• 공학교육연구
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• 제25권6호
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• pp.3-13
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• 2022

This study aims to develop and implement extra-curricular program applying project-based learning (PBL) and to find out its effectiveness. The research was conducted from March 2021 to December 2021 according to the ADDIE model. Surveys, t-test and descriptive statistics were also conducted. The results of the study are as follows. First, project-based learning was applied to the extra-curricular program by reflecting the characteristics of students of University A and the requirements of the person in charge of the teaching and learning center. Second, project tasks related to education of universities were proposed. Third, the programs were designed as three common courses and four consulting courses. Fourth, the program was conducted with 32 students for two months. Fifth, the post-test results of problem-solving skills rose to 0.9 points compared to the pre-test but there was no significant difference, while the post-test results of communication skills were 0.5 points lower than before and statistically significant. Sixth, the satisfaction survey result was high with a rating of 4.59. Lastly, educational implications are also discussed.

• 디지털융복합연구
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• 제19권10호
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• pp.29-38
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• 2021

목적: 이러닝 활성화를 위해 여러 방식의 LMS와 접목하여 연동 가능한 최적의 에듀테크 교수학습 플랫폼 모형을 설계한 연구이다. 방법: 이를 위해 사이버대학교와 일반대학교의 4차 산업기술에서 활용 가능한 이러닝 시스템을 횡단적으로 내용분석 하였다. 결과: 사이버대학교에서는 전적으로 LMS에 의존하였고, 일반대학교에서는 LMS 이외에도 구글 클래스룸, 줌 비디오 커뮤니케이션, 유튜브 등 교수별 각기 다른 에듀테크 방법을 보완 활용하고 있어, LMS에 구글 및 유튜브 등 메타데이터를 공유할 수 있도록 최소한의 알고리즘 매핑을 제공하는 것이 에듀테크 교수학습 플랫폼 모형에 유의미할 것으로 보았다. 이에 본 연구는 LMS 기반 에듀테크 교수학습 플랫폼 모형을 통해 교수법 향상과 학업성취도 향상에 기여할 것으로 사료된다.

• 공학교육연구
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• 제17권2호
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• pp.11-24
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• 2014

The purpose of this study is to develop a teaching-learning model of convergence project based on team teaching. Based on development research methodology which explored a university case, the teaching-learning model was developed including three phases such as preparation, planning, and implementation & evaluation. The preparation phase has three steps as follows: to organize team teaching faculty; to develop convergence projects cooperated by industry and university; and to design instructions based on supporting convergence projects. The last step of preparation phase consists of five design activities of: (1) instructions and teaching contents; (2) communication channel among faculty members; (3) feedback system on students' performance; (4) tools to support learners' activity; and (5) evaluation system. The planning phase has two steps to analyze learners and to introduce and modify instruction and themes of convergence projects. The implementation & evaluation phase includes five steps as bellow: (1) to organize project teams and match teams with faculty members; (2) to do team building and assign duties to students of a team; (3) to provide instruction and consulting to teams; (4) to help teams to conduct projects through creative problem solving; and (5) to design mid-term/final presentation and evaluation. Lastly, the research implications and limitations were discussed for future studies.

• ETRI Journal
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• 제31권4호
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• pp.419-428
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• 2009

A question answering (QA) system can be built using multiple QA modules that can individually serve as a QA system in and of themselves. This paper proposes a learnable, strategy-driven QA model that aims at enhancing both efficiency and effectiveness. A strategy is learned using a learning-based classification algorithm that determines the sequence of QA modules to be invoked and decides when to stop invoking additional modules. The learned strategy invokes the most suitable QA module for a given question and attempts to verify the answer by consulting other modules until the level of confidence reaches a threshold. In our experiments, our strategy learning approach obtained improvement over a simple routing approach by 10.5% in effectiveness and 27.2% in efficiency.

• Asia pacific journal of information systems
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• 제29권4호
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• pp.789-816
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• 2019

Text classification is a challenging task, especially when dealing with a huge amount of text data. The performance of a classification model can be varied depending on what type of words contained in the document corpus and what type of features generated for classification. Aside from proposing a new modified version of the existing algorithm or creating a new algorithm, we attempt to modify the use of data. The classifier performance is usually affected by the quality of learning data as the classifier is built based on these training data. We assume that the data from different domains might have different characteristics of noise, which can be utilized in the process of learning the classifier. Therefore, we attempt to enhance the robustness of the classifier by injecting the heterogeneous data artificially into the learning process in order to improve the classification accuracy. Semi-supervised approach was applied for utilizing the heterogeneous data in the process of learning the document classifier. However, the performance of document classifier might be degraded by the unlabeled data. Therefore, we further proposed an algorithm to extract only the documents that contribute to the accuracy improvement of the classifier.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권7호
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• pp.1774-1794
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• 2024

