• 산업융합연구
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• 제22권2호
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• pp.13-22
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• 2024

현대 학습자들은 배경, 학습 스타일, 능력 등에서 다양한 차이를 보인다. 하지만 모든 학습자에게 동일한 학습 내용을 전달하는 전통적 교육 방법은 이러한 학습자의 다양성을 충분히 고려하지 못한다. 따라서 개별 학습자의 특성에 따라 최적의 학습 경험을 제공하는 맞춤형 학습 시스템의 구현은 오늘날 에듀테크 시대에 더욱 중요해졌다. 본 논문은 증가하는 학습자 중심의 교육 요구에 따라 학습자의 특성, 관심사, 학습 이력 등을 종합적으로 분석할 수 있는 모델들을 파악한 후 이를 기반으로 맞춤형 학습 시스템을 설계했다. 본 시스템은 학습자의 학습 이력을 기반으로 학습자의 현재 수준과 목표에 맞춘 자기주도적 학습을 지원하기 위해 강점과 약점을 파악할 수 있도록 설계되었으며 이 과정에서 시스템의 설계 변경 없이 필요한 학습 요소들을 확장할 수 있도록 구성하였다. 본 연구를 통해 사용자 맞춤형 학습 시스템 구축에 필요한 주요 기반을 파악하고 맞춤형 학습을 지원하기 위한 시스템 아키텍처를 효과적으로 구축할 수 있다.

• International Journal of Computer Science & Network Security
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• 제24권8호
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• pp.21-31
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• 2024

This study investigates the user experience (UX) of first aid training using virtual reality (VR) technology. As VR continues to be adopted for educational and training purposes, it is important to understand how learners perceive and engage with this medium for developing critical skills, such as first aid. In this study, we developed a VR application called "VR First Aid" that includes training modules on three emergency scenarios: heatstroke, shock, and seizure. The application has both tutorial and hands-on training components. We conducted a UX study by administering a questionnaire to participants. The UX of learning through the VR application was then compared to using a traditional e-book format. Results indicate that participants perceived stronger internal behavior control with the e-book but reported better confirmation, engagement, enjoyment, and intention to use when training with the VR system. Gender differences were also explored, revealing that female participants expressed greater interest in learning through the VR platform compared to male participants. These findings provide insights into the strengths and limitations of VR-based first aid training compared to traditional methods. Implications for the design and deployment of VR training systems are discussed, with a focus on optimizing the learner experience and learning outcomes.

• 한국학교수학회논문집
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• 제18권2호
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• pp.223-240
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• 2015

본 논문의 목적은 미적분에 관한 보충학습을 요하는 이공계 대학생들을 위하여 공업수학의 벡터미적분 교육을 중심으로 개념적 이해와 계산 과정의 단계별 풀이를 보여주는 웹 기반 이러닝 콘텐츠를 설계 및 개발하는 것이다. 이를 위하여 먼저 수학교육용 소프트웨어에 관한 고찰을 하였으며 학교 수학에서 등장하는 문제해결의 과정을 규칙 재작성으로 처리함으로써 화이트박스 형태의 콘텐츠 제작에 관한 이론적 토대를 살펴보았다. 구체적으로 Mathematica의 패턴 매칭을 이용하여 미분과 적분 연산자를 구현하였고, 이를 벡터미적분에서 등장하는 매개변수화된 곡선에 대한 길이 구하기 문제에 적용함으로써 콘텐츠 개발의 예를 제시하였다. 튜토리얼 형태로 개발된 이러닝 콘텐츠는 단계별 풀이 과정이 나오는 실습하기 콘텐츠와 퀴즈 문제를 통하여 학습자의 과정을 진단해 주는 형성평가 모듈로 구성되었다. 끝으로 개발된 이러닝 콘텐츠의 특징과 이공계 대학생들의 수학에 관한 기초학력을 증진하는데 활용될 수 있는 장점을 살펴보았으며 향후 연구 방향을 제시하였다.

• 인지과학
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• 제30권1호
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• pp.1-30
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• 2019

인지는 더 이상 개인 내적인 과정으로 개념화 할 수 없으며 학습 또한 마찬가지이다. 협동 및 상호작용에 대한 정보처리적 이해는 아직 부족한 실정인데, 본 논문에서는 학습의 개념이 어떻게 변화해 왔는지 그리고 협동의 과정이 어떠한 정보처리 기제에 의해서 매개되는지 살펴보았다. 협동학습의 주요 인지적 기제로 자원 공유, 구성적 학습 활동의 촉진, 지식 공동 구성, 및 모니터링과 조절 지원을 들 수 있는데, 이들 기제는 학습자 집단을 둘러싼 동기적, 환경적 기제와 상호작용하면서 협동학습의 결과물을 만들어 내는데 기여한다. 테크놀로지의 발달은 협동의 기회를 더욱 확장하고 있는데, 테크놀로지가 협동학습에 제공하는 기능을 7개의 어포던스를 중심으로 살펴보았다. 협업에 대한 보다 정교한 이해를 바탕으로 할 때 협업에 따르는 비용을 줄이면서 협동이 제공하는 다양한 학습 효과를 누리는 것은 물론 협업을 지원하는 효과적인 도구를 개발하는 것이 가능해질 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.1-15
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• 2023

