• Title/Summary/Keyword: AI convergence education

Search Result 198, Processing Time 0.023 seconds

An Artificial Intelligence Ethics Education Model for Practical Power Strength (실천력 강화를 위한 인공지능 윤리 교육 모델)

  • Bae, Jinah;Lee, Jeonghun;Cho, Jungwon
    • Journal of Industrial Convergence
    • /
    • v.20 no.5
    • /
    • pp.83-92
    • /
    • 2022
  • As cases of social and ethical problems caused by artificial intelligence technology have occurred, artificial intelligence ethics are drawing attention along with social interest in the risks and side effects of artificial intelligence. Artificial intelligence ethics should not just be known and felt, but should be actionable and practiced. Therefore, this study proposes an artificial intelligence ethics education model to strengthen the practical ability of artificial intelligence ethics. The artificial intelligence ethics education model derived educational goals and problem-solving processes using artificial intelligence through existing research analysis, applied teaching and learning methods to strengthen practical skills, and compared and analyzed the existing artificial intelligence education model. The artificial intelligence ethics education model proposed in this paper aims to cultivate computing thinking skills and strengthen the practical ability of artificial intelligence ethics. To this end, the problem-solving process using artificial intelligence was presented in six stages, and artificial intelligence ethical factors reflecting the characteristics of artificial intelligence were derived and applied to the problem-solving process. In addition, it was designed to unconsciously check the ethical standards of artificial intelligence through preand post-evaluation of artificial intelligence ethics and apply learner-centered education and learning methods to make learners' ethical practices a habit. The artificial intelligence ethics education model developed through this study is expected to be artificial intelligence education that leads to practice by developing computing thinking skills.

A Study on the Development of Industrial Field Technical Education Programs Integrating Robotics and Artificial Intelligence

  • Yong-Kwan Kwon
    • Journal of the Korea Society of Computer and Information
    • /
    • v.29 no.8
    • /
    • pp.209-221
    • /
    • 2024
  • The purpose of this study is to develop technical education programs that integrate robotics and artificial intelligence for employees in the robotics industry. To achieve this, the current status of robotics education programs for employees at domestic robotics institutions was investigated, and a demand survey on integrated robotics and AI education was conducted for domestic robotics companies. Based on the results of the demand survey, a robotics and AI integration education program was developed, and the contents of the designed curriculum and the survey results were presented. The developed education program was applied to the actual industry, and through evaluations of participant satisfaction and learning effectiveness, it was confirmed that the program can be effectively utilized in the industry. Suggestions for further research were also made.

Educational Model for Artificial Intelligence Convergence Education (예비 교사의 인공지능 융합 수업 전문성 함양을 위한 교육 모델 제안)

  • Seong-Won Kim
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2023.01a
    • /
    • pp.229-231
    • /
    • 2023
  • 테크놀로지의 발달에 따라 수업에서 테크놀로지의 도입이 증가하고 있다. 테크놀로지는 학교 현장에 도입되어서, 교수-학습 형태의 변화와 교육 환경의 혁신을 이끌고 있다. 이에 따라 수업에서 테크놀로지 중요성은 더욱 증가하였으며, 예비 교사의 교육 모델에서 테크놀로지 지식을 함양하기 위한 노력이 이어졌다. 이에 따라 Mishra and Koehler(2006)의 TPACK 모델을 활용한 교육이 활발하게 이루어지고 있다. 본 연구에서는 TPACK 모델을 활용하여 예비 교사의 인공지능 융합 수업 전문성을 함양하기 위한 교육 모델을 개발하였다. 개발한 교육 모델은 브레인스토밍, 협력, 탐색(TPACK, AI, 교육과정, 교육적 맥락, 수업 사례), 수업 설계, 마이크로티칭, 수업 비평, 수업 성찰을 포함하였다. 본 연구에서 개발한 인공지능 융합 TPACK 교육 모델을 바탕으로 예비 교사의 인공지능 융합 수업 전문성 변화를 분석하는 후속 연구가 필요하다.