In the field of environmental sensing, it is necessary to develop radio planning techniques for the next generation Internet of Things (IoT) networks over mixed terrains. Such techniques are needed for smart remote monitoring of utility supplies, with links situated close to but out of range of cellular networks. In this paper, a three-dimension (3-D) geometric optimization algorithm is proposed, considering the positions of edge IoT devices and antenna coupling factors. Firstly, a multi-level single linkage (MLSL) iteration method, based on geometric objectives, is derived to evaluate the data rates over ISM 915 MHz channels, utilizing optimized power-distance profiles of continuous waves. Subsequently, a federated learning (FL) data selection algorithm is designed based on the 3-D geometric positions. Finally, a measurement example is taken in a meadow biome of the Mexican Colima district, which is prone to fluvial floods. The empirical path loss model has been enhanced, demonstrating the accuracy of the proposed optimization algorithm as well as the possibility of further prediction work.

• Human Ecology Research
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• 제52권6호
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• pp.669-682
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• 2014

The purpose of this study is to present a practical class design model that applies the problem-based learning (PBL) method to the subject of home economics. To begin with, a specific class model example was developed by conducting thorough document research and expert consulting. Two modules, named "Click! Global Leisure Environment" and "Happy Leisure Product Launching" were presented as the PBL questions. The case study focused upon in this research is an elective course called "Leisure Culture and Life Management". The 21 students enrolled in this course were considered in this study. Two teaching methods, namely a face-to-face teaching method and a web-based system "Snowboard" teaching method, were used to run the class. The research results are as follows: first, theoretical research and program development and demonstration were practiced with five different age groups: childhood, adolescence, university student, middle age, and senescence. Then, selfevaluation, peer evaluation, and group evaluation were conducted to motivate the students. Finally, a class evaluation was conducted by questioning the lecturer, who ranked well, scoring higher than or equal to 4.0 points out of 5.0 on all the questions. Through the PBL method, students showed an improved study attitude with more proactive participation in the class, they strengthened their communication skills and created a synergy with their team members. This study has significant meaning because it is the first research to apply the PBL method to home economics. Therefore, we expect other curricula to apply PBL and fully utilize this teaching method as well in the future.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• 디지털융복합연구
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• 제17권12호
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• pp.171-179
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• 2019

본 연구는 조직에서 지식의 습득이 창의성에 미치는 영향을 확인하고자 하였다. 지식의 습득과 관련된 변수 중 학습지향성을 선정하여 이를 통해 구성원이 창의성을 발현하는 과정에 대해 분석하였다. 구체적으로 학습지향성, 전문지식, 창의적 사고능력의 매개 과정과 이들 간의 관계에서 동기의 조절효과를 실증분석하였다. 이를 위해 문헌연구를 통해 연구모형 및 가설을 설정하였고, 대구·경북에서 제조업 종사자을 대상으로 296부의 설문지를 배포·회수하여 가설을 검증하였다. 계층적 회귀분석을 통한 검증 결과, 학습지향성은 창의적사고능력에 긍정적인 영향을 미치고 전문지식은 매개효과가 있는 것을 확인하였다. 그리고 이러한 매개 관계에서 동기의 조절효과를 확인하였다. 이러한 연구결과는 창의성의 발현에 대해 구성요소의 관계를 보다 상세하게 확인하고, 학습지향성이 미치는 영향에 대해 규명함으로써 시사성이 있다고 할 수 있다. 즉, 지식의 함양을 통해 창의성이 발현되는 과정을 설명함으로써 조직 관리 방안에 가이드라인을 제공할 수 있을 것이다.

• 한국전자거래학회지
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• 제22권4호
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• pp.159-173
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• 2017

기술력 기반의 중소벤처기업에 대한 기술금융 지원을 위해 정부는 2014년 7월부터 기술보증기금 및 일정 자격을 갖춘 민간 기술신용평가사에게 일종의 기술력 등급평가인 기술신용평가를 실시하여 은행의 여신에 활용토록 하였다. 본 논문에서는 최근까지의 기술신용평가 현황 및 한국신용정보원에서 축적하고 있는 기술평가 관련 가용 지표들에 대한 선행 연구를 개략적으로 살펴본 후 기술평가등급점수에 유의적인 영향을 미치는 지표(indicator)를 통상적인 다중회귀기법으로 탐색할 것이다. 본 논문의 관심 대상인 지표 별 등급 영향도와 모형의 적합도는 대표적인 기계학습 분류기(classifier)인 일반화가속모형(Generalized Boosting Model; GBM)을 적용하여 분석하였는 바, 주요 지표를 독립변수(feature)로 투입하여 지표의 상대적 중요성 및 분류 정확도를 산출하였다. 분석결과 회귀모형과 기계학습 모형 간 지표별 상대적인 중요도는 크게 차이나지 않는 것으로 분석되었으나, GBM 모형의 경우 회귀모형에 비해서 이노비즈인증, 연구소 및 연구개발전담부서 보유, 특허등록건수, 벤처확인 지표 등 기술개발역량이 상대적으로 기술등급에 더 큰 영향을 미치는 것으로 분석되었다.