• 한국정보교육학회:학술대회논문집
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• 2004.01a
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• pp.413-421
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• 2004

지식 정보화 시대의 새로운 교육 패러다임의 변화에 따라 웹을 통하여 정보와 아이디어를 서로 공유할 수 있는 사회적 상호작용이 요구되고 있다. 이러한 사회적 상호작용을 증진시키기 위해서는 다양한 사회적 상호작용 도구를 제공할 수 있는 웹 기반협동학습 시스템이 필요하다. 따라서 이 논문에서는 사회적 상호작용을 증진시키기 위해서 웹 기반 협동학습 환경을 쉽게 구성할 수 있도록 재사용 가능한 협동학습객체 모형을 SCORM을 기반으로 설계하였다. 협동학습객체 모형을 필드와 메소드, 속성으로 구성하였다. 필드는 상호작용을 통해 발생된 상호작용 결과를 저장하기 위해 데이터 모델로 구현하였으며, 메소드는 상호작용 결과를 LMS에 전달하는 방법을 제공하기 위해 API 함수로 구현하였다. 또한 협동학습객체의 속성은 접근성, 다형성, 포장성, 제어성으로 구분하여 각각 베타데이터, 계열화, 패키지, 런치를 통해 구현하였다. 이러한 협동학습객체는 학습 내용과 결합하여 하나의 협동학습 활동을 구성하게 되고, 이렇게 구성된 협동학습 활동을 계열화함으로써 교수 학습 설계가 이루어진다.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.25-26
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• 2019

소셜 미디어(social media)가 급속히 발달하고 대중화되면서, 뮤지엄(museum)의 관람객은 시 공간의 제약 없이 뮤지엄의 콘텐츠를 향유하는 동시에, 전통적인 관람객의 역할을 넘어 매개자(mediator), 프로슈머(prosumer), 그리고 크리에이터(creator)로 활동하고 있다. 또한, 뮤지엄도 고유의 업무 수행에 다수 관람객의 참여를 유도하며 관람객과 적극적으로 소통하고 있다. 이러한 흐름 속에, 이화여자대학교박물관에서는 소셜 미디어를 기반으로 사전 설문조사를 진행하여 작품에 대한 설문 참여자의 반응을 수집한 후 이를 바탕으로 큐레이션에 대중의 선호도를 반영하는 '관람객 참여전시'를 개최하였다. 더 나아가 알고리즘 기반 전시 큐레이션 모델도 개발하였는데, 이 모델은 앞의 관람객 참여전시에서 얻은 데이터를 활용하여 컴퓨터가 일반 관람객의 개인적 취향에 부합하는 작품을 자동으로 추천하고, 이를 바탕으로 개별 관람객에게 '개인적으로 최적화된' 전시를 구성할 수 있는 기반을 제공한다. 본 논문은 이러한 이화여자대학교박물관의 최신 전시활동을 소개하며, 초연결, 초지능화의 시대에 관람객들이 뮤지엄에 다양하게 참여하고 함께 소통할 수 있는 방법을 모색하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.95-97
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• 2023

본 논문에서는 임베디드 기반의 다양한 센서를 활용한 드론의 비행기록장치 시스템 개발에 대한 새로운 아이디어를 제시한다. 이 시스템은 오픈소스 기반의 개발 보드인 라즈베리파이를 중심으로, 온도, 습도, 조도, 미세먼지 센서, 이산화탄소, 일산화탄소, 산소, 이산화질소, 아황산가스, 메탄가스, GPS, 고도 측정, IR 카메라, 카메라 모듈 센서 등 다양한 센서를 탑재하여 구성한다. 기존 드론은 주로 방역 및 방제 활동에 활용되었으나, 그 활동의 효과를 정밀하게 측정하고 분석하는 데에는 한계가 있었다. 그러나 이 논문에서 제안하는 임베디드 기반의 센서 구성은 이러한 한계를 극복할 수 있을 것으로 기대된다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.18-31
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• 2018

It is important to conduct various analyzes to evacuate occupants in advance, because the disaster can cause serious injury. Therefore, it is necessary to analyze all the predictable scenarios that may occur. In this study, we propose a method to analyze the evacuation of indoor disaster using activity - based transport model MATSim. We have developed the university building as target area and simulated about 5,000 occupants. The analysis scenarios are set as basic evacuation conditions, exit closures and emergency stair closures. As a result of analysis of each scenario, the evacuation time was analyzed to be about 5:40(340s) in the base scenario, increased by 15% in the scenario 2 and increased by 23% in scenario 3. As a result of this study, we suggest that it is important to manage illegal obstacles of emergency stairs for rapid evacuation. Therefore, this study can contribute to the effective disaster prevention strategy of the building.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.734-743
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• 2007

The KTX station is one of special generators that produce a lot of trips caused by special land use such as university, airport, and super shopping mall. Special generators need special attention in developing travel demand models since the standard trip generation and distribution model in the conventional four-step approach do not provide reliable estimates of their travel patterns. New modeling approach, activity-based model, considering travel behavior of person, seem to be more appropriate for those special generators. Thus, this study introduces a spatial-temporal activity-based approach and how activity-based approach can be applied to estimation of travel demand at KTX stations.

