• Informatization Policy
• /
• v.29 no.2
• /
• pp.3-36
• /
• 2022

Most research in artificial intelligence (AI) has focused on the development of new algorithms. But as artificial intelligence has been spreading over many applications and gaining more attention from managers in the organization, academia has begun to understand the necessity of developing new artificial intelligence theories related to AI management. We reviewed recent studies in the field from 2015, and further analysis has been done for 785 studies chosen based on citation numbers of over 20. The results show that most studies have still been in the prototyping application phase of artificial intelligence across different industries. We conclude our study by calling for more research in the application of artificial intelligence in terms of organizational structures and project and risk management.

• Journal of The Korean Association of Information Education
• /
• v.24 no.5
• /
• pp.453-462
• /
• 2020

With the development of artificial intelligence, a lot of platforms have emerged that enable anyone to easily access and learn about artificial intelligence or create artificial intelligence models. Therefore, in this study, we analyzed various artificial intelligence education platforms and developed and proposed a SW education class plan using a framework-based artificial intelligence education platform for activating artificial intelligence based SW education. The artificial intelligence-based SW education framework aims to cultivate artificial intelligence literacy on the basis of computational thinking. In addition, a learner-centered project class was formed to include elements that could be fused with real life contexts or other subjects. Using this, with the theme of creating an artificial intelligence program to help separate garbage collection, a six-hour project-based class was developed and proposed using practical arts, social studies, and creative experiential activities. This project class was organized using a platform that is not difficult, such as AI Oceans and Entry.

• Journal of The Korean Association of Information Education
• /
• v.24 no.4
• /
• pp.391-400
• /
• 2020

While artificial intelligence (AI) is attracting attention as a core technology in the era of the 4th industrial revolution, needs for artificial intelligence education to cultivate AI literacy is emerging. In this regard, we developed and applied a project-based AI education program for elementary and middle school students, and analyzed its effects. Participants were assigned into teams with three members, and each team engaged in a project-based AI education program for two nights and three days. In the project, they selected an real-world problem they wanted and devised an AI-enabled artifact to solve it. The effectiveness of the program was investigated with the changes in attitude and efficacy of learners toward artificial intelligence. The results showed that the AI project learning positively changed both attitudes and efficacy toward artificial intelligence at a statistically significant level. This change was more pronounced as the level of perceived programming skills increased, and the level of interest in the project learning increased.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.8
• /
• pp.253-261
• /
• 2022

In this study, the educational effect were sought to be identified after developing and applying project learning for the artificial intelligence based liberal arts education for the non-computer majors. A paired-sample t-test was performed within each group to determine the extent of improvement in the learning flow and artificial intelligence efficacy in the experimental and control groups. After class, an independent sample t-test was performed to examine the statistical effects of pre-test and post-test on the learning flow and artificial intelligence efficacy in the experimental and control groups. The experimental group and control group demonstrated significant improvements in the learning flow and artificial intelligence efficacy before and after class, each respectively. There was no statistically significant difference in the learning flow between the experimental group for which the project learning method was applied and the control group for which only theory and practice were conducted in the artificial intelligence class. It was also confirmed that the experimental group for which the project learning method was applied improved the efficacy of artificial intelligence to a significant level compared to the control group which only proceeded with theory and practice.

• Electronics and Telecommunications Trends
• /
• v.29 no.4
• /
• pp.30-38
• /
• 2014

최근의 플랫폼 기술동향은 웹 기반 혹은 단순 의사소통이 가능한 모바일 플랫폼에서 빅데이터와 인공지능기술이 접목되면서 심층 질의응답이 가능한 차세대 지능형 지식처리 플랫폼으로의 진화가 진행 중이다. 선진국에서는 국가 차원 혹은 글로벌 기업의 주도하에 대형 장기 프로젝트가 진행 중이다. 국가 주도의 프로젝트로는 미국의 PAL, 유럽의 Human Brain, 일본의 Todai 프로젝트가 대표적인 예이며, 글로벌 기업의 경우는 IBM의 Watson, Google의 Knowledge Graph, Apple의 Sir가 대표적인 예이다. 본고에서는 차세대 지능형 플랫폼의 핵심기술인 인간과 기계의 지식소통을 위한 빅데이터 기반의 지식처리 인공지능 소프트웨어 기술의 개념과 국내외 기술 및 산업, 지식재산권 동향 등을 살펴보고 산업계 활용방안 및 발전방향에 대해 논하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.19-22
• /
• 2024

전통 소프트웨어 프로젝트 개발과 AI 관련된 소프트웨어 프로젝트 개발에 큰 차이가 있어서 AI 관련된 소프트웨어 프로젝트 개발 환경을 이해하려는 많은 노력이 있었지만 AI 관련 소프트웨어 프로젝트 개발에서 어떤 API들이 자주 사용되는지에 대해서 아직 충분히 조사되지 않았다. 본 논문에서는 "AI 관련 오픈 소스 소프트웨어 프로젝트에서 어떤 파이썬 API들이 자주 사용되는가?"에 대한 연구 질문의 해답을 알아보는 경험 연구를 소개한다. 이 경험 연구의 결과로 AI 관련 오픈 소스 소프트웨어 프로젝트에서 파이썬 표준 라이브러리와 관려된 API들이 가장 자주 사용된다는 것을 확인했다. 또한 기계 학습을 포함해서 데이터 처리, 이미지 처리, 테스팅, 웹 서비스와 관련된 라이브러리들에 있는 API들도 AI 관련 오픈 소스 소프트웨어 프로젝트들에 자주 사용된다는 것을 알아냈다.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.3
• /
• pp.110-115
• /
• 2021

With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.

• The Mathematical Education
• /
• v.62 no.2
• /
• pp.289-302
• /
• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• 발명특허
• /
• v.16 no.10 s.188
• /
• pp.52-57
• /
• 1991

인간이 지닌 지적인 능력을 규명하여 컴퓨터로 하여금 지능이 필요로 하는 일을 수행할 수 있도록 하는 인공지능(Artificial Intelligence, 이하 AI)기술에 관한 관심이 높아지고 있는 가운데 선진각국에서는 철강, 자동차, 산업기계 등 다양한 분야에서 제품의 라이프 사이클 단축, 다품종 소량 생산, 효율적인 조업, 고도의 품질제어 요구에 유연하게 대처하기 위하여 인공지능 개발 프로젝트를 활발히 진행중이다. 본고에서는 산업기계분야에서 인공지능 개발에 필요한 기반환경에 대하여 살펴보고 선진국의 주요 개발동향 및 우리나라의 개발실태를 살표보고자 한다.

• 발명특허
• /
• v.16 no.11 s.189
• /
• pp.50-53
• /
• 1991

인간이 지닌 지적인 능력을 규명하여 컴퓨터로 하여금 지능이 필요로 하는 일을 수행할 수 있도록 하는 인공지능(Artificial Intelligence, 이하 AI)기술에 관한 관심이 높아지고 있는 가운데 선진각국에서는 철강, 자동차, 산업기계 등 다양한 분야에서 제품의 라이프 사이클 단축, 다품종 소량 생산, 효율적인 조업, 고도의 품질제어 요구에 유연하게 대처하기 위하여 인공지능 개발 프로젝트를 활발히 진행중이다. 본고에서는 산업기계분야에서 인공지능 개발에 필요한 기반환경에 대하여 살펴보고 선진국의 주요 개발동향 및 우리나라의 개발실태를 살펴보고자 한다.