• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.251-258
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• 2022

In this paper, we propose a standard AI developer job training track based on industry needs. The characteristic of this curriculum is that it can minimize the mismatch of AI developer job competency between industries and universities. To develop an AI developer job training track, a survey will be conducted for AI developers working in industrial fields. In this survey, among the five NCS-based AI developer jobs, job analysis is conducted by deriving AI developer jobs with high demand for manpower in industrial fields. In job analysis, the core competency unit elements of the job are selected, and knowledge, skills, tools, etc. necessary to perform the core competency unit elements are derived. In addition, a standard AI developer job curriculum is developed by deriving core subjects and road-map that can educate knowledge, skills, tools, etc. In addition, we present an efficient AI developer job training method using the standard AI developer job training course proposed in this paper.

• East Asian mathematical journal
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• v.39 no.2
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• pp.93-117
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• 2023

The aim of this study is to explore the pre-service math teachers' characteristics of education to develop their AI literacy and SW competency, and to derive some implications. We conducted a 14-hours AI and SW education program for pre-service teachers with theory and practice, and an analysis on class observation data, video frames of classes and interview, Python programming assignments and papers. The results of this case study for 3 pre-service teachers are as follows. First, two students understood artificial neural network and deep learning system accurately, furthermore, all students conducted a couple of explorations related with performance improvement of deep learning system with interest. Second, coding and exploration activities using Python improved students' computational thinking as well as SW competency, which help them give convergence education in the future. Third, they responded positively to the necessity of AI literacy and SW competency development, and to applying coding to math class. Lastly, it's necessary to endeavor to give a coding education to the student's eye level according to his or her prerequisite and to ease the burden of student's studying AI technology.

• 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 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.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.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.113-121
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• 2021

This study was intended to present an online survey and analysis of the survey results after the operation of the AI education leading school initiation workshop consulting training and the creative convergence type information education room consulting training. Through this, it was confirmed that there is a perception that support such as AI education leading school consulting training is necessary, and the network should be activated to share best practices and an efficient and flexible operating system in terms of operation of leading schools nationwide. could In addition, while the subjects of the survey recognized the importance of AI education-related competency, it was identified that they had low awareness of their AI education-related competency, and recognized the need for various support for systematic and customized AI education-related competency reinforcement.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.39-46
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• 2023

The purpose of this study is to design and develop the test standard to measure AI literacy abilities. First, we selected key areas of AI literacy through the related studies and expert FGI and designed detailed standard. The area of the test standard is divided into three categories: AI concept, practice, and impact. In order to confirm the validity of the test standard, we conducted twice expert validity tests and then modified and supplemented the test index. To confirm the validity of the test standard, we conducted an expert validity test twice and then modified and supplemented the test standard. The final AI literacy test standard consisted of a total of 30 questions. The AI literacy test standard developed in this study can be an important tool for developing self-checklists or AI competency test questions for measuring AI literacy ability.

• Journal of Christian Education in Korea
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• v.72
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• pp.183-203
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• 2022

The purpose of this study is to construct factors of AI education utilization competency. AI education utilization competency is used as basic data for education to enhance the AI education competency of pre-service early childhood teachers. To this end, 7 studies related to competency factors and models were selected by searching for previous studies. Seven preceding studies were analyzed. As a result, 18 competency factors were extracted, including understanding of artificial intelligence. The extracted competency elements were divided into six areas, which are divided into understanding subject knowledge through coding, class preparation, class management, class result feedback, class guidance, and self-development. And 15 factors were constructed. The draft formed through coding was improved through review by three early childhood education experts. Factors improved through expert review were structured by classifying them into knowledge, skills, and attitudes to organize the curriculum. The validity of the structured competency factor was verified through expert Delphi. As a result of the Delphi verification, all factors were converged in the first survey. Through this, 6 competency areas, 11 competency factors, and 19 competency factors were composed of knowledge, 10 skills, and 5 attitudes. The implication is that the competency factors presented as a result of this study can be used as basic data for organizing a curriculum to improve the ability of pre-service early childhood teachers to use artificial intelligence education.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.99-110
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• 2023

In this study, in order to strengthen the AI utilization competency of pre-service secondary science teachers, a project activity in which pre-service teachers directly create an 'AI-based molecular structure customized learning support tool' by using Google's teachable machine was developed and applied. To this end, the program developed for 26 third-grade pre-service teachers enrolled in the Department of Chemistry Education at H University in Chungcheongbuk-do was applied for 14 sessions during extracurricular activities. Then, the perceptions of 'understanding how AI works', 'efficacy of using AI in science classes', and 'plans to utilize AI in science classes' were investigated. As a result of the study, it was found that the program developed in this study was effective in helping pre-service teachers understand the operating principle of AI technology for machine learning at a basic level and learning how to use it. In addition, the program developed in this study was found to be effective in increasing the efficacy of pre-service teachers for the use of AI in science classes. And it was also found that pre-service teachers recognized the aspect of using AI technology as a new teaching·learning strategy and tool that can help students understand science concepts. Accordingly, it was found that the program developed in this study had a positive impact on pre-service teachers' AI utilization competency reinforcement and perception improvement at the basic level. Implications of this were discussed.

• Informatization Policy
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• v.28 no.2
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• pp.34-56
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• 2021

According to the Fourth Industrial Revolution, demand for and interest in jobs in the field of AI and data science - such as artificial intelligence/data analysts - are increasing. In order to keep pace with this trend, and to supply human resources that can effectively perform such jobs in the relevant fields in a timely manner, job seekers must develop the competencies required by the companies, and universities must be in charge of training. However, it is difficult to devise appropriate response strategies at the level of job seekers, companies and universities, which are stakeholders in terms of supplying suitably competent personnel. Therefore, the purpose of this study is to determine which competencies are required in practice in order to cultivate and supply human talents equipped with the necessary job competencies, and to propose plans for the development of the required competencies at the university level. In order to identify the required competencies in the field of AI and data science, data on job postings on the LinkedIn site, the recruitment platform, were analyzed using text mining techniques. Then, research was conducted with the aim of devising and proposing concrete plans for competency development at the university level by comparing and verifying the results of the international graduate school curriculum in the field of AI and data science, and the interview results with the hiring managers, respectively, with the results of the topic model.