The aim of this study is to identify intelligent learning support functions in Learning Management System (LMS) to support university student learning activities during the transition from face-to-face classes to online learning. To accomplish this, we investigated the perceptions of students on the levels of importance and urgency toward learning support functions of LMS powered with Artificial Intelligent (AI) technology and analyzed the differences in perception according to student characteristics. As a result of this study, the function that students considered to be the most important and felt an urgent need to adopt was to give automated grading and feedback for their writing assignments. The functions with the next highest score in importance and urgency were related to receiving customized feedback and help on task performance processed as well as results in the learning progress. In addition, students view a function to receive customized feedback according to their own learning plan and progress and to receive suggestions for improvement by diagnosing their strengths and weaknesses to be both vitally important and urgently needed. On the other hand, the learning support function of LMS, which was ranked as low importance and urgency, was a function that analyzed the interaction between professors and students and between fellow students. It is expected that the results of this student needs analysis will be helpful in deriving the contents of learning support functions that should be developed as well as providing basic information for prioritizing when applying AI technology to implement learner-centered LMS in the future.

• 한국분말재료학회지
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• 제30권3호
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• pp.217-222
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• 2023

Machine learning-based data analysis approaches have been employed to overcome the limitations in accurately analyzing data and to predict the results of the design of Nb-based superalloys. In this study, a database containing the composition of the alloying elements and their room-temperature tensile strengths was prepared based on a previous study. After computing the correlation between the tensile strength at room temperature and the composition, a material science analysis was conducted on the elements with high correlation coefficients. These alloying elements were found to have a significant effect on the variation in the tensile strength of Nb-based alloys at room temperature. Through this process, a model was derived to predict the properties using four machine learning algorithms. The Bayesian ridge regression algorithm proved to be the optimal model when Y, Sc, W, Cr, Mo, Sn, and Ti were used as input features. This study demonstrates the successful application of machine learning techniques to effectively analyze data and predict outcomes, thereby providing valuable insights into the design of Nb-based superalloys.

• 정보교육학회논문지
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• 제21권2호
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• pp.231-245
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• 2017

본 연구를 통해 자석 및 자기장과 관련된 웹기반 과학학습 시뮬레이션들의 현황을 살펴보고, 시뮬레이션의 내용과 전략 및 디자인 측면에서 적절성을 평가하였다. 연구를 위해 과학학습 시뮬레이션 평가 기준을 고안하였으며, 초등교사 8명이 참여하여 자석 및 자기장 관련 시뮬레이션 14종을 평가 기준에 맞추어 평가하고 각 시뮬레이션의 특징을 기술하였다. 평가 결과를 바탕으로 시뮬레이션들을 상 그룹과 하 그룹으로 분류하였고, 상 그룹의 시뮬레이션에서 강점과, 하 그룹의 시뮬레이션에서 보완할 점들을 교수학습 내용, 교수학습 전략, 화면구성, 기술의 측면에 따라 분석하고 도출하였다. 연구 결과를 근거로 교수학습에 효과적인 자석 및 자기장 주제의 웹기반 시뮬레이션 개선을 위한 방안을 논의하였다.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.318-326
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• 2022

Marketing stress testing is a new method of identifying the company's strengths and weaknesses in a turbulent environment. Technically, this is a complex procedure, so it involves artificial intelligence and machine learning. The main problem is currently the development of methodological approaches to the development of the company's digital model, which will provide a framework for machine learning. The aim of the study was to identify and develop an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. This aim provided the company's activities to be considered as a set of elements (business processes, products) and factors that affect them (marketing environment). The article proposes an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. The proposed approach includes four main elements that are subject to parameterization: elements of the company's internal environment, factors of the marketing environment, the company' core competency and factors impacting the company. Matrices for evaluating the results of the work of expert groups to determine the degree of influence of the marketing environment factors were developed. It is proposed to distinguish between mega-level, macro-level, meso-level and micro-level factors depending on the degree of impact on the company. The methodological limitation of the study is that it involves the modelling method as the only one possible at this stage of the study. The implementation limitation is that the proposed approach can only be used if the company plans to use machine learning for marketing stress testing.

• 열처리공학회지
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• 제35권6호
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• pp.327-336
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• 2022

In this study, a model for automatically recognizing several steel parts through a camera before charging materials was developed under the assumption that the temperature distribution in the pre-air atmosphere was known. For model development, datasets were collected in random environments and factories. In this study, the YOLO-v5 model, which is a YOLO model with strengths in real-time detection in the field of object detection, was used, and the disadvantages of taking a lot of time to collect images and learning models was solved through the transfer learning methods. The performance evaluation results of the derived model showed excellent performance of 0.927 based on mAP 0.5. The derived model will be applied to the model development study, which uses the model to accurately recognize the material and then match it with the temperature distribution in the atmosphere to determine whether the material layout is suitable before charging materials.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.273-275
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• 2022

Deep Learning is used nowadays in Nuclei segmentation. While recent developments in theory and open-source software have made these tools easier to implement, expert knowledge is still required to choose the exemplary model architecture and training setup. We compare two popular segmentation frameworks, U-Net and Mask-RCNN, in the nuclei segmentation task and find that they have different strengths and failures. we compared both models aiming for the best nuclei segmentation performance. Experimental Results of Nuclei Medical Images Segmentation using U-NET algorithm Outperform Mask R-CNN Algorithm.