• Title/Summary/Keyword: 인공지능 개발자

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Teaching and Learning Design for AI Value Judgment (인공지능 가치판단에 대한 교수학습 설계)

  • Jeong, Minhee;Shin, Seungki
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.233-237
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    • 2021
  • With the advent of the 4th industrial revolution, interest in artificial intelligence education is increasing in elementary schools. In order to nurture future talents with artificial intelligence capabilities, AI education should be actively conducted at school sites. Although basic software education is provided in the 2015 revised curriculum, there is a tendency to view the programming process that creates artificial intelligence only as a problem-solving process. However, when creating an artificial intelligence, the value of the developer who creates artificial intelligence is projected. Therefore, it is necessary to deal with the contents of artificial intelligence value judgment during SW education. This study has limitations due to the fact that Delphi research was conducted with a group of experts. In the future, it is judged that quantitative research should be conducted to supplement these limitations.

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A Study on Teaching of Convolution in Engineering Mathematics and Artificial Intelligence (인공지능에 활용되는 공학수학 합성곱(convolution) 교수·학습자료 연구)

  • Lee, Sang-Gu;Nam, Yun;Lee, Jae Hwa;Kim, Eung-Ki
    • Communications of Mathematical Education
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    • v.37 no.2
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    • pp.277-297
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    • 2023
  • In mathematics, the concept of convolution is widely used. The convolution operation is required for understanding computer vision and deep learning in artificial intelligence. Therefore, it is vital for this concept to be explained in college mathematics education. In this paper, we present our new teaching and learning materials on convolution available for engineering mathematics. We provide the knowledge and applications on convolution with Python-based code, and introduce Convolutional Neural Network (CNN) used for image classification as an example. These materials can be utilized in class for the teaching of convolution and help students have a good understanding of the related knowledge in artificial intelligence.

A Study on the Construction of Intelligent Learning Platform Model for Faith Education in the Post Corona Era (포스트 코로나 시대 신앙교육을 위한 지능형학습플랫폼 모형 구성 연구)

  • Lee, Eun Chul
    • Journal of Christian Education in Korea
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    • v.66
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    • pp.309-341
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    • 2021
  • The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

Flip Side of Artificial Intelligence Technologies: New Labor-Intensive Industry of the 21st Century (4차 산업혁명시대의 디지털 경공업)

  • Heo, Seokjae;Na, Seunguk;Han, Sehee;Shin, Yoonsoo;Lee, Sanghyun
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.5
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    • pp.327-337
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    • 2021
  • The paper acknowledges that many human resources are needed on the research and development (R&D) process of artificial intelligence (AI), and discusses on factors to consider on the current method of development. Enfin, in order to enhance efficiency of AI development, it seems possible through labour division of a few managers and numerous ordinary workers as a type of light industry. Thus, the research team names the development process of AI, which maximizes production efficiency by handling digital resources named 'data' with mechanical equipment called 'computer', as digital light industry of fourth industrial era. As experienced during the previous Industrial Revolution, if human resources are efficiently distributed and utilized, digital light industry would be able to expect progress no less than the second Industrial Revolution, and human resources development for this is considered urgent.

Foreign Language Self Study Learning System Using Generative Artificial Intelligence (생성형 인공지능을 활용한 외국어 작문 자가 학습 시스템)

  • Ji - Woong-Kim;Jeong - Joon Lee
    • Annual Conference of KIPS
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    • 2023.11a
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    • pp.587-588
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    • 2023
  • 최근 텍스트 생성형 인공지능인 ChatGPT가 화두가 되면서 생성형 인공지능을 이용한 서비스에 사람들의 관심이 높아졌다. 이를 활용하여 시간과 비용이 많이 드는 분야인 외국어 작문 학습을 자기 주도적으로 학습할 수 있을 것이라 조망하였다. 따라서 텍스트 생성형 인공지능인 ChatGPT API를 활용하여 사용자가 자기 주도적으로 외국어를 학습할 수 있는 방향성을 제시하고 더욱 쉽고 저렴한 비용으로 외국어를 익힐 수 있도록 하는 시스템을 개발한다.

A Study on Development and Application of Artificial Intelligence Education Program using Robot (로봇 활용 인공지능 교육 프로그램 개발과 적용에 관한 연구)

  • Yoo, Inhwan;Bae, Youngkwon;Park, Daeryoon;Ahn, Joongmin;Kim, Wooyeol
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.443-451
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    • 2020
  • In elementary school software education, a programming process is experienced through a simple problem solving process. And even this experience emphasizes that the problem-solving process is a CS Unplugged activity. However, CS Unplugged has a disadvantage in that it only learns the principles of computing, and the learner cannot experience real problem solving. In this study, a learning program using artificial intelligence robots was developed with the goal of cultivating the ability to solve problems encountered in the real life of elementary school students. Students could solve complex problems in real life from the point of view of artificial intelligence through the developed program, and increase their interest and understanding of artificial intelligence education through robot control.

