest the need for changing teachers' perceptions through professional development and information provision to ensure the successful adoption and use of mathematics AI digital textbooks. Specifically, providing concrete and practical ways to use the AI digital textbook, exploring alternatives to digital overload, and continuing development and research on core technologies.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.397-398
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• 2022

본 논문에서는 SK텔레콤에서 진행하는 디지털 선도기업 아카데미 FLYAI의 교육과정을 설계하고 개발한다. 이 교육과정은 Project Based Learning(272시간)과 Product Based Learning(128시간)으로 구성하여 총 400시간을 교육하도록 설계한다. 특히 Product Based Learning의 AI-Hackathon(80시간)에서는 SK텔레콤 각 부서에서 제안하는 제픔을 기획하고 개발하는 과정으로 SK텔레콤 AI 개발자들이 멘토로 참여함으로써 기업 현장의 경험을 체험할 수 있도록 개발한다.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.139-147
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• 2016

The purpose of this study is to identify the relationships between AI education characteristics and psychological capital, psychological capital and flow, AI characteristics and flow through meditating effect of psychological capital in the digital convergence society. There are three AI characteristics: correctness, usefulness, easy of use. This empirical study was examined by 282 questionnaires to the three universities that teach accounting information system. It was performed by three-step method of the hierarchical regression analysis for the multiple regression analysis and parameter using the SPSS 22.0. The results and implications by analysis are as follows. First, AI characteristics and psychological capital have statistically significant positive influence. From AI attribute, correctness was established as the most important element. Second, psychological capital positively(+) influences flow. It allowed for the developed in flow. Third, psychological capital was shown as the major meditative variable between AI characteristics and flow. Through these, this paper suggests to reinforce self-efficacy, hope, resilience, optimism.

• 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.