  • PDF

In the Digital Big Data Classroom Reality and Application of Smart Education : Learner-Centered Education using Edutech (디지털 빅데이터 교실에서 스마트교육의 실제와 활용 : 에듀테크를 활용한 학습자 중심 교육)

  • Kim, Seong-Hee
    • Journal of Korea Entertainment Industry Association
    • /
    • v.15 no.4
    • /
    • pp.279-286
    • /
    • 2021
  • In this study, we looked at the appearance of Edutech, which is being put into the educational field after Corona 19, with the advent of the 4th industrial revolution. In the era of the 4th industrial revolution, the infrastructure, data, and service of Smart Stick that actively utilized ICT became the main pillars of smart education. In particular, smart education is being implemented through e-learning, smart learning, and edutech, and on this basis, it has become possible through the expansion and use of the Internet and computers, the dissemination of smart devices, and a software foundation using big data. Based on this, it was confirmed that Edutech is being implemented through the establishment of a quarantine safety net, a learning safety net, and a care safety net for individual learners and safe life based on artificial intelligence. Lastly, in order for edutech education using big data to become a discourse for everyone, it is necessary to consider artificial intelligence and ethics in the use and application of edutech.

A Study on the Effectiveness of Algorithm Education Based on Problem-solving Learning (문제해결학습의 알고리즘 교육의 효과성 연구)

  • Lee, Youngseok
    • Journal of Convergence for Information Technology
    • /
    • v.10 no.8
    • /
    • pp.173-178
    • /
    • 2020
  • In the near future, as artificial intelligence and computing network technology develop, collaboration with artificial intelligence (AI) will become important. In an AI society, the ability to communicate and collaborate among people is an important element of talent. To do this, it is necessary to understand how artificial intelligence based on computer science works. An algorithmic education focused on problem solving and learning is efficient for computer science education. In this study, the results of an assessment of computational thinking at the beginning of the semester, a satisfaction survey at the end of the semester, and academic performance were compared and analyzed for 28 students who received algorithmic education focused on problem-solving learning. As a result of diagnosing students' computational thinking and problem-solving learning, teaching methods, lecture satisfaction, and other environmental factors, a correlation was found, and regression analysis confirmed that problem-solving learning had an effect on improving lecture satisfaction and computational thinking ability. For algorithmic education, if you pursue a problem-solving learning technique and a way to improve students' satisfaction, it will help students improve their problem-solving skills.

Data Framework Design of EDISON 2.0 Digital Platform for Convergence Research

  • Sunggeun Han;Jaegwang Lee;Inho Jeon;Jeongcheol Lee;Hoon Choi
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.8
    • /
    • pp.2292-2313
    • /
    • 2023
  • With improving computing performance, various digital platforms are being developed to enable easily utilization of high-performance computing environments. EDISON 1.0 is an online simulation platform widely used in computational science and engineering education. As the research paradigm changes, the demand for developing the EDISON 1.0 platform centered on simulation into the EDISON 2.0 platform centered on data and artificial intelligence is growing. Herein, a data framework, a core module for data-centric research on EDISON 2.0 digital platform, is proposed. The proposed data framework provides the following three functions. First, it provides a data repository suitable for the data lifecycle to increase research reproducibility. Second, it provides a new data model that can integrate, manage, search, and utilize heterogeneous data to support a data-driven interdisciplinary convergence research environment. Finally, it provides an exploratory data analysis (EDA) service and data enrichment using an AI model, both developed to strengthen data reliability and maximize the efficiency and effectiveness of research endeavors. Using the EDISON 2.0 data framework, researchers can conduct interdisciplinary convergence research using heterogeneous data and easily perform data pre-processing through the web-based UI. Further, it presents the opportunity to leverage the derived data obtained through AI technology to gain insights and create new research topics.

