• 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.

• The Journal of Information Systems
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• v.30 no.3
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• pp.177-199
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• 2021

Purpose This study explores the development direction of the artificial intelligence curriculum as a universal education that enhances the ability of college students to flexibly use artificial intelligence these days, where artificial intelligence education is spreading, and the educational components based on this are subdivided according to the characteristics of each major. Design/methodology/approach In order to develop the educational purpose of the subject and the detailed educational curriculum suitable for the subject of education, we first analyzed domestic and foreign prior research related to artificial intelligence liberal arts education. As the main components derived by experts, the basic concept of artificial intelligence converges to literacy to read and write for everyday problem solving, as well as problem-solving ability to manipulate real data and software. Findings The results showed that In the artificial intelligence literacy module, trends and prospects of artificial intelligence and necessary competencies were checked, and cases applied to major fields were examined. In the AI utilization and application part, basic data analysis items and content composition were composed through creative thinking, logical thinking, and intelligence. In order to design the curriculum, a software development language suitable for each major area was first selected, and AI education content areas, elements, and packages were defined and designed for each major area to meet the objectives of the subject.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.927-934
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• 2021

AI(Artificial intelligence) is gradually taking up a large part of our lives, and the pace of AI development is accelerating. It is called ACT that develop students' computational thinking in the way artificial intelligence learns. Among ACTs, pattern recognition is an essential factor in efficiently solving problems. Pattern analysis is part of the pattern recognition process. In fact, Netflix's personalized movie recommendation service and what it named Covid-19 after repeated symptoms are all the results of pattern analysis. While the importance of ACT, including pattern recognition, is highlighted, software education for kindergarten and elementary school lower grades is much insufficient compared to foreign countries. Therefore, this study aims to design and develop textbooks for the development of artificial intelligence-based computational thinking through pattern analysis for kindergarten students.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.937-940
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• 2020

본 논문은 AI 기술을 기반으로 텍스트 스크립트를 자동으로 인식하고 영상 합성 기술을 응용하여 텍스트 정보를 시각화하는 AI 아나운서 소프트웨어 연구에 대하여 기술한다. 기존의 AI 기반 영상 정보 전달 서비스인 AI 앵커는 텍스트를 인식하여 영상을 합성하는데 오랜 시간이 필요하였으며, 특정 인물 이미지로만 영상 합성이 가능했기 때문에 그 용도가 제한적이었다. 본 연구에서 제안하는 방법은 Tacotron 으로 새로운 음성을 학습 및 합성하여, LRW 데이터셋으로 학습된 모델을 사용하여 자연스러운 영상 합성 체계를 구축한다. 단순한 얼굴 이미지의 합성을 개선하고 다채로운 이미지 제작을 위한 과정을 간략화하여 다양한 비대면 영상 정보 제공 환경을 구성할 수 있을 것으로 기대된다.

• Journal of the Korean Society for Precision Engineering
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• v.4 no.4
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• pp.6-12
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• 1987

지능화(Intelligence) 전반적인 경향 : 생산분야에 있어서의 지능화는 인공지능(AI)기법이 활용되면서 부터 관심을 모으게 되었다. AI기법이라고 하여도 그에 관련된 기술은 Software기술, 지식표현과 같은 기초기술 에서 부터, 지식공학, 화상인식 이해, 자연언어 이해, 음성이해 등의 응용기술에 이르기까지 다양한 분야를 포함하고 있다. 여기서는, 최근 실용화 면에서 주목을 받고 있는 지식공학의 실용 또는 그 응용시스템인 expert system(전문가시스템)에 주목하면서, 설계와 공정설계 중에 최근의 AI활용과 동향을 요약해 보기로 한다.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.25-31
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• 2022

The purpose of this study is to explore the implications for the systematic operation of the AI curriculum by analyzing the current status of the AI major curriculum in universities. To this end, This study analyzed the relevant curriculum of domestic universities(a total of 51 schools) and overseas QS Top 10 universities based on the industry demand-based standard of AI major curriculum developed through prior research. The main research results are as follows. First, in the case of domestic universities, Python-centered programming subjects were lacking. Second, there were few subjects for advanced learning such as AI application and convergence. Third, the subjects required to perform the AI developer job were insufficient. Fourth, in the case of colleges, the ratio of AI mathematics-related subjects was low. Based on these results, this study presented implications for the systematic operation of the AI major education.

• 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 Society of Industry Convergence
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• v.25 no.2_2
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• pp.247-255
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• 2022

Robot Process Automation (RPA) is a computer technology called Robotic Process Automation, a form of business process automation based on the concept of software robots or artificial intelligence (AI) walkers. In general, in traditional workflow automation tools, software developers design software that creates a set of actions to automate tasks and interfaces for the back-end systems using internal APIs or dedicated script languages. However, in RPA software, automation can be implemented by configuring an operating processor as if the general user is directly performing the task of the application. In other words, it can be said that it is a suitable development method for automating simply repetitive tasks rather than developing specific programs in which all necessary functions are implemented, as in general software development. Thus, this is more appropriate for configuring and automating RPA software in traditional manufacturing companies that are not easy to develop and apply smart factories or high-end AI software. Therefore, this research aims to analyze the requirements required at the actual manufacturing companies, focusing on the manufacturer's case in Changwon, Gyeongsangnam-do, called SinceWin Co., Ltd., and to examine the possibility of RPA software in the manufacturing companies by implementing actual RPA software that supports office automation. Through the research, it was confirmed that the actually implemented RPA software met the requirements of the company and helped manufacturer practice significantly by automating the parts that were worked error-prone and manually periodically.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.