• International Area Studies Review
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• v.21 no.1
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• pp.303-324
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• 2017

Current methods to evaluate the performance of ROK military contingents to UN missions unnecessarily raises the issues of relevance, validity and reliability. Thus, this article aims to suggest how the result based evaluation (RBE) model which is widely adopted in the UN field missions as well as the international development community would be modified and applied to peace operation of the ROK contingent. As a result of the study, the model presents a framework that integrates the planning process and monitoring and evaluation with a logical framework, which entails a cycle of assessment of pre-deployment planning, monitoring and phased evaluation, and post-deployment evaluation. Secondly, according to measurement of RBE benchmarks to the present ROK's monitoring and evaluation system, factors in an evaluation unit and a logical framework approach are unmet or partly met to the benchmarks. In addition, ex-post impact evaluation has been rarely performed. Finally, the policy recommendations for resolution of the aforementioned challenges as well as a joint evaluation unit, participated by experts in a civilian, public, and a military domain are proposed.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.589-596
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• 2022

This study aims to investigate the effect of an educational gamification-based quiz on the recall of formulaic sequences (FS). The experiment involved 87 freshmen enrolled in general English classes at a university in Seoul. As material, EFL textbooks based on content from popular franchises, such as the Marvel Cinematic Universe, Twilight, and Harry Potter, were used. The experiment was carried out as follows: first, vocabulary learning, second, reading comprehension, and third, writing. The fourth activity proceeded differently in two groups. The experimental group used gamification-based quiz to practice FS, whereas the comparison group summarized the reading. FS was evaluated using meaning recall and form recall. Consequently, no difference was found between the groups on meaning recall tests of FS, but the experimental group had a significantly higher average score than the comparison group on the post-test on the form recall of FS.

• Communications of Mathematical Education
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• v.36 no.1
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• pp.59-72
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• 2022

The purpose of this study is to understand the characteristics of the mathematical modeling tasks and lesson designs developed by pre-service teachers based on the inherent awareness of mathematical modeling, considering the importance of creating a task to perform mathematical modeling activity and designing a lesson. As a result, the mathematical modeling tasks developed by pre-service teachers mainly presents an appropriate amount of information using real life contexts for the purpose of learning using concepts, and it showed a tendency to develop to the level of cognitive demand that required procedures with connections to understanding, meaning, or concepts. And most of the developed modeling task-based lessons showed a tendency to design warm-up activity, model-eliciting activity, and model-exploration activity. This result is due to the lack of experience of pre-service teachers in creating mathematical modeling tasks. Therefore, it is necessary to continuously provide opportunities for pre-service teachers to learn concepts or create mathematical modeling tasks intended for exploration according to various mathematical contents, thereby actively cultivating their ability to create modeling tasks in the course of training pre-service teachers. Furthermore, it is necessary to strengthen the expertise in mathematical modeling teaching and learning by providing opportunities to actually perform the mathematical modeling-based classes designed by pre-service teachers and to experience the process of reflecting on the lessons.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.121-127
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• 2023

The purpose of this pilot study is to examine the responses of middle school students to English learning after conducting English writing activities using DALL-E2, an image-generating artificial intelligence tool. To this end, an experimental class was conducted for 3 weeks for 15 middle school English learners, and the results are summarized as follows. First, as a result of a survey on English writing activities using DALL-E2, it was found that confidence, interest, and awareness of writing using artificial intelligence-based tools changed positively. In addition, it was confirmed that there was a statistically significant difference, which meant that learning using artificial intelligence had a positive effect on English writing and overall English learning. Second, as a result of analyzing the English writing activities using DALL-E2, core themes could be extracted into three (cognitive, affective, and psychodynamic characteristics), and the use and implementation of artificial intelligence-based DALL-E2 in English learning showed potential to increase learning interest, challenge, will, and desire in learning and ultimately contribute to enhancing productive skill.

• The Journal of the Convergence on Culture Technology
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• v.11 no.1
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• pp.411-419
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• 2025

This study explored the impact of generative AI-based entrepreneurship education readiness on entrepreneurial intention, with a focus on the mediating roles of entrepreneurial self-efficacy and teamwork satisfaction. Findings revealed that AI readiness and class satisfaction positively influenced self-efficacy and teamwork satisfaction. Notably, self-efficacy had a strong positive effect on entrepreneurial intention, whereas teamwork satisfaction showed no significant impact. These results highlight the critical role of generative AI in enhancing learners' confidence and entrepreneurial capabilities. Furthermore, self-efficacy was identified as a key determinant of entrepreneurial intention. The study provides actionable insights and practical implications for improving the effectiveness of AI-driven entrepreneurship education.