• 실천공학교육논문지
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• 제12권2호
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• pp.301-308
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• 2020

근래 다문화가족의 급증 및 코로나-19로 인한 원격수업 등 비대면교육의 지속으로 초등 저학년의 교육격차가 발생하고 있다는 우려가 있다. 특히, 초등 저학년에서는 우리 말을 읽고, 쓰고, 듣고, 말하는 능력이 정착이 되어야 한다는 점에서 중요성이 부각되고 있다. 따라서 이 연구에서는 최근 관심도가 높은 인공지능 도구를 활용함으로써 이해도를 높이고, 놀이를 통하여 흥미롭게 한글교육을 할 수 있는 콘텐츠를 개발하였다. 앞으로 인공지능 도구들이 초등 저학년 교과교육에서 활용할 수 있는 다양한 시도가 필요하다.

• 한국정보교육학회:학술대회논문집
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• 한국정보교육학회 2021년도 학술논문집
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• pp.233-237
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• 2021

4차 산업혁명이 도래함에 따라 초등학교 현장에서는 인공지능 교육에 대한 관심이 증가하고 있다. 인공지능 역량을 지닌 미래 인재를 기르기 위해서는 학교 현장에서 인공지능 교육이 적극적으로 이루어져야 한다. 2015 개정 교육과정에서는 기초적인 소프트웨어 교육을 하고 있지만 인공지능을 만들어내는 프로그래밍 과정을 문제해결 과정으로만 보는 경향이 있다. 하지만 하나의 인공지능을 만들 때에는 인공지능을 만드는 개발자의 가치가 투영된다. 따라서 SW교육 시 인공지능 가치 판단에 대한 내용을 다루어야 할 것이다. 본 연구는 전문가 집단을 대상으로 델파이 조사가 이루어진 점에 따라 제한점이 존재한다. 향후 이와 같은 제한점을 보완하기 위해 양적 연구가 진행되어야 할 것으로 판단된다.

• 정보교육학회논문지
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• 제24권5호
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• pp.443-451
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• 2020

초등학교 소프트웨어 교육에서는 간단한 문제해결 과정을 통하여 프로그래밍 과정을 경험하고 있다. 그리고 이러한 경험조차도 문제 해결 과정을 CS Unplugged 활동으로 하도록 강조하는 실정이다. 하지만 CS Unplugged는 컴퓨팅 원리의 습득에 그치고 학습자가 실제 문제 해결의 처리 경험을 하지 못한다는 단점이 존재한다. 본 연구에서는 초등학생들의 실제적 삶에서 부딪히는 문제들을 해결할 수 있는 역량을 기르는 것에 목표를 두고 로봇 활용 인공지능 교육 프로그램을 개발하였다. 프로그램을 적용한 결과, 학생들은 개발된 프로그램을 통하여 실생활의 복잡한 문제를 인공지능의 관점으로 해결하고, 로봇 제어를 통하여 인공지능 교육에 대한 흥미 및 이해도가 높아질 수 있었다.

• 정보교육학회논문지
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• 제25권6호
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• pp.927-934
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• 2021

인공지능은 우리의 삶에 점차 많은 부분을 차지하고 있으며, 발전하는 속도도 빨라지고 있다. 학생들의 컴퓨팅 사고력을 인공지능이 학습하는 방법대로 길러주는 것을 ACT(AI based Computational Thinking)라고 한다. ACT 중 패턴 인식은 문제를 효율적으로 해결하기 위해 필수적인 요소이다. 패턴 분석은 패턴 인식 과정의 일부로 볼 수 있다. 실제로 넷플릭스의 개인 맞춤 영화 추천, 반복된 증상을 분석하여 코로나 바이러스로 명명하는 것 등이 모두 패턴 분석의 결과이다. 패턴인식을 포함한 ACT의 중요성이 부각되는 것에 반면, 유치원과 초등학교 저학년을 대상으로 한 소프트웨어 교육은 국외에 비해 많이 부족한 실정이다. 따라서 본 연구에서는 유치원 학생들을 대상으로 하여 패턴 분석을 통한 인공지능 기반 컴퓨팅 사고력 계발을 위한 교재를 설계하고 개발하였다.

• Journal of Digestive Cancer Research
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• 제12권1호
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• pp.38-43
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• 2024

Artificial Intelligence (AI) is the intelligence of machines or software, in contrast to human intelligence. Generative AI technologies, such as ChatGPT, have emerged as valuable research tools that facilitate brainstorming ideas for research, analyzing data, and writing papers. However, their application has raised concerns regarding authorship, copyright, and ethical considerations. Many organizations of medical journal editors, including the International Committee of Medical Journal Editors and the World Association of Medical Editors, do not recognize AI technology as an author. Instead, they recommend that researchers explicitly acknowledge the use of AI tools in their research methods or acknowledgments. Similarly, international journals do not recognize AI tools as authors and insist that human authors should be accountable for the research findings. Therefore, when integrating AI-generated content into papers, it should be disclosed under the responsibility of human authors, and the details of the AI tools employed should be specified to ensure transparency and reliability.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.630-644
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• 2021

Educational data analysis is attracting increasing attention with the rise of the big data industry. The amounts and types of learning data available are increasing steadily, and the information technology required to analyze these data continues to develop. The early identification of potential dropout students is very important; education is important in terms of social movement and social achievement. Here, we analyze educational data and generate predictive models for student dropout using logistic regression, a decision tree, a naïve Bayes method, and a multilayer perceptron. The multilayer perceptron model using independent variables selected via the variance analysis showed better performance than the other models. In addition, we experimentally found that not only grades but also extracurricular activities were important in terms of preventing student dropout.