A Study on the Development of Health Care Service Platform for Chronic Patients Based on AI Chatbot Using Personal Life Log (개인 라이프로그를 활용한 AI 챗봇 기반 만성질환자 건강관리서비스 플랫폼 개발에 대한 연구)

  • So-Jeong Byun;Mun-Sung Kim;Hyong-Shik Kim;Seung-Hwan Byun
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2023.07a
    • /
    • pp.309-311
    • /
    • 2023
  • 본 논문에서는 만성질환자 건강관리서비스 플랫폼 개발을 위항여 건강측정기 모바일 연계기술 개발 및 적용하고 IoT 기반 생체정보 획득 및 라이프로그 건강관리 플랫폼 API 연계 기술을 통하여 지역 만성질환자를 위한 언택트 헬스 모니터링 플랫폼 개발을 수행하였다. 해당 시스템을 통하여 지역 보건소 협력 및 가족 중심 만성질환자 입체적 건강관리 모니터링 시스템 개발에 적용하고 IoT 장비 인터페이스기술, 개인 건강관리기술, 플랫폼 운영 및 구현기술, 데이터 관리기술 개발을 통하여 효율적으로 개인 라이프로그를 활용할 수 있도록 하였으며, 효율적인 관리를 위하여 AI 챗봇 서비스 시스템을 통한 효율성을 극대화를 추진하였다. 본 논문에서는 개인 라이프로그를 활용한 AI 챗봇 기반 만성질환자 건강관리서비스 플랫폼을 구현하여 만성질환자에 대한 서비스를 제공하고 만족도를 실증하여 서비스의 우수함을 입증하였다.

  • PDF

The Impact of Speech-To-Text-based Class on Learners' Cognitive Abilities

  • HyunMin Kang;SunKwan Han
    • Journal of the Korea Society of Computer and Information
    • /
    • v.29 no.1
    • /
    • pp.287-293
    • /
    • 2024
  • This research studied the cognitive impact of classes using artificial intelligence on aviation technical school students. First, we developed a class consisting of a class based on traditional presentation materials and a class composed of speech-to-text (STT)-based artificial intelligence materials. A 133 students from an aviation education institution participated in two types of classes. We measured students' cognitive load and Mind Wandering test results before and after class, and conducted an achievement evaluation. As a result of the test analysis, we confirmed that extraneous cognitive load was reduced, content concentration increased, and achievement improved. In the future, we hope that AI-based STT classes will be widely used in schools that teach technology.

A Study on the Recognition of English Pronunciation based on Artificial Intelligence (인공지능 기반 영어 발음 인식에 관한 연구)

  • Lee, Cheol-Seung;Baek, Hye-Jin
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.16 no.3
    • /
    • pp.519-524
    • /
    • 2021
  • Recently, the fourth industrial revolution has become an area of interest to many countries, mainly in major advanced countries. Artificial intelligence technology, the core technology of the fourth industrial revolution, is developing in a form of convergence in various fields and has a lot of influence on the edutech field to change education innovatively. This paper builds an experimental environment using the DTW speech recognition algorithm and deep learning on various native and non-native data. Furthermore, through comparisons with CNN algorithms, we study non-native speakers to correct them with similar pronunciation to native speakers by measuring the similarity of English pronunciation.

Validation of the effectiveness of AI-Based Personalized Adaptive Learning: Focusing on basic math class cases (인공지능(AI) 기반 맞춤형 학습의 효과검증: 기초 수학수업 사례 중심으로)

  • Eunae Burm;Yeol-Eo Chun;Ji Youn Han
    • Journal of Internet of Things and Convergence
    • /
    • v.9 no.3
    • /
    • pp.35-43
    • /
    • 2023
  • This study tried to find out the applicability and effectiveness of the AI-based adaptive learning system in university classes by operating an AI-based adaptive learning system on a pilot basis. To this end, an AI-based adaptive learning system was applied to analyze the operation results of 42 learners who participated in basic mathematics classes, and a survey and in-depth interviews were conducted with students and professors. As a result of the study, the use of an AI-based customized learning system improved students' academic achievement. Both instructors and learners seem to contribute to improving learning performance in basic concept learning, and through this, the AI-based adaptive learning system is expected to be an effective way to enhance self-directed learning and strengthen knowledge through concept learning. It is expected to be used as basic data related to the introduction and application of basic science subjects for AI-based adaptive learning systems. In the future, we suggest a strategy study on how to use the analyzed data and to verify the effect of linking the learning process and analyzed data provided to students in AI-based customized learning to face-to-face classes.