Development of an Artificial Intelligence Integrated Korean Language Education Program

  • Dae-Sun Kim;Eun-Hee Goo
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.67-78
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    • 2024
  • Amidst the onset of the Fourth Industrial Revolution and the prominence of artificial intelligence, societal structures are undergoing significant changes. There is a heightened global interest in AI education for nurturing future talents. Consequently, this research aims to develop an AI-integrated Korean language curriculum for first-year high school students, utilizing the ADDIE model for instructional program development. To assess the program's effectiveness, pre-post assessments were conducted on future core competencies (Collaboration, Communication, Critical Thinking, Creativity) and knowledge information processing skills. The curriculum, spanning nine sessions and incorporating four small projects, sought to provide students with a new experience of AI-integrated Korean language education. As a result, students who participated in the program demonstrated improvement in future core competencies across all areas, and positive outcomes were observed in satisfaction levels and qualitative analysis. Through these findings, it is suggested that this program successfully integrates artificial intelligence into high school Korean language education, potentially contributing to the cultivation of future talents among students.

Distributed Autonomous Robotics System based on Classifier System and Artificial Immune Network (분류자 시스템과 인공 면역 네트워크에 기반한 자율 분산 로봇 시스템 개발)

  • 황철민;박창현;심귀보
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.85-88
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    • 2004
  • 본 논문에서는 인공 면역 네트워크와 분류자 시스템을 이용한 자율 분산 로봇 시스템을 제안한다. 시스템에서 각 로봇의 행동은 전역행동과 지역행동으로 구성된다. 전역행동은 작업을 찾고 수행하기 위해 필요한 환경을 조성하는데 필요한 전반적인 행동들을 결정하고, 지역 행동은 작업을 수행할 때 각 로봇들이 어떤 방식으로 동작하는가를 결정한다. 이때 전역 행동은 인공 면역 네트워크를 이용하여 결정되며 작업을 빠른 속도로 탐색하며 탐색한 작업 주위로 적절한 수의 로봇이 집합하도록 한다. 또한 지역 행동은 분류자 시스템을 이용하여 결정되며 작업을 수행하는데 적절한 로봇의 역할을 결정한다.

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YOLOv8-based Climbing Hold Extraction and Route Recommendation 2D Rendering System (YOLOv8 모델 기반 클라이밍 홀드 추출 및 경로 추천 2D 렌더링 시스템)

  • Jinwoo Kim;Hyeongjoon Seo;Jaemyung Lee;Farkhodov Khurshedjon;Rak Young Choi;Ki-Ryong Kwon
    • Annual Conference of KIPS
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    • 2024.10a
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    • pp.617-618
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    • 2024
  • 본 연구는 AI 기술을 이용해 클라이밍 홀드를 추출하고, 사용자가 선택한 홀드에 맞는 경로를 추천하여 시각적으로 렌더링하는 시스템을 개발하는 것을 목표로 한다. YOLOv8 모델을 활용해 홀드를 인식하고, 서버에서 경로를 분석하여 사용자에게 제공한다. 이를 통해 클라이밍 초보자와 숙련자 모두에게 안전하고 효율적인 등반 경로를 제시한다.

Expansion of Product Liability : Applicability of SW and AI (제조물책임 범위의 확장 : SW와 AI의 적용가능성)

  • KIM, Yun-Myung
    • Informatization Policy
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    • v.30 no.1
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    • pp.67-88
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    • 2023
  • The expansion of the scope of product liability is necessary because the industrial environment has changed following the enactment of the Product Liability Act. Unlike human-coded algorithms, artificial intelligence is black-boxed according to machine learning, and even developers cannot explain the results. In particular, since the cause of the problem by artificial intelligence is unknown, the responsibility is unclear, and compensation for victims is not easy. This is because software or artificial intelligence is a non-object, and its productivity is not recognized under the Product Liability Act, which is limited to movable property. As a desperate measure, productivity may be recognized if it is stored or embedded in the medium. However, it is not reasonable to apply differently depending on the medium. The EU revise the product liability guidelines that recognize product liability when artificial intelligence is included. Although compensation for victims is the value pursued by the Product Liability Act, the essence has been overlooked by focusing on productivity. Even if an accident occurs using an artificial intelligence-adopted service, however, it is desirable to present standards according to practical risks instead of unconditionally holding product responsibility.