• 통합자연과학논문집
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• 제15권4호
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• pp.163-169
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• 2022

Currently, many universities are implementing software-oriented universities and artificial intelligence-oriented universities to foster software-oriented manpower. We are educating students to design and produce computational thinking and coding directly with their major knowledge. However, computer education is not easy for non-majors, and there are many difficulties in coding. The results of responses from 104 students from the College of Health Sciences and College of Social Management who took the liberal arts computer at University H were analyzed using SPSS 26.0 version. In the liberal arts computer class for non-majors, a PJBL-based class plan was proposed. The effectiveness of PJBL-based classes was confirmed through a questionnaire for the improvement of artificial intelligence liberal arts courses. As a result, PJBL-based education showed statistically significant results in terms of satisfaction, effectiveness, and self-efficiency of classes regardless of major.

• Korean Journal of Radiology
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• 제24권5호
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• pp.454-464
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• 2023

Objective: We aimed to investigate current expectations and clinical adoption of artificial intelligence (AI) software among neuroradiologists in Korea. Materials and Methods: In April 2022, a 30-item online survey was conducted by neuroradiologists from the Korean Society of Neuroradiology (KSNR) to assess current user experiences, perceptions, attitudes, and future expectations regarding AI for neuro-applications. Respondents with experience in AI software were further investigated in terms of the number and type of software used, period of use, clinical usefulness, and future scope. Results were compared between respondents with and without experience with AI software through multivariable logistic regression and mediation analyses. Results: The survey was completed by 73 respondents, accounting for 21.9% (73/334) of the KSNR members; 72.6% (53/73) were familiar with AI and 58.9% (43/73) had used AI software, with approximately 86% (37/43) using 1-3 AI software programs and 51.2% (22/43) having up to one year of experience with AI software. Among AI software types, brain volumetry software was the most common (62.8% [27/43]). Although 52.1% (38/73) assumed that AI is currently useful in practice, 86.3% (63/73) expected it to be useful for clinical practice within 10 years. The main expected benefits were reducing the time spent on repetitive tasks (91.8% [67/73]) and improving reading accuracy and reducing errors (72.6% [53/73]). Those who experienced AI software were more familiar with AI (adjusted odds ratio, 7.1 [95% confidence interval, 1.81-27.81]; P = 0.005). More than half of the respondents with AI software experience (55.8% [24/43]) agreed that AI should be included in training curriculums, while almost all (95.3% [41/43]) believed that radiologists should coordinate to improve its performance. Conclusion: A majority of respondents experienced AI software and showed a proactive attitude toward adopting AI in clinical practice, suggesting that AI should be incorporated into training and active participation in AI development should be encouraged.

• 한국정보시스템학회지:정보시스템연구
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• 제32권4호
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• pp.189-210
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• 2023

Purpose This study aims to investigate factors that positively influence the continuous Artificial Intelligence(AI) Learning Continuity of business major students. Design/methodology/approach To evaluate the impact of AI education, a survey was conducted among 119 business-related majors who completed a software/AI course. Frequency analysis was employed to examine the general characteristics of the sample. Furthermore, factor analysis using Varimax rotation was conducted to validate the derived variables from the survey items, and Cronbach's α coefficient was used to measure the reliability of the variables. Findings Positive correlations were observed between business major students' AI Learning Continuity and their AI Interest, AI Awareness, and Data Analysis Capability related to their majors. Additionally, the study identified that AI Project Awareness and AI Literacy Capability play pivotal roles as mediators in fostering AI Learning Continuity. Students who acquired problem-solving skills and related technologies through AI Projects Awareness showed increased motivation for AI Learning Continuity. Lastly, AI Self-Efficacy significantly influences students' AI Learning Continuity.

• International Journal of Precision Engineering and Manufacturing
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• 제2권3호
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• pp.27-33
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• 2001

The aim of the present work is to propose a model for Computer Aided programming of numerical Control lathe. This model is based on the concept by features. It has been developed in an Artificial Intelligence environment, that offers a rapidity as well as a precision for NC code elaboration. In this study a pre-processor has been elaborated to study the geometry of turning workpiece. This pre-processor is a hybrid system which combine a module of design by features and a module of features recognition for a piece provided from an other CAD software. Then, we have conceived a processor that is the heart of the CAD/CAM software. The main functions are to study the fixture of the workpiece, to choose automatically manufacturing cycles, to choose automatically cutting tools (the most relevant), to simulate tool path of manufacturing and calculate cutting conditions, end to elaborate a typical manufacturing process. Finally, the system generates the NC program from information delivered by the processor.