• Educational Technology International
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• 제6권1호
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• pp.81-101
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• 2005

Campus-based universities have provided face-to-face instruction traditionally. But recently, it is becoming a trend that they provide blended learning which combines e-learning and f2f instruction. Therefore, traditional university has been installing the ICT related convenience for the faculty and students to use easily to their classes. The purpose of this study is to develop quality indicators of ICT-related support for proper blended learning in traditional campus-based universities. This indicators are used for measuring the quality of ICT-related services at university level for quality education. To this end, first, we reviewed literature about quality indicators of university evaluation and e-learning. Second,we did case study. We selected and analyzed one university for a case, And we identified what elements are perceived important to faculty for more efficient use of technology to their class. Third, we summarized all this data and established the quality indicators framework of ICT-related components for blended learning in campus-based universities. Then, these indicators were revised after the expert evaluation. And then 10 experts and practitioners scored importance rating. Finally, we sum them up to 17 indicators and 48 sub-indicators in three phases (input, process, output). Among them, e-learning related organization or body, usability of Learning Management System, and quality assessment system got the highest scores. These indicators are supposed to contribute to measure the quality of ICT-related environment for blended learning and to provide informations about what is required for efficient blended learning in the campus-based universities.

• 한국간호교육학회지
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• 제29권3호
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• pp.234-246
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• 2023

Purpose: This study aimed to develop a case-based nursing education program using generative artificial intelligence and to assess its usability and applicability in nursing curriculums. Methods: The program was developed by following the five steps of the ADDIE model: analysis, design, development, implementation, and evaluation. A panel of five nursing professors served as experts to implement and evaluate the program. Results: Utilizing ChatGPT, six program modules were designed and developed based on experiential learning theory. The experts' evaluations confirmed that the program was suitable for case-based learning, highly usable, and applicable to nursing education. Conclusion: Generative artificial intelligence was identified as a valuable tool for enhancing the effectiveness of case-based learning. This study provides insights and future directions for integrating generative artificial intelligence into nursing education. Further research should be attempted to implement and evaluate this program with nursing students.

• 공학교육연구
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• 제26권4호
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• pp.36-46
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• 2023

This paper presents a case study and online-offline (hybrid) course structure for project-oriented community-based service learning in order to solve real-world problems for society. It examines social issues and conduct student projects to develop solutions that can generate sustainable value. This course helps students to use their major knowledge to assess and solve the problems faced by the local community. The outcomes of this course conducted via online lectures and offline project activities are discussed. The operation of this blended type of social problem-solving course is also stated.

• 공학교육연구
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• 제25권2호
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• pp.13-21
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• 2022

In many existing studies, the analyses on the application and effect of the project-based learning model (PBL), a student-centered teaching and learning strategy, have been emphasized and carried out in various majors and courses. This case study analyzes the effects of applying a project-based learning model to the engineering accounting course for engineering students in 2021 in the context of the COVID-19 pandemic, compared with the offline course in 2019 and the simple online course in 2020. Project team consisting of 2-3 students carried out online collaborative learning activities for solving open-ended problems through the 5-step PBL procedure including presenting the final result. Except for this online PBL application in 2021, textbooks, lecture contents, assignments, and tests were implemented the same for each semester for three years. Through lecture evaluation and survey by students, the online PBL application semester showed higher effects in inducing student-centered learning, lecture satisfaction, and student competency improvement compared to the non-applying semesters, further, it was evaluated that the online PBL application to the course and evaluation method were more appropriate than other semesters. It is expected that the online PBL method and operation procedure applied in this study can be utilized as a best practice for the design and operation of various online courses for student-centered collaborative learning activities and educational effects.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.47-49
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• 2022

Robot navigation has seen a major improvement since the the rediscovery of the potential of Artificial Intelligence (AI) and the attention it has garnered in research circles. A notable achievement in the area was Deep Learning (DL) application in computer vision with outstanding daily life applications such as face-recognition, object detection, and more. However, robotics in general still depend on human inputs in certain areas such as localization, navigation, etc. In this paper, we propose a study case of robot navigation based on deep reinforcement technology. We look into the benefits of switching from traditional ROS-based navigation algorithms towards machine learning approaches and methods. We describe the state-of-the-art technology by introducing the concepts of Reinforcement Learning (RL), Deep Learning (DL) and DRL before before focusing on visual navigation based on DRL. The case study preludes further real life deployment in which mobile navigational agent learns to navigate unbeknownst areas.

• 디지털융복합연구
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• 제19권11호
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• pp.373-379
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• 2021

본 연구는 블랜디드러닝 융합 사례기반학습이 간호대학생의 학습전략, 비판적 사고성향 및 학업적 자기효능감에 미치는 효과를 규명하기 위해 시도되었다. 단일군 사전-사후 설계로 23명의 간호대학생을 대상으로 하였다. 자료수집은 2021년 3월 2일부터 4월 30까지로 수집된 자료는 SPSS/WIN 23.0을 이용하여 분석하였다. 연구결과 블랜디드러닝융합 사례기반학습 적용 후 학습전략(t=-2.43, p=.019)과 하위요인인 인지전략(t=-2.22, p=.031), 메타전략(t=-2.59, p=.013), 자원관리전략(z=-2.46, p=.014)이 유의하게 증가하였다. 비판적 사고성향(t=-1.14, p=.262)과 학업적 자기효능감(t=-.34, p=.734)은 증가하였으나 통계적으로 유의하지 않았다. 결론적으로 블랜디드러닝 융합 사례기반학습이 간호대학생의 학습전략을 향상시키는 효과적인 교육 프로그램임이 확인되었다. 추후 블랜디드러닝 융합 사례기반 학습이 비판적 사고성향과 학업적 자기 효능감을 향상시킬 수 있는 프로그램 개발 및 효과검증이 필요하다.

• 대한건축학회논문집:계획계
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• 제34권3호
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• pp.61-72
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• 2018

This study pursued to obtain 3 consecutive purposes. First, a conceptual model for comparing 3 constructivist teaching and learning strategies( problem-based learning[$P_bBL$], case-based learning[CBL] and project-based learning[$P_jBL$]) was developed. Relationships of these constructivist strategies with the development of expertise for learners were discussed. Second, specific differences between $P_bBL$, CBL and $P_jBL$ as applied in architectural design courses were analyzed under each of the teaching and learning category. Some analytical indexes were developed by content analysis, which are applicable effectively to reveal the differences. Based on the previous findings, third, a set of strategic guidelines for use in class were made and suggested in order to develop and improve expertise in architectural design. These guidelines were largely targeted for university design courses as well as education or reeducation of practicing architects. Expecially, combined application of $P_bBL$, CBL and $P_jBL$ was hypothesized and suggested as class management guidelines. In sum, a variety of $P_bBL$ problems, CBL cases and $P_jBL$ projects should be developed for expecting audience based on design subjects and tasks. As working domains of practicing architects, exploring/analyzing, understanding/making applications, and criticizing/self-reflecting should be considered in the development process.

• 한국융합학회논문지
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• 제11권8호
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• pp.351-360
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• 2020

본 연구는 사례기반 및 코넬식 노트 활용법을 간호학 전공기초 과목인 인체해부학 교육에 적용하여 간호대학생들의 자기주도학습 능력, 비판적 사고 성향과 팀워크에 미치는 효과를 측정하기 위해 시도된 혼합연구방법이다. 인체해부학 교과목 이수자 중 학습부진 학생 34명을 대상으로 수강 전후 설문조사와 사례기반 및 코넬식 노트 활용에 대한 면담을 하였다. 자료분석에 양적연구는 SPSS/WIN 21.0을 이용하여 빈도, paired t-test, Pearson's correlation coefficients으로 분석하였고, 질적연구는 내용분석을 시행하였다. 연구결과 학습부진 간호대학생의 자기주도학습 능력(t=-9.69, p<.001), 비판적 사고 성향(t=-7.75, p<.001)과 팀워크(t=-12.43, p<.001)가 유의하게 증가하였다. 또한 자기주도학습 능력, 비판적 사고 성향과 팀워크 간에 유의한 상관관계가 있었다. 결론적으로 사례기반 및 코넬식 노트를 적용한 학습법은 인체해부학 수업에 효과적이며, 추후 타 교과목에서의 사례기반학습 적용과 코넬식 노트 활용에 대한 지속적인 연구가 필요하다.

• 한국응급구조학회지
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• 제17권2호
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• pp.77-87
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• 2013

Purpose : The purpose of this study was to develop a scenario and to evaluate the students by simulation-based learning of acute abdominal pain case in an emergency unit. The expert group of simulation developed the scenario based on actual abdominal pain by medical treatment records. Methods : Scenario was developed to evaluate the simMan3G simulation-based learning. The scenario was used in 2013 with ten groups of fourth grade 50 nursing students who voluntarily participated in the simulation class. Results : The nursing students were able to express nursing knowledge, learning attitude and self-efficacy. The simulation-based scenario proved to be very effective to students' skill training. The performance of nursing practice through simulation class made the nursing students more confident with patient care. Conclusion : Simulation-based learning was found to be the most effective curriculum to the nursing students and made the students satisfied and confident. So the simulation-based learning would be helpful to other students including paramedic students and medical school students.

• 지능정보연구
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• 제25권3호
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• pp.239-251
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• 2019

본 논문은 학습데이터의 크기에 따른 사례기반추론기법이 주가예측력에 어떻게 영향을 미치는지 살펴본다. 삼성전자 주가를 대상을 학습데이터를 2000년부터 2017년까지 이용한 경우와 2015년부터 2017년까지 이용한 경우를 비교하였다. 테스트데이터는 두 경우 모두 2018년 1월 1일부터 2018년 8월 31일까지 이용하였다. 시계 열데이터의 경우 과거데이터가 얼마나 유용한지 살펴보는 측면과 유사사례개수의 중요성을 살펴보는 측면에서 연구를 진행하였다. 실험결과 학습데이터가 많은 경우가 그렇지 않은 경우보다 예측력이 높았다. MAPE을 기준으로 비교할 때, 학습데이터가 적은 경우, 유사사례 개수와 상관없이 k-NN이 랜덤워크모델에 비해 좋은 결과를 보여주지 못했다. 그러나 학습데이터가 많은 경우, 일반적으로 k-NN의 예측력이 랜덤워크모델에 비해 좋은 결과를 보여주었다. k-NN을 비롯한 다른 데이터마이닝 방법론들이 주가 예측력 제고를 위해 학습데이터의 크기를 증가시키는 것 이외에, 거시경제변수를 고려한 기간유사사례를 찾아 적용하는 것을 제안한다.